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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/104_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/104_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..6dcad964f2989e0d0cf47acae69290f30713c793
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/104_data/wts32.txt
@@ -0,0 +1,20160 @@
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/109_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/109_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..553150ceab04db8c661295f6b6617abda8610c3c
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/109_data/wts32.txt
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/116_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/116_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..11911d2fd7fc63987886685d42dad48113c8dda2
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/116_data/wts32.txt
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/117_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/117_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..feadbf3793fc5778ce80fc76210d4f9a3af0f9da
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/117_data/wts32.txt
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/123_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/123_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..03b3c5cee2da6b3efc3b7ba13e594c4f035d33c4
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/123_data/wts32.txt
@@ -0,0 +1,32000 @@
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/124_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/124_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..f643adab6ce221af29064b8152b094e07493da04
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/124_data/wts32.txt
@@ -0,0 +1,45696 @@
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/129_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/129_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..4b4b0555a0ffc4e7538c9e65d3b622b41e8eeebe
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/129_data/wts32.txt
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/136_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/136_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..57e82b8c1021af918b409658222a1768182ba51f
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/136_data/wts32.txt
@@ -0,0 +1,67200 @@
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/137_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/137_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..2a3c6c30136a8881a437baccfae582f839edf114
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/137_data/wts32.txt
@@ -0,0 +1,60544 @@
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index 0000000000000000000000000000000000000000..62273899e7d1883fad1f3b66d96ac366299ef101
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/143_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/143_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..5964dfbbaf79f01bae46bad257d81500d5301807
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/143_data/wts32.txt
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/144_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/144_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..686cd82f037672381253455eebd37188e5cc08d0
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/144_data/wts32.txt
@@ -0,0 +1,45696 @@
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/149_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/149_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..5ac9ef1bc176bc3df12bcf1e33e4802c9434d49c
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/149_data/wts32.txt
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/14_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/14_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..5b90e43d93dc0c84c6e6117caf388d21eafe6ac8
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/14_data/wts32.txt
@@ -0,0 +1,1088 @@
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/156_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/156_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..52f1b9047e65b10488f54750fa502606b699e2bc
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/156_data/wts32.txt
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/157_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/157_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..b683fee7d80f650451ec05a6038207b1086d60d7
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/157_data/wts32.txt
@@ -0,0 +1,60544 @@
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/15_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/15_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..bcbb4074e3c6afa23d0047fd46f7b61d1a3a42ee
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/15_data/wts32.txt
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/163_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/163_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..52a4d6a1f7f07acce793e52377fdb62d16d71241
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/163_data/wts32.txt
@@ -0,0 +1,60480 @@
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/164_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/164_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..06f9f5ab7ae532ea48badff75d06dfa2f31cf907
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/164_data/wts32.txt
@@ -0,0 +1,80640 @@
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/169_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/169_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..cbb00995d50c9d520dfe146c27c9f820e8a60102
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/169_data/wts32.txt
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/16_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/16_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..52a1fec465d821f68edaa112ce7ed39b1aacb5e2
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/16_data/wts32.txt
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/176_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/176_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..0f489aa639c607676409136aade2635329457ef0
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/176_data/wts32.txt
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/177_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/177_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..f1e5fba7a61f27ea67f8a3f5e37307955162fe99
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/177_data/wts32.txt
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/183_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/183_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e85623666f4fe9b744deefffefd94994b0612d50
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/183_data/wts32.txt
@@ -0,0 +1,100224 @@
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/184_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/184_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..c1e136864230dfb72a7305d1e06ceca10ab1cc24
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/184_data/wts32.txt
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/189_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/189_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..8b9310cec372b3974239b1de66aabbb874830b82
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/189_data/wts32.txt
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/18_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/18_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..3f95cc958598b44ba7f4e7cd2ba34c22c9fcd444
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/18_data/wts32.txt
@@ -0,0 +1,2176 @@
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/196_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/196_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..5f39177041ef1b0d92d8f9d9ec84c5899e62c0d8
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/196_data/wts32.txt
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/197_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/197_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..52f5356ab4d679f3f8753f9ca46f43b61be0017f
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/197_data/wts32.txt
@@ -0,0 +1,120960 @@
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/19_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/19_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..f4932fe15d195fa4098d9a72263dac1876649b22
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/19_data/wts32.txt
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/203_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/203_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..894996892c13b0106cedbdba1e2d17ab9f518ea8
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/203_data/wts32.txt
@@ -0,0 +1,100224 @@
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/204_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/204_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..3dff23f12ee0d46c75927e6b3defb0329f51e740
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/204_data/wts32.txt
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/20_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/20_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..9b0fdd27135ebe9dd86b792783351e9be62d05b3
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/20_data/wts32.txt
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/211_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/211_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..7e2754b3d15a80aebf5f93146cb1ff314b491fd0
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/211_data/wts32.txt
@@ -0,0 +1,62720 @@
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/214_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/214_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..5f12d4d3af6617d9666279fce3cf8a13d27e95f6
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/214_data/wts32.txt
@@ -0,0 +1,64000 @@
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/218_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/218_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..319eb39137bd1590c73b4a6f95d0576ef5a67c5f
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/218_data/wts32.txt
@@ -0,0 +1,75776 @@
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/226_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/226_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..0b196a6a45c51a9c96398a8b42bcbe90c851aae7
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/226_data/wts32.txt
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/22_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/22_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..814fa50823cf9e0960a1749e83d000709b412ef5
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/22_data/wts32.txt
@@ -0,0 +1,2432 @@
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/237_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/237_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..cf653cef6c9cb3e72755efccfc7d88fadde0a0b7
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/237_data/wts32.txt
@@ -0,0 +1,104192 @@
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/23_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/23_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..beaf9e70f58f2ba30f1b1abde872960083c6e613
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/241_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/241_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..c6e5a67e26a67b782f9c7de839a7c799ef5f0aca
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/241_data/wts32.txt
@@ -0,0 +1,47360 @@
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/249_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/249_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..187d830d036f670c560d6860253ababf6987b8b2
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/249_data/wts32.txt
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/24_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/24_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..df2ec5ea4c10a4b619efedee83e40ae049fe24e2
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/24_data/wts32.txt
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/257_data/wts32.txt b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/257_data/wts32.txt
new file mode 100644
index 0000000000000000000000000000000000000000..65d8a2259b95263ba431438324090c00b5236ae1
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/257_data/wts32.txt
@@ -0,0 +1,33152 @@
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/InactiveSpillingDebug_Dump_0.dot b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/InactiveSpillingDebug_Dump_0.dot
new file mode 100644
index 0000000000000000000000000000000000000000..703b303ffced18f3e23c86fc00bbacb247107d49
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/InactiveSpillingDebug_Dump_0.dot
@@ -0,0 +1,1798 @@
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+"646" [label="(Node ID: 246\nTopoID: 646\nSplit_379_Duplicated#0)\n(SliceHCWC8Adf)\n(L-246)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"667" [label="(Node ID: 254\nTopoID: 667\nResize_391)\n(ResizeAdf)\n(L-254)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"685" [label="(Node ID: 261\nTopoID: 685\nConv_403)\n(L-261)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"698" [label="(Node ID: 265\nTopoID: 698\nMul_412)\n(L-265)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"700" [label="(Node ID: 266\nTopoID: 700\nSplit_405_Duplicated#0)\n(SliceHCWC8Adf)\n(L-266)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"703" [label="(Node ID: 267\nTopoID: 703\nL2_IFM_Buffer_from_layer_266_for_layer_267_port0)\n Buffer dim : {1,24,45,80}\n Buffer bound : {1,24,45,80}\n Buffer Size : 172800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
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+"706" [label="(Node ID: 267\nTopoID: 706\nl2l3_267_spill)\n Buffer dim : {1,24,45,80}\n Buffer bound : {1,20,45,80}\n Buffer Size : 172800\n DataType : BF16", shape="rect", color="red"];
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+"727" [label="(Node ID: 276\nTopoID: 727\nl2l3_276_spill)\n Buffer dim : {1,32,90,160}\n Buffer bound : {1,32,90,160}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"728" [label="(Node ID: 277\nTopoID: 728\nSplit_421_Duplicated#0)\n(SliceHCWC8Adf)\n(L-277)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"730" [label="(Node ID: 278\nTopoID: 730\nSplit_421_Duplicated#1)\n(SliceHCWC8Adf)\n(L-278)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"737" [label="(Node ID: 280\nTopoID: 737\nConv_423)\n(L-280)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"744" [label="(Node ID: 282\nTopoID: 744\nSplit_425_Duplicated#1)\n(SliceHCWC8Adf)\n(L-282)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"749" [label="(Node ID: 283\nTopoID: 749\nSub_431)\n(L-283)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"751" [label="(Node ID: 283\nTopoID: 751\nl2l3_283_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
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+"753" [label="(Node ID: 284\nTopoID: 753\nL2_IFM_Buffer_from_layer_283_for_layer_284_port0)\n Buffer dim : {1,16,30,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 307200\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"754" [label="(Node ID: 284\nTopoID: 754\nMul_432)\n(L-284)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"756" [label="(Node ID: 284\nTopoID: 756\nl2l3_284_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_0.dot b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_0.dot
new file mode 100644
index 0000000000000000000000000000000000000000..f82cb6e4a1b59105730222a25f24a2878cc37367
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_0.dot
@@ -0,0 +1,1804 @@
+digraph G {
+"0" [label="(START)"];
+"1" [label="(Node ID: 0\nTopoID: 1\nifm_ddr)\n Buffer dim : {1,184,320,4}\n Buffer bound : {1,180,320,4}\n Buffer Size : 471040\n DataType : BF16", shape="rect", color="red"];
+"2" [label="(Node ID: 1\nTopoID: 2\nL2_IFM_Buffer_for_input0_0_port0)\n Buffer dim : {1,184,320,4}\n Buffer bound : {1,184,320,4}\n Buffer Size : 471040\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"3" [label="(Node ID: 1\nTopoID: 3\nDiv_2)\n(L-1)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"4" [label="(Node ID: 1\nTopoID: 4\nl2_1)\n Buffer dim : {1,192,320,4}\n Buffer bound : {1,184,320,4}\n Buffer Size : 491520\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"5" [label="(Node ID: 2\nTopoID: 5\nl2l3_1_spill)\n Buffer dim : {1,184,320,4}\n Buffer bound : {1,180,320,4}\n Buffer Size : 471040\n DataType : BF16", shape="rect", color="red"];
+"6" [label="(Node ID: 2\nTopoID: 6\nSlice_7)\n(SliceHCWC8Adf)\n(L-2)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"7" [label="(Node ID: 2\nTopoID: 7\nl2l3_2_spill)\n Buffer dim : {1,184,320,3}\n Buffer bound : {1,180,320,3}\n Buffer Size : 353280\n DataType : BF16", shape="rect", color="red"];
+"8" [label="(Node ID: 2\nTopoID: 8\nl2l3_scratch_0_3_spill)\n Buffer dim : {942080}\n Buffer bound : {942080}\n Buffer Size : 942080\n DataType : INT8", shape="rect", color="red"];
+"9" [label="(Node ID: 3\nTopoID: 9\nGenerated-#0)\n(BufferPadAdf)\n(L-3)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"10" [label="(Node ID: 4\nTopoID: 10\nl2l3_3_spill)\n Buffer dim : {1,184,320,8}\n Buffer bound : {1,180,320,3}\n Buffer Size : 942080\n DataType : BF16", shape="rect", color="red"];
+"11" [label="(Node ID: 4\nTopoID: 11\nGenerated-#2)\n(Transpose4dAdf)\n(L-4)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"12" [label="(Node ID: 4\nTopoID: 12\nl2l3_4_spill)\n Buffer dim : {1,8,184,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 942080\n DataType : BF16", shape="rect", color="red"];
+"13" [label="(Node ID: 4\nTopoID: 13\nl2l3_scratch_0_5_spill)\n Buffer dim : {921600}\n Buffer bound : {921600}\n Buffer Size : 921600\n DataType : INT8", shape="rect", color="red"];
+"14" [label="(Node ID: 5\nTopoID: 14\nGenerated-#4)\n(BufferUnpadAdf)\n(L-5)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"15" [label="(Node ID: 5\nTopoID: 15\nl2l3_5_spill)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"16" [label="(Node ID: 0\nTopoID: 16\nconst_ifm_ddr_5)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"17" [label="(Node ID: 6\nTopoID: 17\nL2_CONST_IFM_Buffer_for_input5_0_port1)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"18" [label="(Node ID: 6\nTopoID: 18\nL2_IFM_Buffer_from_layer_5_for_layer_6_port0)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"19" [label="(Node ID: 6\nTopoID: 19\nSub_14)\n(L-6)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"20" [label="(Node ID: 6\nTopoID: 20\nl2_6)\n Buffer dim : {1,32,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 819200\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"21" [label="(Node ID: 6\nTopoID: 21\nl2l3_6_spill)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"22" [label="(Node ID: 0\nTopoID: 22\nconst_ifm_ddr_4)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"23" [label="(Node ID: 7\nTopoID: 23\nL2_CONST_IFM_Buffer_for_input4_0_port1)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"24" [label="(Node ID: 7\nTopoID: 24\nL2_IFM_Buffer_from_layer_6_for_layer_7_port0)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
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+"27" [label="(Node ID: 7\nTopoID: 27\nl2l3_7_spill)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"28" [label="(Node ID: 8\nTopoID: 28\nL2_IFM_Buffer_from_layer_7_for_layer_8_port0)\n Buffer dim : {1,8,61,320}\n Buffer bound : {1,8,61,320}\n Buffer Size : 624640\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"29" [label="(Node ID: 8\nTopoID: 29\nConv_17)\n(L-8)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"30" [label="(Node ID: 8\nTopoID: 30\nl2_8)\n Buffer dim : {1,32,32,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 655360\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"31" [label="(Node ID: 8\nTopoID: 31\nl2l3_8_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"32" [label="(Node ID: 9\nTopoID: 32\nL2_IFM_Buffer_from_layer_8_for_layer_9_port0)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"33" [label="(Node ID: 9\nTopoID: 33\nAdd_19)\n(L-9)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"34" [label="(Node ID: 9\nTopoID: 34\nl2_9)\n Buffer dim : {1,32,92,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 942080\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"35" [label="(Node ID: 9\nTopoID: 35\nl2l3_9_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"36" [label="(Node ID: 10\nTopoID: 36\nL2_IFM_Buffer_from_layer_9_for_layer_10_port0)\n Buffer dim : {1,16,45,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 230400\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"37" [label="(Node ID: 10\nTopoID: 37\nClip_22)\n(L-10)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"38" [label="(Node ID: 10\nTopoID: 38\nl2_10)\n Buffer dim : {1,32,48,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 491520\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"39" [label="(Node ID: 10\nTopoID: 39\nl2l3_10_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"40" [label="(Node ID: 11\nTopoID: 40\nL2_IFM_Buffer_from_layer_10_for_layer_11_port0)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"41" [label="(Node ID: 11\nTopoID: 41\nDiv_24)\n(L-11)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"42" [label="(Node ID: 11\nTopoID: 42\nl2_11)\n Buffer dim : {1,32,92,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 942080\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"43" [label="(Node ID: 11\nTopoID: 43\nl2l3_11_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"44" [label="(Node ID: 12\nTopoID: 44\nL2_IFM_Buffer_from_layer_8_for_layer_12_port0)\n Buffer dim : {1,16,30,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 307200\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"45" [label="(Node ID: 12\nTopoID: 45\nL2_IFM_Buffer_from_layer_11_for_layer_12_port1)\n Buffer dim : {1,16,30,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 307200\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"46" [label="(Node ID: 12\nTopoID: 46\nMul_25)\n(L-12)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"47" [label="(Node ID: 12\nTopoID: 47\nl2_12)\n Buffer dim : {1,32,32,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 655360\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"48" [label="(Node ID: 12\nTopoID: 48\nl2l3_12_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"49" [label="(Node ID: 13\nTopoID: 49\nL2_IFM_Buffer_from_layer_12_for_layer_13_port0)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"50" [label="(Node ID: 13\nTopoID: 50\nConv_26)\n(L-13)\n TG Layer : False\n IncoreChain Kernels Type : DepthwiseConv2d", shape="ellipse"];
+"51" [label="(Node ID: 13\nTopoID: 51\nl2_13)\n Buffer dim : {1,32,96,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 983040\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"52" [label="(Node ID: 13\nTopoID: 52\nl2l3_13_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"53" [label="(Node ID: 14\nTopoID: 53\nL2_IFM_Buffer_from_layer_12_for_layer_14_port1)\n Buffer dim : {1,32,48,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 491520\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"54" [label="(Node ID: 14\nTopoID: 54\nL2_IFM_Buffer_from_layer_13_for_layer_14_port0)\n Buffer dim : {1,16,45,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 230400\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"55" [label="(Node ID: 14\nTopoID: 55\nConv_28)\n(L-14)\n TG Layer : False\n IncoreChain Kernels Type : Conv2dElementwiseBinary", shape="ellipse"];
+"56" [label="(Node ID: 14\nTopoID: 56\nl2_14)\n Buffer dim : {1,32,48,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 491520\n Buffer concat offset : { spill_L3_Concat_Buffer_layer_275 : {0,40,0,0}, l2l3_14_spill : {0,0,0,0} }\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"57" [label="(Node ID: 14\nTopoID: 57\nl2l3_14_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"58" [label="(Node ID: 15\nTopoID: 58\nL2_IFM_Buffer_from_layer_14_for_layer_15_port0)\n Buffer dim : {1,16,18,160}\n Buffer bound : {1,16,18,160}\n Buffer Size : 184320\n Tiling Factor : {1,1,5,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"59" [label="(Node ID: 15\nTopoID: 59\nConv_30)\n(L-15)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"60" [label="(Node ID: 15\nTopoID: 60\nl2_15)\n Buffer dim : {1,64,18,160}\n Buffer bound : {1,64,18,160}\n Buffer Size : 737280\n Tiling Factor : {1,1,5,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"61" [label="(Node ID: 15\nTopoID: 61\nl2l3_15_spill)\n Buffer dim : {1,64,90,160}\n Buffer bound : {1,64,90,160}\n Buffer Size : 1843200\n DataType : BF16", shape="rect", color="red"];
+"62" [label="(Node ID: 16\nTopoID: 62\nL2_IFM_Buffer_from_layer_15_for_layer_16_port0)\n Buffer dim : {1,64,17,160}\n Buffer bound : {1,64,17,160}\n Buffer Size : 696320\n Tiling Factor : {1,1,6,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"63" [label="(Node ID: 16\nTopoID: 63\nConv_32)\n(L-16)\n TG Layer : False\n IncoreChain Kernels Type : DepthwiseConv2d", shape="ellipse"];
+"64" [label="(Node ID: 16\nTopoID: 64\nl2_16)\n Buffer dim : {1,64,8,84}\n Buffer bound : {1,64,8,80}\n Buffer Size : 172032\n Tiling Factor : {1,1,6,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"65" [label="(Node ID: 16\nTopoID: 65\nl2l3_16_spill)\n Buffer dim : {1,64,48,80}\n Buffer bound : {1,64,45,80}\n Buffer Size : 491520\n DataType : BF16", shape="rect", color="red"];
+"66" [label="(Node ID: 16\nTopoID: 66\nl2l3_scratch_0_17_spill)\n Buffer dim : {460800}\n Buffer bound : {460800}\n Buffer Size : 460800\n DataType : INT8", shape="rect", color="red"];
+"67" [label="(Node ID: 17\nTopoID: 67\nGenerated-#60)\n(BufferUnpadAdf)\n(L-17)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"68" [label="(Node ID: 17\nTopoID: 68\nl2l3_17_spill)\n Buffer dim : {1,64,45,80}\n Buffer bound : {1,64,45,80}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"69" [label="(Node ID: 18\nTopoID: 69\nL2_IFM_Buffer_from_layer_17_for_layer_18_port0)\n Buffer dim : {1,64,45,80}\n Buffer bound : {1,64,45,80}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"70" [label="(Node ID: 18\nTopoID: 70\nConv_34)\n(L-18)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"587" [label="(Node ID: 224\nTopoID: 587\nL2_IFM_Buffer_from_layer_223_for_layer_224_port0)\n Buffer dim : {1,64,12,20}\n Buffer bound : {1,64,12,20}\n Buffer Size : 30720\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"588" [label="(Node ID: 224\nTopoID: 588\nMul_354)\n(L-224)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"604" [label="(Node ID: 231\nTopoID: 604\nspill_L3_Concat_Buffer_layer_230)\n Buffer dim : {1,128,12,20}\n Buffer bound : {1,128,12,20}\n Buffer Size : 61440\n DataType : BF16", shape="rect", color="red"];
+"605" [label="(Node ID: 231\nTopoID: 605\nResize_365)\n(ResizeAdf)\n(L-231)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"613" [label="(Node ID: 233\nTopoID: 613\nl2l3_233_spill)\n Buffer dim : {1,8,90,160}\n Buffer bound : {1,3,90,160}\n Buffer Size : 230400\n DataType : BF16", shape="rect", color="red"];
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+"615" [label="(Node ID: 234\nTopoID: 615\nAveragePool_347)\n(L-234)\n TG Layer : False\n IncoreChain Kernels Type : AvgPool2d", shape="ellipse"];
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+"617" [label="(Node ID: 235\nTopoID: 617\nAveragePool_348)\n(L-235)\n TG Layer : False\n IncoreChain Kernels Type : AvgPool2d", shape="ellipse"];
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+"621" [label="(Node ID: 237\nTopoID: 621\nConv_373)\n(L-237)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"624" [label="(Node ID: 238\nTopoID: 624\nSplit_375_Duplicated#0)\n(SliceHCWC8Adf)\n(L-238)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"626" [label="(Node ID: 239\nTopoID: 626\nSplit_375_Duplicated#1)\n(SliceHCWC8Adf)\n(L-239)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"631" [label="(Node ID: 240\nTopoID: 631\nspill_L3_Concat_Buffer_layer_240)\n Buffer dim : {1,80,23,40}\n Buffer bound : {1,80,23,40}\n Buffer Size : 147200\n DataType : BF16", shape="rect", color="red"];
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+"633" [label="(Node ID: 241\nTopoID: 633\nConv_377)\n(L-241)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"635" [label="(Node ID: 242\nTopoID: 635\nSigmoid_378)\n(L-242)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
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+"637" [label="(Node ID: 242\nTopoID: 637\nl2l3_242_spill)\n Buffer dim : {1,80,23,40}\n Buffer bound : {1,80,23,40}\n Buffer Size : 147200\n DataType : BF16", shape="rect", color="red"];
+"638" [label="(Node ID: 243\nTopoID: 638\nSplit_379_Duplicated#1)\n(SliceHCWC8Adf)\n(L-243)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"643" [label="(Node ID: 244\nTopoID: 643\nSub_385)\n(L-244)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"648" [label="(Node ID: 246\nTopoID: 648\nSplit_379_Duplicated#0)\n(SliceHCWC8Adf)\n(L-246)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"659" [label="(Node ID: 250\nTopoID: 659\nTanh_383)\n(L-250)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
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+"662" [label="(Node ID: 251\nTopoID: 662\nMul_387)\n(L-251)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"669" [label="(Node ID: 254\nTopoID: 669\nResize_391)\n(ResizeAdf)\n(L-254)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"702" [label="(Node ID: 266\nTopoID: 702\nSplit_405_Duplicated#0)\n(SliceHCWC8Adf)\n(L-266)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"751" [label="(Node ID: 283\nTopoID: 751\nSub_431)\n(L-283)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"753" [label="(Node ID: 283\nTopoID: 753\nl2l3_283_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
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+"756" [label="(Node ID: 284\nTopoID: 756\nMul_432)\n(L-284)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"758" [label="(Node ID: 284\nTopoID: 758\nl2l3_284_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
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+"763" [label="(Node ID: 286\nTopoID: 763\nMul_426)\n(L-286)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_1.dot b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_1.dot
new file mode 100644
index 0000000000000000000000000000000000000000..508f243935fdca5d30c62af504ef2dc61ede8cdf
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_1.dot
@@ -0,0 +1,1810 @@
+digraph G {
+"0" [label="(START)"];
+"1" [label="(Node ID: 0\nTopoID: 1\nifm_ddr)\n Buffer dim : {1,184,320,4}\n Buffer bound : {1,180,320,4}\n Buffer Size : 471040\n DataType : BF16", shape="rect", color="red"];
+"2" [label="(Node ID: 1\nTopoID: 2\nL2_IFM_Buffer_for_input0_0_port0)\n Buffer dim : {1,184,320,4}\n Buffer bound : {1,184,320,4}\n Buffer Size : 471040\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"3" [label="(Node ID: 1\nTopoID: 3\nDiv_2)\n(L-1)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"4" [label="(Node ID: 1\nTopoID: 4\nl2_1)\n Buffer dim : {1,192,320,4}\n Buffer bound : {1,184,320,4}\n Buffer Size : 491520\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"5" [label="(Node ID: 2\nTopoID: 5\nl2l3_1_spill)\n Buffer dim : {1,184,320,4}\n Buffer bound : {1,180,320,4}\n Buffer Size : 471040\n DataType : BF16", shape="rect", color="red"];
+"6" [label="(Node ID: 2\nTopoID: 6\nSlice_7)\n(SliceHCWC8Adf)\n(L-2)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"7" [label="(Node ID: 2\nTopoID: 7\nl2l3_2_spill)\n Buffer dim : {1,184,320,3}\n Buffer bound : {1,180,320,3}\n Buffer Size : 353280\n DataType : BF16", shape="rect", color="red"];
+"8" [label="(Node ID: 2\nTopoID: 8\nl2l3_scratch_0_3_spill)\n Buffer dim : {942080}\n Buffer bound : {942080}\n Buffer Size : 942080\n DataType : INT8", shape="rect", color="red"];
+"9" [label="(Node ID: 3\nTopoID: 9\nGenerated-#0)\n(BufferPadAdf)\n(L-3)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"10" [label="(Node ID: 4\nTopoID: 10\nl2l3_3_spill)\n Buffer dim : {1,184,320,8}\n Buffer bound : {1,180,320,3}\n Buffer Size : 942080\n DataType : BF16", shape="rect", color="red"];
+"11" [label="(Node ID: 4\nTopoID: 11\nGenerated-#2)\n(Transpose4dAdf)\n(L-4)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"12" [label="(Node ID: 4\nTopoID: 12\nl2l3_4_spill)\n Buffer dim : {1,8,184,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 942080\n DataType : BF16", shape="rect", color="red"];
+"13" [label="(Node ID: 4\nTopoID: 13\nl2l3_scratch_0_5_spill)\n Buffer dim : {921600}\n Buffer bound : {921600}\n Buffer Size : 921600\n DataType : INT8", shape="rect", color="red"];
+"14" [label="(Node ID: 5\nTopoID: 14\nGenerated-#4)\n(BufferUnpadAdf)\n(L-5)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"15" [label="(Node ID: 5\nTopoID: 15\nl2l3_5_spill)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"16" [label="(Node ID: 0\nTopoID: 16\nconst_ifm_ddr_5)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"17" [label="(Node ID: 6\nTopoID: 17\nL2_CONST_IFM_Buffer_for_input5_0_port1)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"18" [label="(Node ID: 6\nTopoID: 18\nL2_IFM_Buffer_from_layer_5_for_layer_6_port0)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"19" [label="(Node ID: 6\nTopoID: 19\nSub_14)\n(L-6)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"20" [label="(Node ID: 6\nTopoID: 20\nl2_6)\n Buffer dim : {1,32,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 819200\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"21" [label="(Node ID: 6\nTopoID: 21\nl2l3_6_spill)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"22" [label="(Node ID: 0\nTopoID: 22\nconst_ifm_ddr_4)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"23" [label="(Node ID: 7\nTopoID: 23\nL2_CONST_IFM_Buffer_for_input4_0_port1)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"24" [label="(Node ID: 7\nTopoID: 24\nL2_IFM_Buffer_from_layer_6_for_layer_7_port0)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"25" [label="(Node ID: 7\nTopoID: 25\nDiv_16)\n(L-7)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"26" [label="(Node ID: 7\nTopoID: 26\nl2_7)\n Buffer dim : {1,32,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 819200\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"27" [label="(Node ID: 7\nTopoID: 27\nl2l3_7_spill)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"28" [label="(Node ID: 8\nTopoID: 28\nL2_IFM_Buffer_from_layer_7_for_layer_8_port0)\n Buffer dim : {1,8,61,320}\n Buffer bound : {1,8,61,320}\n Buffer Size : 624640\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"29" [label="(Node ID: 8\nTopoID: 29\nConv_17)\n(L-8)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"30" [label="(Node ID: 8\nTopoID: 30\nl2_8)\n Buffer dim : {1,32,32,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 655360\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"31" [label="(Node ID: 8\nTopoID: 31\nl2l3_8_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"32" [label="(Node ID: 9\nTopoID: 32\nL2_IFM_Buffer_from_layer_8_for_layer_9_port0)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"33" [label="(Node ID: 9\nTopoID: 33\nAdd_19)\n(L-9)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"34" [label="(Node ID: 9\nTopoID: 34\nl2_9)\n Buffer dim : {1,32,92,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 942080\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"35" [label="(Node ID: 9\nTopoID: 35\nl2l3_9_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"36" [label="(Node ID: 10\nTopoID: 36\nL2_IFM_Buffer_from_layer_9_for_layer_10_port0)\n Buffer dim : {1,16,45,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 230400\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"37" [label="(Node ID: 10\nTopoID: 37\nClip_22)\n(L-10)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"38" [label="(Node ID: 10\nTopoID: 38\nl2_10)\n Buffer dim : {1,32,48,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 491520\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"39" [label="(Node ID: 10\nTopoID: 39\nl2l3_10_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"40" [label="(Node ID: 11\nTopoID: 40\nL2_IFM_Buffer_from_layer_10_for_layer_11_port0)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"41" [label="(Node ID: 11\nTopoID: 41\nDiv_24)\n(L-11)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"42" [label="(Node ID: 11\nTopoID: 42\nl2_11)\n Buffer dim : {1,32,92,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 942080\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"43" [label="(Node ID: 11\nTopoID: 43\nl2l3_11_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"44" [label="(Node ID: 12\nTopoID: 44\nL2_IFM_Buffer_from_layer_8_for_layer_12_port0)\n Buffer dim : {1,16,30,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 307200\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"45" [label="(Node ID: 12\nTopoID: 45\nL2_IFM_Buffer_from_layer_11_for_layer_12_port1)\n Buffer dim : {1,16,30,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 307200\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"46" [label="(Node ID: 12\nTopoID: 46\nMul_25)\n(L-12)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"47" [label="(Node ID: 12\nTopoID: 47\nl2_12)\n Buffer dim : {1,32,32,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 655360\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"48" [label="(Node ID: 12\nTopoID: 48\nl2l3_12_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"49" [label="(Node ID: 13\nTopoID: 49\nL2_IFM_Buffer_from_layer_12_for_layer_13_port0)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"50" [label="(Node ID: 13\nTopoID: 50\nConv_26)\n(L-13)\n TG Layer : False\n IncoreChain Kernels Type : DepthwiseConv2d", shape="ellipse"];
+"51" [label="(Node ID: 13\nTopoID: 51\nl2_13)\n Buffer dim : {1,32,96,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 983040\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"52" [label="(Node ID: 13\nTopoID: 52\nl2l3_13_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"53" [label="(Node ID: 14\nTopoID: 53\nL2_IFM_Buffer_from_layer_12_for_layer_14_port1)\n Buffer dim : {1,32,48,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 491520\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"54" [label="(Node ID: 14\nTopoID: 54\nL2_IFM_Buffer_from_layer_13_for_layer_14_port0)\n Buffer dim : {1,16,45,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 230400\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"55" [label="(Node ID: 14\nTopoID: 55\nConv_28)\n(L-14)\n TG Layer : False\n IncoreChain Kernels Type : Conv2dElementwiseBinary", shape="ellipse"];
+"56" [label="(Node ID: 14\nTopoID: 56\nl2_14)\n Buffer dim : {1,32,48,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 491520\n Buffer concat offset : { spill_L3_Concat_Buffer_layer_275 : {0,40,0,0}, l2l3_14_spill : {0,0,0,0} }\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"57" [label="(Node ID: 14\nTopoID: 57\nl2l3_14_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"58" [label="(Node ID: 15\nTopoID: 58\nL2_IFM_Buffer_from_layer_14_for_layer_15_port0)\n Buffer dim : {1,16,18,160}\n Buffer bound : {1,16,18,160}\n Buffer Size : 184320\n Tiling Factor : {1,1,5,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"59" [label="(Node ID: 15\nTopoID: 59\nConv_30)\n(L-15)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"60" [label="(Node ID: 15\nTopoID: 60\nl2_15)\n Buffer dim : {1,64,18,160}\n Buffer bound : {1,64,18,160}\n Buffer Size : 737280\n Tiling Factor : {1,1,5,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"61" [label="(Node ID: 15\nTopoID: 61\nl2l3_15_spill)\n Buffer dim : {1,64,90,160}\n Buffer bound : {1,64,90,160}\n Buffer Size : 1843200\n DataType : BF16", shape="rect", color="red"];
+"62" [label="(Node ID: 16\nTopoID: 62\nL2_IFM_Buffer_from_layer_15_for_layer_16_port0)\n Buffer dim : {1,64,17,160}\n Buffer bound : {1,64,17,160}\n Buffer Size : 696320\n Tiling Factor : {1,1,6,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"63" [label="(Node ID: 16\nTopoID: 63\nConv_32)\n(L-16)\n TG Layer : False\n IncoreChain Kernels Type : DepthwiseConv2d", shape="ellipse"];
+"64" [label="(Node ID: 16\nTopoID: 64\nl2_16)\n Buffer dim : {1,64,8,84}\n Buffer bound : {1,64,8,80}\n Buffer Size : 172032\n Tiling Factor : {1,1,6,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"65" [label="(Node ID: 16\nTopoID: 65\nl2l3_16_spill)\n Buffer dim : {1,64,48,80}\n Buffer bound : {1,64,45,80}\n Buffer Size : 491520\n DataType : BF16", shape="rect", color="red"];
+"66" [label="(Node ID: 16\nTopoID: 66\nl2l3_scratch_0_17_spill)\n Buffer dim : {460800}\n Buffer bound : {460800}\n Buffer Size : 460800\n DataType : INT8", shape="rect", color="red"];
+"67" [label="(Node ID: 17\nTopoID: 67\nGenerated-#60)\n(BufferUnpadAdf)\n(L-17)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"68" [label="(Node ID: 17\nTopoID: 68\nl2l3_17_spill)\n Buffer dim : {1,64,45,80}\n Buffer bound : {1,64,45,80}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"69" [label="(Node ID: 18\nTopoID: 69\nL2_IFM_Buffer_from_layer_17_for_layer_18_port0)\n Buffer dim : {1,64,45,80}\n Buffer bound : {1,64,45,80}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"70" [label="(Node ID: 18\nTopoID: 70\nConv_34)\n(L-18)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"71" [label="(Node ID: 18\nTopoID: 71\nl2_18)\n OFM_MEM_SHARE : 1\n Buffer dim : {1,64,48,80}\n Buffer bound : {1,24,45,80}\n Buffer Size : 491520\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"72" [label="(Node ID: 18\nTopoID: 72\nL3_OFM_Buffer_layer_TGSpilling_1818)\n Buffer dim : {1,24,45,80}\n Buffer bound : {1,24,45,80}\n Buffer Size : 172800\n DataType : BF16", shape="rect", color="red"];
+"73" [label="(Node ID: 19\nTopoID: 73\nConv_35)\n(L-19)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"606" [label="(Node ID: 231\nTopoID: 606\nspill_L3_Concat_Buffer_layer_230)\n Buffer dim : {1,128,12,20}\n Buffer bound : {1,128,12,20}\n Buffer Size : 61440\n DataType : BF16", shape="rect", color="red"];
+"607" [label="(Node ID: 231\nTopoID: 607\nResize_365)\n(ResizeAdf)\n(L-231)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"615" [label="(Node ID: 233\nTopoID: 615\nl2l3_233_spill)\n Buffer dim : {1,8,90,160}\n Buffer bound : {1,3,90,160}\n Buffer Size : 230400\n DataType : BF16", shape="rect", color="red"];
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+"617" [label="(Node ID: 234\nTopoID: 617\nAveragePool_347)\n(L-234)\n TG Layer : False\n IncoreChain Kernels Type : AvgPool2d", shape="ellipse"];
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+"619" [label="(Node ID: 235\nTopoID: 619\nAveragePool_348)\n(L-235)\n TG Layer : False\n IncoreChain Kernels Type : AvgPool2d", shape="ellipse"];
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+"621" [label="(Node ID: 236\nTopoID: 621\nspill_L3_Concat_Buffer_layer_236)\n Buffer dim : {1,176,23,40}\n Buffer bound : {1,171,23,40}\n Buffer Size : 323840\n DataType : BF16", shape="rect", color="red"];
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+"625" [label="(Node ID: 237\nTopoID: 625\nl2l3_237_spill)\n Buffer dim : {1,80,23,40}\n Buffer bound : {1,80,23,40}\n Buffer Size : 147200\n DataType : BF16", shape="rect", color="red"];
+"626" [label="(Node ID: 238\nTopoID: 626\nSplit_375_Duplicated#0)\n(SliceHCWC8Adf)\n(L-238)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"633" [label="(Node ID: 240\nTopoID: 633\nspill_L3_Concat_Buffer_layer_240)\n Buffer dim : {1,80,23,40}\n Buffer bound : {1,80,23,40}\n Buffer Size : 147200\n DataType : BF16", shape="rect", color="red"];
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+"635" [label="(Node ID: 241\nTopoID: 635\nConv_377)\n(L-241)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"637" [label="(Node ID: 242\nTopoID: 637\nSigmoid_378)\n(L-242)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
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+"639" [label="(Node ID: 242\nTopoID: 639\nl2l3_242_spill)\n Buffer dim : {1,80,23,40}\n Buffer bound : {1,80,23,40}\n Buffer Size : 147200\n DataType : BF16", shape="rect", color="red"];
+"640" [label="(Node ID: 243\nTopoID: 640\nSplit_379_Duplicated#1)\n(SliceHCWC8Adf)\n(L-243)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"645" [label="(Node ID: 244\nTopoID: 645\nSub_385)\n(L-244)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"650" [label="(Node ID: 246\nTopoID: 650\nSplit_379_Duplicated#0)\n(SliceHCWC8Adf)\n(L-246)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"658" [label="(Node ID: 249\nTopoID: 658\nL2_IFM_Buffer_from_layer_248_for_layer_249_port0)\n Buffer dim : {1,80,23,40}\n Buffer bound : {1,80,23,40}\n Buffer Size : 147200\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"659" [label="(Node ID: 249\nTopoID: 659\nConv_382)\n(L-249)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"664" [label="(Node ID: 251\nTopoID: 664\nMul_387)\n(L-251)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"671" [label="(Node ID: 254\nTopoID: 671\nResize_391)\n(ResizeAdf)\n(L-254)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"673" [label="(Node ID: 255\nTopoID: 673\nSlice_397)\n(SliceHCWC8Adf)\n(L-255)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"704" [label="(Node ID: 266\nTopoID: 704\nSplit_405_Duplicated#0)\n(SliceHCWC8Adf)\n(L-266)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"758" [label="(Node ID: 284\nTopoID: 758\nMul_432)\n(L-284)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"760" [label="(Node ID: 284\nTopoID: 760\nl2l3_284_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
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+"765" [label="(Node ID: 286\nTopoID: 765\nMul_426)\n(L-286)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_10.dot b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_10.dot
new file mode 100644
index 0000000000000000000000000000000000000000..867a2b3c1252ada610c1dd3a4cc9e27d507263d8
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_10.dot
@@ -0,0 +1,1882 @@
+digraph G {
+"0" [label="(START)"];
+"1" [label="(Node ID: 0\nTopoID: 1\nifm_ddr)\n Buffer dim : {1,184,320,4}\n Buffer bound : {1,180,320,4}\n Buffer Size : 471040\n DataType : BF16", shape="rect", color="red"];
+"2" [label="(Node ID: 1\nTopoID: 2\nL2_IFM_Buffer_for_input0_0_port0)\n Buffer dim : {1,184,320,4}\n Buffer bound : {1,184,320,4}\n Buffer Size : 471040\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"3" [label="(Node ID: 1\nTopoID: 3\nDiv_2)\n(L-1)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"4" [label="(Node ID: 1\nTopoID: 4\nl2_1)\n Buffer dim : {1,192,320,4}\n Buffer bound : {1,184,320,4}\n Buffer Size : 491520\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"5" [label="(Node ID: 2\nTopoID: 5\nl2l3_1_spill)\n Buffer dim : {1,184,320,4}\n Buffer bound : {1,180,320,4}\n Buffer Size : 471040\n DataType : BF16", shape="rect", color="red"];
+"6" [label="(Node ID: 2\nTopoID: 6\nSlice_7)\n(SliceHCWC8Adf)\n(L-2)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"7" [label="(Node ID: 2\nTopoID: 7\nl2l3_2_spill)\n Buffer dim : {1,184,320,3}\n Buffer bound : {1,180,320,3}\n Buffer Size : 353280\n DataType : BF16", shape="rect", color="red"];
+"8" [label="(Node ID: 2\nTopoID: 8\nl2l3_scratch_0_3_spill)\n Buffer dim : {942080}\n Buffer bound : {942080}\n Buffer Size : 942080\n DataType : INT8", shape="rect", color="red"];
+"9" [label="(Node ID: 3\nTopoID: 9\nGenerated-#0)\n(BufferPadAdf)\n(L-3)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"10" [label="(Node ID: 4\nTopoID: 10\nl2l3_3_spill)\n Buffer dim : {1,184,320,8}\n Buffer bound : {1,180,320,3}\n Buffer Size : 942080\n DataType : BF16", shape="rect", color="red"];
+"11" [label="(Node ID: 4\nTopoID: 11\nGenerated-#2)\n(Transpose4dAdf)\n(L-4)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"12" [label="(Node ID: 4\nTopoID: 12\nl2l3_4_spill)\n Buffer dim : {1,8,184,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 942080\n DataType : BF16", shape="rect", color="red"];
+"13" [label="(Node ID: 4\nTopoID: 13\nl2l3_scratch_0_5_spill)\n Buffer dim : {921600}\n Buffer bound : {921600}\n Buffer Size : 921600\n DataType : INT8", shape="rect", color="red"];
+"14" [label="(Node ID: 5\nTopoID: 14\nGenerated-#4)\n(BufferUnpadAdf)\n(L-5)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"15" [label="(Node ID: 5\nTopoID: 15\nl2l3_5_spill)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"16" [label="(Node ID: 0\nTopoID: 16\nconst_ifm_ddr_5)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"17" [label="(Node ID: 6\nTopoID: 17\nL2_CONST_IFM_Buffer_for_input5_0_port1)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"18" [label="(Node ID: 6\nTopoID: 18\nL2_IFM_Buffer_from_layer_5_for_layer_6_port0)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"19" [label="(Node ID: 6\nTopoID: 19\nSub_14)\n(L-6)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"20" [label="(Node ID: 6\nTopoID: 20\nl2_6)\n Buffer dim : {1,32,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 819200\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"21" [label="(Node ID: 6\nTopoID: 21\nl2l3_6_spill)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"22" [label="(Node ID: 0\nTopoID: 22\nconst_ifm_ddr_4)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"23" [label="(Node ID: 7\nTopoID: 23\nL2_CONST_IFM_Buffer_for_input4_0_port1)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"24" [label="(Node ID: 7\nTopoID: 24\nL2_IFM_Buffer_from_layer_6_for_layer_7_port0)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"25" [label="(Node ID: 7\nTopoID: 25\nDiv_16)\n(L-7)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"27" [label="(Node ID: 7\nTopoID: 27\nl2l3_7_spill)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"28" [label="(Node ID: 8\nTopoID: 28\nL2_IFM_Buffer_from_layer_7_for_layer_8_port0)\n Buffer dim : {1,8,61,320}\n Buffer bound : {1,8,61,320}\n Buffer Size : 624640\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"29" [label="(Node ID: 8\nTopoID: 29\nConv_17)\n(L-8)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"30" [label="(Node ID: 8\nTopoID: 30\nl2_8)\n Buffer dim : {1,32,32,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 655360\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"31" [label="(Node ID: 8\nTopoID: 31\nl2l3_8_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"32" [label="(Node ID: 9\nTopoID: 32\nL2_IFM_Buffer_from_layer_8_for_layer_9_port0)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"33" [label="(Node ID: 9\nTopoID: 33\nAdd_19)\n(L-9)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"34" [label="(Node ID: 9\nTopoID: 34\nl2_9)\n Buffer dim : {1,32,92,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 942080\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"35" [label="(Node ID: 9\nTopoID: 35\nl2l3_9_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"36" [label="(Node ID: 10\nTopoID: 36\nL2_IFM_Buffer_from_layer_9_for_layer_10_port0)\n Buffer dim : {1,16,45,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 230400\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"37" [label="(Node ID: 10\nTopoID: 37\nClip_22)\n(L-10)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"38" [label="(Node ID: 10\nTopoID: 38\nl2_10)\n Buffer dim : {1,32,48,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 491520\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"39" [label="(Node ID: 10\nTopoID: 39\nl2l3_10_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"40" [label="(Node ID: 11\nTopoID: 40\nL2_IFM_Buffer_from_layer_10_for_layer_11_port0)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"41" [label="(Node ID: 11\nTopoID: 41\nDiv_24)\n(L-11)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"42" [label="(Node ID: 11\nTopoID: 42\nl2_11)\n Buffer dim : {1,32,92,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 942080\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"43" [label="(Node ID: 11\nTopoID: 43\nl2l3_11_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"44" [label="(Node ID: 12\nTopoID: 44\nL2_IFM_Buffer_from_layer_8_for_layer_12_port0)\n Buffer dim : {1,16,30,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 307200\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"45" [label="(Node ID: 12\nTopoID: 45\nL2_IFM_Buffer_from_layer_11_for_layer_12_port1)\n Buffer dim : {1,16,30,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 307200\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"46" [label="(Node ID: 12\nTopoID: 46\nMul_25)\n(L-12)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"47" [label="(Node ID: 12\nTopoID: 47\nl2_12)\n Buffer dim : {1,32,32,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 655360\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"48" [label="(Node ID: 12\nTopoID: 48\nl2l3_12_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"49" [label="(Node ID: 13\nTopoID: 49\nL2_IFM_Buffer_from_layer_12_for_layer_13_port0)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"50" [label="(Node ID: 13\nTopoID: 50\nConv_26)\n(L-13)\n TG Layer : False\n IncoreChain Kernels Type : DepthwiseConv2d", shape="ellipse"];
+"51" [label="(Node ID: 13\nTopoID: 51\nl2_13)\n Buffer dim : {1,32,96,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 983040\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"52" [label="(Node ID: 13\nTopoID: 52\nl2l3_13_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"53" [label="(Node ID: 14\nTopoID: 53\nL2_IFM_Buffer_from_layer_12_for_layer_14_port1)\n Buffer dim : {1,32,48,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 491520\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"54" [label="(Node ID: 14\nTopoID: 54\nL2_IFM_Buffer_from_layer_13_for_layer_14_port0)\n Buffer dim : {1,16,45,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 230400\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"55" [label="(Node ID: 14\nTopoID: 55\nConv_28)\n(L-14)\n TG Layer : False\n IncoreChain Kernels Type : Conv2dElementwiseBinary", shape="ellipse"];
+"56" [label="(Node ID: 14\nTopoID: 56\nl2_14)\n Buffer dim : {1,32,48,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 491520\n Buffer concat offset : { spill_L3_Concat_Buffer_layer_275 : {0,40,0,0}, l2l3_14_spill : {0,0,0,0} }\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"57" [label="(Node ID: 14\nTopoID: 57\nl2l3_14_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"58" [label="(Node ID: 15\nTopoID: 58\nL2_IFM_Buffer_from_layer_14_for_layer_15_port0)\n Buffer dim : {1,16,18,160}\n Buffer bound : {1,16,18,160}\n Buffer Size : 184320\n Tiling Factor : {1,1,5,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"59" [label="(Node ID: 15\nTopoID: 59\nConv_30)\n(L-15)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"60" [label="(Node ID: 15\nTopoID: 60\nl2_15)\n Buffer dim : {1,64,18,160}\n Buffer bound : {1,64,18,160}\n Buffer Size : 737280\n Tiling Factor : {1,1,5,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"61" [label="(Node ID: 15\nTopoID: 61\nl2l3_15_spill)\n Buffer dim : {1,64,90,160}\n Buffer bound : {1,64,90,160}\n Buffer Size : 1843200\n DataType : BF16", shape="rect", color="red"];
+"62" [label="(Node ID: 16\nTopoID: 62\nL2_IFM_Buffer_from_layer_15_for_layer_16_port0)\n Buffer dim : {1,64,17,160}\n Buffer bound : {1,64,17,160}\n Buffer Size : 696320\n Tiling Factor : {1,1,6,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"63" [label="(Node ID: 16\nTopoID: 63\nConv_32)\n(L-16)\n TG Layer : False\n IncoreChain Kernels Type : DepthwiseConv2d", shape="ellipse"];
+"64" [label="(Node ID: 16\nTopoID: 64\nl2_16)\n Buffer dim : {1,64,8,84}\n Buffer bound : {1,64,8,80}\n Buffer Size : 172032\n Tiling Factor : {1,1,6,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"65" [label="(Node ID: 16\nTopoID: 65\nl2l3_16_spill)\n Buffer dim : {1,64,48,80}\n Buffer bound : {1,64,45,80}\n Buffer Size : 491520\n DataType : BF16", shape="rect", color="red"];
+"66" [label="(Node ID: 16\nTopoID: 66\nl2l3_scratch_0_17_spill)\n Buffer dim : {460800}\n Buffer bound : {460800}\n Buffer Size : 460800\n DataType : INT8", shape="rect", color="red"];
+"67" [label="(Node ID: 17\nTopoID: 67\nGenerated-#60)\n(BufferUnpadAdf)\n(L-17)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"68" [label="(Node ID: 17\nTopoID: 68\nl2l3_17_spill)\n Buffer dim : {1,64,45,80}\n Buffer bound : {1,64,45,80}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"69" [label="(Node ID: 18\nTopoID: 69\nL2_IFM_Buffer_from_layer_17_for_layer_18_port0)\n Buffer dim : {1,64,45,80}\n Buffer bound : {1,64,45,80}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"70" [label="(Node ID: 18\nTopoID: 70\nConv_34)\n(L-18)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"71" [label="(Node ID: 18\nTopoID: 71\nl2_18)\n OFM_MEM_SHARE : 1\n Buffer dim : {1,64,48,80}\n Buffer bound : {1,24,45,80}\n Buffer Size : 491520\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"72" [label="(Node ID: 18\nTopoID: 72\nL3_OFM_Buffer_layer_TGSpilling_1818)\n Buffer dim : {1,24,45,80}\n Buffer bound : {1,24,45,80}\n Buffer Size : 172800\n DataType : BF16", shape="rect", color="red"];
+"73" [label="(Node ID: 19\nTopoID: 73\nConv_35)\n(L-19)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"637" [label="(Node ID: 233\nTopoID: 637\nl2l3_233_spill)\n Buffer dim : {1,8,90,160}\n Buffer bound : {1,3,90,160}\n Buffer Size : 230400\n DataType : BF16", shape="rect", color="red"];
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+"639" [label="(Node ID: 234\nTopoID: 639\nAveragePool_347)\n(L-234)\n TG Layer : False\n IncoreChain Kernels Type : AvgPool2d", shape="ellipse"];
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+"641" [label="(Node ID: 235\nTopoID: 641\nAveragePool_348)\n(L-235)\n TG Layer : False\n IncoreChain Kernels Type : AvgPool2d", shape="ellipse"];
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+"643" [label="(Node ID: 236\nTopoID: 643\nspill_L3_Concat_Buffer_layer_236)\n Buffer dim : {1,176,23,40}\n Buffer bound : {1,171,23,40}\n Buffer Size : 323840\n DataType : BF16", shape="rect", color="red"];
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+"657" [label="(Node ID: 241\nTopoID: 657\nConv_377)\n(L-241)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"661" [label="(Node ID: 242\nTopoID: 661\nl2l3_242_spill)\n Buffer dim : {1,80,23,40}\n Buffer bound : {1,80,23,40}\n Buffer Size : 147200\n DataType : BF16", shape="rect", color="red"];
+"662" [label="(Node ID: 243\nTopoID: 662\nSplit_379_Duplicated#1)\n(SliceHCWC8Adf)\n(L-243)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"695" [label="(Node ID: 254\nTopoID: 695\nResize_391)\n(ResizeAdf)\n(L-254)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"728" [label="(Node ID: 266\nTopoID: 728\nSplit_405_Duplicated#0)\n(SliceHCWC8Adf)\n(L-266)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"743" [label="(Node ID: 271\nTopoID: 743\nMul_413)\n(L-271)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"745" [label="(Node ID: 272\nTopoID: 745\nAdd_414)\n(L-272)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"747" [label="(Node ID: 272\nTopoID: 747\nofm_ddr_2_l2l3_272_spill)\n Buffer dim : {1,24,45,80}\n Buffer bound : {1,20,45,80}\n Buffer Size : 172800\n DataType : BF16", shape="rect", color="red"];
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+"753" [label="(Node ID: 276\nTopoID: 753\nConv_419)\n(L-276)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"755" [label="(Node ID: 276\nTopoID: 755\nl2l3_276_spill)\n Buffer dim : {1,32,90,160}\n Buffer bound : {1,32,90,160}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"756" [label="(Node ID: 277\nTopoID: 756\nSplit_421_Duplicated#0)\n(SliceHCWC8Adf)\n(L-277)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"758" [label="(Node ID: 278\nTopoID: 758\nSplit_421_Duplicated#1)\n(SliceHCWC8Adf)\n(L-278)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_11.dot b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_11.dot
new file mode 100644
index 0000000000000000000000000000000000000000..a80233c645cddbdf919ef8ca5c81f2b36ad9254a
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_11.dot
@@ -0,0 +1,1888 @@
+digraph G {
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+"802" [label="(Node ID: 289\nTopoID: 802\nl2l3_289_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
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+"805" [label="(Node ID: 290\nTopoID: 805\nMul_433)\n(L-290)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"807" [label="(Node ID: 290\nTopoID: 807\nl2l3_290_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
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+"810" [label="(Node ID: 291\nTopoID: 810\nAdd_434)\n(L-291)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_12.dot b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_12.dot
new file mode 100644
index 0000000000000000000000000000000000000000..a80233c645cddbdf919ef8ca5c81f2b36ad9254a
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_12.dot
@@ -0,0 +1,1888 @@
+digraph G {
+"0" [label="(START)"];
+"1" [label="(Node ID: 0\nTopoID: 1\nifm_ddr)\n Buffer dim : {1,184,320,4}\n Buffer bound : {1,180,320,4}\n Buffer Size : 471040\n DataType : BF16", shape="rect", color="red"];
+"2" [label="(Node ID: 1\nTopoID: 2\nL2_IFM_Buffer_for_input0_0_port0)\n Buffer dim : {1,184,320,4}\n Buffer bound : {1,184,320,4}\n Buffer Size : 471040\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"3" [label="(Node ID: 1\nTopoID: 3\nDiv_2)\n(L-1)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"4" [label="(Node ID: 1\nTopoID: 4\nl2_1)\n Buffer dim : {1,192,320,4}\n Buffer bound : {1,184,320,4}\n Buffer Size : 491520\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"5" [label="(Node ID: 2\nTopoID: 5\nl2l3_1_spill)\n Buffer dim : {1,184,320,4}\n Buffer bound : {1,180,320,4}\n Buffer Size : 471040\n DataType : BF16", shape="rect", color="red"];
+"6" [label="(Node ID: 2\nTopoID: 6\nSlice_7)\n(SliceHCWC8Adf)\n(L-2)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"7" [label="(Node ID: 2\nTopoID: 7\nl2l3_2_spill)\n Buffer dim : {1,184,320,3}\n Buffer bound : {1,180,320,3}\n Buffer Size : 353280\n DataType : BF16", shape="rect", color="red"];
+"8" [label="(Node ID: 2\nTopoID: 8\nl2l3_scratch_0_3_spill)\n Buffer dim : {942080}\n Buffer bound : {942080}\n Buffer Size : 942080\n DataType : INT8", shape="rect", color="red"];
+"9" [label="(Node ID: 3\nTopoID: 9\nGenerated-#0)\n(BufferPadAdf)\n(L-3)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"10" [label="(Node ID: 4\nTopoID: 10\nl2l3_3_spill)\n Buffer dim : {1,184,320,8}\n Buffer bound : {1,180,320,3}\n Buffer Size : 942080\n DataType : BF16", shape="rect", color="red"];
+"11" [label="(Node ID: 4\nTopoID: 11\nGenerated-#2)\n(Transpose4dAdf)\n(L-4)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"12" [label="(Node ID: 4\nTopoID: 12\nl2l3_4_spill)\n Buffer dim : {1,8,184,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 942080\n DataType : BF16", shape="rect", color="red"];
+"13" [label="(Node ID: 4\nTopoID: 13\nl2l3_scratch_0_5_spill)\n Buffer dim : {921600}\n Buffer bound : {921600}\n Buffer Size : 921600\n DataType : INT8", shape="rect", color="red"];
+"14" [label="(Node ID: 5\nTopoID: 14\nGenerated-#4)\n(BufferUnpadAdf)\n(L-5)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"15" [label="(Node ID: 5\nTopoID: 15\nl2l3_5_spill)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"16" [label="(Node ID: 0\nTopoID: 16\nconst_ifm_ddr_5)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"17" [label="(Node ID: 6\nTopoID: 17\nL2_CONST_IFM_Buffer_for_input5_0_port1)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"18" [label="(Node ID: 6\nTopoID: 18\nL2_IFM_Buffer_from_layer_5_for_layer_6_port0)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"19" [label="(Node ID: 6\nTopoID: 19\nSub_14)\n(L-6)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"20" [label="(Node ID: 6\nTopoID: 20\nl2_6)\n Buffer dim : {1,32,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 819200\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"21" [label="(Node ID: 6\nTopoID: 21\nl2l3_6_spill)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"22" [label="(Node ID: 0\nTopoID: 22\nconst_ifm_ddr_4)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"23" [label="(Node ID: 7\nTopoID: 23\nL2_CONST_IFM_Buffer_for_input4_0_port1)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"24" [label="(Node ID: 7\nTopoID: 24\nL2_IFM_Buffer_from_layer_6_for_layer_7_port0)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"25" [label="(Node ID: 7\nTopoID: 25\nDiv_16)\n(L-7)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"26" [label="(Node ID: 7\nTopoID: 26\nl2_7)\n Buffer dim : {1,32,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 819200\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"27" [label="(Node ID: 7\nTopoID: 27\nl2l3_7_spill)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"28" [label="(Node ID: 8\nTopoID: 28\nL2_IFM_Buffer_from_layer_7_for_layer_8_port0)\n Buffer dim : {1,8,61,320}\n Buffer bound : {1,8,61,320}\n Buffer Size : 624640\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"29" [label="(Node ID: 8\nTopoID: 29\nConv_17)\n(L-8)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"30" [label="(Node ID: 8\nTopoID: 30\nl2_8)\n Buffer dim : {1,32,32,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 655360\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"31" [label="(Node ID: 8\nTopoID: 31\nl2l3_8_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"32" [label="(Node ID: 9\nTopoID: 32\nL2_IFM_Buffer_from_layer_8_for_layer_9_port0)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"33" [label="(Node ID: 9\nTopoID: 33\nAdd_19)\n(L-9)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"34" [label="(Node ID: 9\nTopoID: 34\nl2_9)\n Buffer dim : {1,32,92,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 942080\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"35" [label="(Node ID: 9\nTopoID: 35\nl2l3_9_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"36" [label="(Node ID: 10\nTopoID: 36\nL2_IFM_Buffer_from_layer_9_for_layer_10_port0)\n Buffer dim : {1,16,45,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 230400\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"37" [label="(Node ID: 10\nTopoID: 37\nClip_22)\n(L-10)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"38" [label="(Node ID: 10\nTopoID: 38\nl2_10)\n Buffer dim : {1,32,48,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 491520\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"39" [label="(Node ID: 10\nTopoID: 39\nl2l3_10_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"40" [label="(Node ID: 11\nTopoID: 40\nL2_IFM_Buffer_from_layer_10_for_layer_11_port0)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"41" [label="(Node ID: 11\nTopoID: 41\nDiv_24)\n(L-11)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"42" [label="(Node ID: 11\nTopoID: 42\nl2_11)\n Buffer dim : {1,32,92,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 942080\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"43" [label="(Node ID: 11\nTopoID: 43\nl2l3_11_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"44" [label="(Node ID: 12\nTopoID: 44\nL2_IFM_Buffer_from_layer_8_for_layer_12_port0)\n Buffer dim : {1,16,30,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 307200\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"45" [label="(Node ID: 12\nTopoID: 45\nL2_IFM_Buffer_from_layer_11_for_layer_12_port1)\n Buffer dim : {1,16,30,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 307200\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"46" [label="(Node ID: 12\nTopoID: 46\nMul_25)\n(L-12)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"47" [label="(Node ID: 12\nTopoID: 47\nl2_12)\n Buffer dim : {1,32,32,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 655360\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"48" [label="(Node ID: 12\nTopoID: 48\nl2l3_12_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"49" [label="(Node ID: 13\nTopoID: 49\nL2_IFM_Buffer_from_layer_12_for_layer_13_port0)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"50" [label="(Node ID: 13\nTopoID: 50\nConv_26)\n(L-13)\n TG Layer : False\n IncoreChain Kernels Type : DepthwiseConv2d", shape="ellipse"];
+"51" [label="(Node ID: 13\nTopoID: 51\nl2_13)\n Buffer dim : {1,32,96,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 983040\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"52" [label="(Node ID: 13\nTopoID: 52\nl2l3_13_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"53" [label="(Node ID: 14\nTopoID: 53\nL2_IFM_Buffer_from_layer_12_for_layer_14_port1)\n Buffer dim : {1,32,48,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 491520\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"54" [label="(Node ID: 14\nTopoID: 54\nL2_IFM_Buffer_from_layer_13_for_layer_14_port0)\n Buffer dim : {1,16,45,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 230400\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"55" [label="(Node ID: 14\nTopoID: 55\nConv_28)\n(L-14)\n TG Layer : False\n IncoreChain Kernels Type : Conv2dElementwiseBinary", shape="ellipse"];
+"56" [label="(Node ID: 14\nTopoID: 56\nl2_14)\n Buffer dim : {1,32,48,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 491520\n Buffer concat offset : { spill_L3_Concat_Buffer_layer_275 : {0,40,0,0}, l2l3_14_spill : {0,0,0,0} }\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"57" [label="(Node ID: 14\nTopoID: 57\nl2l3_14_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"58" [label="(Node ID: 15\nTopoID: 58\nL2_IFM_Buffer_from_layer_14_for_layer_15_port0)\n Buffer dim : {1,16,18,160}\n Buffer bound : {1,16,18,160}\n Buffer Size : 184320\n Tiling Factor : {1,1,5,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"59" [label="(Node ID: 15\nTopoID: 59\nConv_30)\n(L-15)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"60" [label="(Node ID: 15\nTopoID: 60\nl2_15)\n Buffer dim : {1,64,18,160}\n Buffer bound : {1,64,18,160}\n Buffer Size : 737280\n Tiling Factor : {1,1,5,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"61" [label="(Node ID: 15\nTopoID: 61\nl2l3_15_spill)\n Buffer dim : {1,64,90,160}\n Buffer bound : {1,64,90,160}\n Buffer Size : 1843200\n DataType : BF16", shape="rect", color="red"];
+"62" [label="(Node ID: 16\nTopoID: 62\nL2_IFM_Buffer_from_layer_15_for_layer_16_port0)\n Buffer dim : {1,64,17,160}\n Buffer bound : {1,64,17,160}\n Buffer Size : 696320\n Tiling Factor : {1,1,6,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"63" [label="(Node ID: 16\nTopoID: 63\nConv_32)\n(L-16)\n TG Layer : False\n IncoreChain Kernels Type : DepthwiseConv2d", shape="ellipse"];
+"64" [label="(Node ID: 16\nTopoID: 64\nl2_16)\n Buffer dim : {1,64,8,84}\n Buffer bound : {1,64,8,80}\n Buffer Size : 172032\n Tiling Factor : {1,1,6,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"65" [label="(Node ID: 16\nTopoID: 65\nl2l3_16_spill)\n Buffer dim : {1,64,48,80}\n Buffer bound : {1,64,45,80}\n Buffer Size : 491520\n DataType : BF16", shape="rect", color="red"];
+"66" [label="(Node ID: 16\nTopoID: 66\nl2l3_scratch_0_17_spill)\n Buffer dim : {460800}\n Buffer bound : {460800}\n Buffer Size : 460800\n DataType : INT8", shape="rect", color="red"];
+"67" [label="(Node ID: 17\nTopoID: 67\nGenerated-#60)\n(BufferUnpadAdf)\n(L-17)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"68" [label="(Node ID: 17\nTopoID: 68\nl2l3_17_spill)\n Buffer dim : {1,64,45,80}\n Buffer bound : {1,64,45,80}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"69" [label="(Node ID: 18\nTopoID: 69\nL2_IFM_Buffer_from_layer_17_for_layer_18_port0)\n Buffer dim : {1,64,45,80}\n Buffer bound : {1,64,45,80}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"70" [label="(Node ID: 18\nTopoID: 70\nConv_34)\n(L-18)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"71" [label="(Node ID: 18\nTopoID: 71\nl2_18)\n OFM_MEM_SHARE : 1\n Buffer dim : {1,64,48,80}\n Buffer bound : {1,24,45,80}\n Buffer Size : 491520\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"72" [label="(Node ID: 18\nTopoID: 72\nL3_OFM_Buffer_layer_TGSpilling_1818)\n Buffer dim : {1,24,45,80}\n Buffer bound : {1,24,45,80}\n Buffer Size : 172800\n DataType : BF16", shape="rect", color="red"];
+"73" [label="(Node ID: 19\nTopoID: 73\nConv_35)\n(L-19)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"74" [label="(Node ID: 19\nTopoID: 74\nl2_19)\n Buffer dim : {1,96,48,96}\n Buffer bound : {1,72,45,80}\n Buffer Size : 884736\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"75" [label="(Node ID: 19\nTopoID: 75\nl2l3_19_spill)\n Buffer dim : {1,72,45,80}\n Buffer bound : {1,72,45,80}\n Buffer Size : 518400\n DataType : BF16", shape="rect", color="red"];
+"76" [label="(Node ID: 20\nTopoID: 76\nL2_IFM_Buffer_from_layer_19_for_layer_20_port0)\n Buffer dim : {1,72,25,80}\n Buffer bound : {1,72,25,80}\n Buffer Size : 288000\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"77" [label="(Node ID: 20\nTopoID: 77\nConv_37)\n(L-20)\n TG Layer : False\n IncoreChain Kernels Type : DepthwiseConv2d", shape="ellipse"];
+"78" [label="(Node ID: 20\nTopoID: 78\nl2_20)\n Buffer dim : {1,96,24,80}\n Buffer bound : {1,72,23,80}\n Buffer Size : 368640\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"79" [label="(Node ID: 20\nTopoID: 79\nl2l3_20_spill)\n Buffer dim : {1,72,46,80}\n Buffer bound : {1,72,45,80}\n Buffer Size : 529920\n DataType : BF16", shape="rect", color="red"];
+"80" [label="(Node ID: 20\nTopoID: 80\nl2l3_scratch_0_21_spill)\n Buffer dim : {518400}\n Buffer bound : {518400}\n Buffer Size : 518400\n DataType : INT8", shape="rect", color="red"];
+"81" [label="(Node ID: 21\nTopoID: 81\nGenerated-#62)\n(BufferUnpadAdf)\n(L-21)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"82" [label="(Node ID: 21\nTopoID: 82\nl2l3_21_spill)\n Buffer dim : {1,72,45,80}\n Buffer bound : {1,72,45,80}\n Buffer Size : 518400\n DataType : BF16", shape="rect", color="red"];
+"83" [label="(Node ID: 22\nTopoID: 83\nL2_OFM_Buffer_layer_TGSpilling_1818)\n OFM_MEM_SHARE : 1\n Buffer dim : {1,64,48,80}\n Buffer bound : {1,24,45,80}\n Buffer Size : 491520\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"84" [label="(Node ID: 22\nTopoID: 84\nL2_IFM_Buffer_from_layer_21_for_layer_22_port0)\n Buffer dim : {1,72,45,80}\n Buffer bound : {1,72,45,80}\n Buffer Size : 518400\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"85" [label="(Node ID: 22\nTopoID: 85\nConv_39)\n(L-22)\n OFM_MEM_SHARE : 1\n TG Layer : False\n IncoreChain Kernels Type : Conv2dElementwiseBinary", shape="ellipse"];
+"86" [label="(Node ID: 22\nTopoID: 86\nl2_22)\n Buffer dim : {1,64,48,80}\n Buffer bound : {1,24,45,80}\n Buffer Size : 491520\n Buffer concat offset : { l2l3_22_spill : {0,0,0,0}, spill_L3_Concat_Buffer_layer_256 : {0,80,0,0} }\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"87" [label="(Node ID: 23\nTopoID: 87\nConv_41)\n(L-23)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"687" [label="(Node ID: 251\nTopoID: 687\nMul_387)\n(L-251)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"695" [label="(Node ID: 254\nTopoID: 695\nResize_391)\n(ResizeAdf)\n(L-254)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"702" [label="(Node ID: 257\nTopoID: 702\nConv_399)\n(L-257)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"704" [label="(Node ID: 257\nTopoID: 704\nl2l3_257_spill)\n Buffer dim : {1,40,45,80}\n Buffer bound : {1,40,45,80}\n Buffer Size : 288000\n DataType : BF16", shape="rect", color="red"];
+"705" [label="(Node ID: 258\nTopoID: 705\nSplit_401_Duplicated#0)\n(SliceHCWC8Adf)\n(L-258)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"713" [label="(Node ID: 261\nTopoID: 713\nConv_403)\n(L-261)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"726" [label="(Node ID: 265\nTopoID: 726\nMul_412)\n(L-265)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"729" [label="(Node ID: 266\nTopoID: 729\nSplit_405_Duplicated#0)\n(SliceHCWC8Adf)\n(L-266)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"735" [label="(Node ID: 267\nTopoID: 735\nl2l3_267_spill)\n Buffer dim : {1,24,45,80}\n Buffer bound : {1,20,45,80}\n Buffer Size : 172800\n DataType : BF16", shape="rect", color="red"];
+"736" [label="(Node ID: 268\nTopoID: 736\nConcat_407)\n(ConcatC8Adf)\n(L-268)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"744" [label="(Node ID: 271\nTopoID: 744\nMul_413)\n(L-271)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"746" [label="(Node ID: 272\nTopoID: 746\nL2_OFM_Buffer_layer_TGSpilling_265265)\n Buffer dim : {1,32,48,80}\n Buffer bound : {1,24,45,80}\n Buffer Size : 245760\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"747" [label="(Node ID: 272\nTopoID: 747\nAdd_414)\n(L-272)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"750" [label="(Node ID: 273\nTopoID: 750\nConcat_415)\n(ConcatC8Adf)\n(L-273)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"755" [label="(Node ID: 276\nTopoID: 755\nConv_419)\n(L-276)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"757" [label="(Node ID: 276\nTopoID: 757\nl2l3_276_spill)\n Buffer dim : {1,32,90,160}\n Buffer bound : {1,32,90,160}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"758" [label="(Node ID: 277\nTopoID: 758\nSplit_421_Duplicated#0)\n(SliceHCWC8Adf)\n(L-277)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"760" [label="(Node ID: 278\nTopoID: 760\nSplit_421_Duplicated#1)\n(SliceHCWC8Adf)\n(L-278)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"767" [label="(Node ID: 280\nTopoID: 767\nConv_423)\n(L-280)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"769" [label="(Node ID: 280\nTopoID: 769\nl2l3_280_spill)\n Buffer dim : {1,32,90,160}\n Buffer bound : {1,32,90,160}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
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+"771" [label="(Node ID: 281\nTopoID: 771\nSigmoid_424)\n(L-281)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
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+"773" [label="(Node ID: 281\nTopoID: 773\nl2l3_281_spill)\n Buffer dim : {1,32,90,160}\n Buffer bound : {1,32,90,160}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"774" [label="(Node ID: 282\nTopoID: 774\nSplit_425_Duplicated#1)\n(SliceHCWC8Adf)\n(L-282)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_2.dot b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_2.dot
new file mode 100644
index 0000000000000000000000000000000000000000..0668ded3f353bf11b4ac33ddfee11213e2c8e0a2
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_2.dot
@@ -0,0 +1,1822 @@
+digraph G {
+"0" [label="(START)"];
+"1" [label="(Node ID: 0\nTopoID: 1\nifm_ddr)\n Buffer dim : {1,184,320,4}\n Buffer bound : {1,180,320,4}\n Buffer Size : 471040\n DataType : BF16", shape="rect", color="red"];
+"2" [label="(Node ID: 1\nTopoID: 2\nL2_IFM_Buffer_for_input0_0_port0)\n Buffer dim : {1,184,320,4}\n Buffer bound : {1,184,320,4}\n Buffer Size : 471040\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
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+"6" [label="(Node ID: 2\nTopoID: 6\nSlice_7)\n(SliceHCWC8Adf)\n(L-2)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"8" [label="(Node ID: 2\nTopoID: 8\nl2l3_scratch_0_3_spill)\n Buffer dim : {942080}\n Buffer bound : {942080}\n Buffer Size : 942080\n DataType : INT8", shape="rect", color="red"];
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+"11" [label="(Node ID: 4\nTopoID: 11\nGenerated-#2)\n(Transpose4dAdf)\n(L-4)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"18" [label="(Node ID: 6\nTopoID: 18\nL2_IFM_Buffer_from_layer_5_for_layer_6_port0)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
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+"35" [label="(Node ID: 9\nTopoID: 35\nl2l3_9_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"36" [label="(Node ID: 10\nTopoID: 36\nL2_IFM_Buffer_from_layer_9_for_layer_10_port0)\n Buffer dim : {1,16,45,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 230400\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"37" [label="(Node ID: 10\nTopoID: 37\nClip_22)\n(L-10)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
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+"39" [label="(Node ID: 10\nTopoID: 39\nl2l3_10_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"40" [label="(Node ID: 11\nTopoID: 40\nL2_IFM_Buffer_from_layer_10_for_layer_11_port0)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"41" [label="(Node ID: 11\nTopoID: 41\nDiv_24)\n(L-11)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"42" [label="(Node ID: 11\nTopoID: 42\nl2_11)\n Buffer dim : {1,32,92,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 942080\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"43" [label="(Node ID: 11\nTopoID: 43\nl2l3_11_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"44" [label="(Node ID: 12\nTopoID: 44\nL2_IFM_Buffer_from_layer_8_for_layer_12_port0)\n Buffer dim : {1,16,30,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 307200\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"45" [label="(Node ID: 12\nTopoID: 45\nL2_IFM_Buffer_from_layer_11_for_layer_12_port1)\n Buffer dim : {1,16,30,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 307200\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"46" [label="(Node ID: 12\nTopoID: 46\nMul_25)\n(L-12)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"48" [label="(Node ID: 12\nTopoID: 48\nl2l3_12_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
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+"652" [label="(Node ID: 245\nTopoID: 652\nMul_386)\n(L-245)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"654" [label="(Node ID: 246\nTopoID: 654\nSplit_379_Duplicated#0)\n(SliceHCWC8Adf)\n(L-246)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"658" [label="(Node ID: 247\nTopoID: 658\nMul_380)\n(L-247)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"670" [label="(Node ID: 252\nTopoID: 670\nAdd_388)\n(L-252)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"675" [label="(Node ID: 254\nTopoID: 675\nResize_391)\n(ResizeAdf)\n(L-254)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"680" [label="(Node ID: 256\nTopoID: 680\nspill_L3_Concat_Buffer_layer_256)\n Buffer dim : {1,112,45,80}\n Buffer bound : {1,107,45,80}\n Buffer Size : 806400\n DataType : BF16", shape="rect", color="red"];
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+"682" [label="(Node ID: 257\nTopoID: 682\nConv_399)\n(L-257)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"684" [label="(Node ID: 257\nTopoID: 684\nl2l3_257_spill)\n Buffer dim : {1,40,45,80}\n Buffer bound : {1,40,45,80}\n Buffer Size : 288000\n DataType : BF16", shape="rect", color="red"];
+"685" [label="(Node ID: 258\nTopoID: 685\nSplit_401_Duplicated#0)\n(SliceHCWC8Adf)\n(L-258)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"708" [label="(Node ID: 266\nTopoID: 708\nSplit_405_Duplicated#0)\n(SliceHCWC8Adf)\n(L-266)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"714" [label="(Node ID: 267\nTopoID: 714\nl2l3_267_spill)\n Buffer dim : {1,24,45,80}\n Buffer bound : {1,20,45,80}\n Buffer Size : 172800\n DataType : BF16", shape="rect", color="red"];
+"715" [label="(Node ID: 268\nTopoID: 715\nConcat_407)\n(ConcatC8Adf)\n(L-268)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"718" [label="(Node ID: 269\nTopoID: 718\nConv_408)\n(L-269)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"720" [label="(Node ID: 270\nTopoID: 720\nTanh_409)\n(L-270)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
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+"723" [label="(Node ID: 271\nTopoID: 723\nMul_413)\n(L-271)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"725" [label="(Node ID: 272\nTopoID: 725\nAdd_414)\n(L-272)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"727" [label="(Node ID: 272\nTopoID: 727\nofm_ddr_2_l2l3_272_spill)\n Buffer dim : {1,24,45,80}\n Buffer bound : {1,20,45,80}\n Buffer Size : 172800\n DataType : BF16", shape="rect", color="red"];
+"728" [label="(Node ID: 273\nTopoID: 728\nConcat_415)\n(ConcatC8Adf)\n(L-273)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"733" [label="(Node ID: 276\nTopoID: 733\nConv_419)\n(L-276)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"735" [label="(Node ID: 276\nTopoID: 735\nl2l3_276_spill)\n Buffer dim : {1,32,90,160}\n Buffer bound : {1,32,90,160}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"736" [label="(Node ID: 277\nTopoID: 736\nSplit_421_Duplicated#0)\n(SliceHCWC8Adf)\n(L-277)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"738" [label="(Node ID: 278\nTopoID: 738\nSplit_421_Duplicated#1)\n(SliceHCWC8Adf)\n(L-278)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_3.dot b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_3.dot
new file mode 100644
index 0000000000000000000000000000000000000000..0ae3a1c6364037bf589cdef5aa21ae5b5cd63ee4
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_3.dot
@@ -0,0 +1,1834 @@
+digraph G {
+"0" [label="(START)"];
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+"2" [label="(Node ID: 1\nTopoID: 2\nL2_IFM_Buffer_for_input0_0_port0)\n Buffer dim : {1,184,320,4}\n Buffer bound : {1,184,320,4}\n Buffer Size : 471040\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
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+"560" [label="(Node ID: 212\nTopoID: 560\nl2l3_212_spill)\n Buffer dim : {1,128,1,1}\n Buffer bound : {1,128,1,1}\n Buffer Size : 256\n DataType : BF16", shape="rect", color="red"];
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+"634" [label="(Node ID: 238\nTopoID: 634\nSplit_375_Duplicated#0)\n(SliceHCWC8Adf)\n(L-238)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_4.dot b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_4.dot
new file mode 100644
index 0000000000000000000000000000000000000000..ce965ad6fd99756ea4a2b133868abb87d2c31db9
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_4.dot
@@ -0,0 +1,1840 @@
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+"714" [label="(Node ID: 266\nTopoID: 714\nSplit_405_Duplicated#0)\n(SliceHCWC8Adf)\n(L-266)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_5.dot b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_5.dot
new file mode 100644
index 0000000000000000000000000000000000000000..d0e5f85ce644540c398ca76baea9848c267624e6
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_5.dot
@@ -0,0 +1,1852 @@
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+"620" [label="(Node ID: 231\nTopoID: 620\nspill_L3_Concat_Buffer_layer_230)\n Buffer dim : {1,128,12,20}\n Buffer bound : {1,128,12,20}\n Buffer Size : 61440\n DataType : BF16", shape="rect", color="red"];
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+"629" [label="(Node ID: 233\nTopoID: 629\nl2l3_233_spill)\n Buffer dim : {1,8,90,160}\n Buffer bound : {1,3,90,160}\n Buffer Size : 230400\n DataType : BF16", shape="rect", color="red"];
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+"631" [label="(Node ID: 234\nTopoID: 631\nAveragePool_347)\n(L-234)\n TG Layer : False\n IncoreChain Kernels Type : AvgPool2d", shape="ellipse"];
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+"633" [label="(Node ID: 235\nTopoID: 633\nAveragePool_348)\n(L-235)\n TG Layer : False\n IncoreChain Kernels Type : AvgPool2d", shape="ellipse"];
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+"637" [label="(Node ID: 237\nTopoID: 637\nConv_373)\n(L-237)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"639" [label="(Node ID: 237\nTopoID: 639\nl2l3_237_spill)\n Buffer dim : {1,80,23,40}\n Buffer bound : {1,80,23,40}\n Buffer Size : 147200\n DataType : BF16", shape="rect", color="red"];
+"640" [label="(Node ID: 238\nTopoID: 640\nSplit_375_Duplicated#0)\n(SliceHCWC8Adf)\n(L-238)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"642" [label="(Node ID: 239\nTopoID: 642\nSplit_375_Duplicated#1)\n(SliceHCWC8Adf)\n(L-239)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"664" [label="(Node ID: 246\nTopoID: 664\nSplit_379_Duplicated#0)\n(SliceHCWC8Adf)\n(L-246)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"673" [label="(Node ID: 249\nTopoID: 673\nConv_382)\n(L-249)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"678" [label="(Node ID: 251\nTopoID: 678\nMul_387)\n(L-251)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"684" [label="(Node ID: 254\nTopoID: 684\nspill_L3_Concat_Buffer_layer_253)\n Buffer dim : {1,80,23,40}\n Buffer bound : {1,80,23,40}\n Buffer Size : 147200\n DataType : BF16", shape="rect", color="red"];
+"685" [label="(Node ID: 254\nTopoID: 685\nResize_391)\n(ResizeAdf)\n(L-254)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"687" [label="(Node ID: 255\nTopoID: 687\nSlice_397)\n(SliceHCWC8Adf)\n(L-255)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"690" [label="(Node ID: 256\nTopoID: 690\nspill_L3_Concat_Buffer_layer_256)\n Buffer dim : {1,112,45,80}\n Buffer bound : {1,107,45,80}\n Buffer Size : 806400\n DataType : BF16", shape="rect", color="red"];
+"691" [label="(Node ID: 257\nTopoID: 691\nL2_IFM_Buffer_from_layer_256_for_layer_257_port0)\n Buffer dim : {1,112,45,80}\n Buffer bound : {1,112,45,80}\n Buffer Size : 806400\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"692" [label="(Node ID: 257\nTopoID: 692\nConv_399)\n(L-257)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"694" [label="(Node ID: 257\nTopoID: 694\nl2l3_257_spill)\n Buffer dim : {1,40,45,80}\n Buffer bound : {1,40,45,80}\n Buffer Size : 288000\n DataType : BF16", shape="rect", color="red"];
+"695" [label="(Node ID: 258\nTopoID: 695\nSplit_401_Duplicated#0)\n(SliceHCWC8Adf)\n(L-258)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"697" [label="(Node ID: 259\nTopoID: 697\nSplit_401_Duplicated#1)\n(SliceHCWC8Adf)\n(L-259)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_6.dot b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_6.dot
new file mode 100644
index 0000000000000000000000000000000000000000..235872edb21338f0baf4af15206d84b5905a5e9c
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_6.dot
@@ -0,0 +1,1858 @@
+digraph G {
+"0" [label="(START)"];
+"1" [label="(Node ID: 0\nTopoID: 1\nifm_ddr)\n Buffer dim : {1,184,320,4}\n Buffer bound : {1,180,320,4}\n Buffer Size : 471040\n DataType : BF16", shape="rect", color="red"];
+"2" [label="(Node ID: 1\nTopoID: 2\nL2_IFM_Buffer_for_input0_0_port0)\n Buffer dim : {1,184,320,4}\n Buffer bound : {1,184,320,4}\n Buffer Size : 471040\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"3" [label="(Node ID: 1\nTopoID: 3\nDiv_2)\n(L-1)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"4" [label="(Node ID: 1\nTopoID: 4\nl2_1)\n Buffer dim : {1,192,320,4}\n Buffer bound : {1,184,320,4}\n Buffer Size : 491520\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"5" [label="(Node ID: 2\nTopoID: 5\nl2l3_1_spill)\n Buffer dim : {1,184,320,4}\n Buffer bound : {1,180,320,4}\n Buffer Size : 471040\n DataType : BF16", shape="rect", color="red"];
+"6" [label="(Node ID: 2\nTopoID: 6\nSlice_7)\n(SliceHCWC8Adf)\n(L-2)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"7" [label="(Node ID: 2\nTopoID: 7\nl2l3_2_spill)\n Buffer dim : {1,184,320,3}\n Buffer bound : {1,180,320,3}\n Buffer Size : 353280\n DataType : BF16", shape="rect", color="red"];
+"8" [label="(Node ID: 2\nTopoID: 8\nl2l3_scratch_0_3_spill)\n Buffer dim : {942080}\n Buffer bound : {942080}\n Buffer Size : 942080\n DataType : INT8", shape="rect", color="red"];
+"9" [label="(Node ID: 3\nTopoID: 9\nGenerated-#0)\n(BufferPadAdf)\n(L-3)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"10" [label="(Node ID: 4\nTopoID: 10\nl2l3_3_spill)\n Buffer dim : {1,184,320,8}\n Buffer bound : {1,180,320,3}\n Buffer Size : 942080\n DataType : BF16", shape="rect", color="red"];
+"11" [label="(Node ID: 4\nTopoID: 11\nGenerated-#2)\n(Transpose4dAdf)\n(L-4)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"12" [label="(Node ID: 4\nTopoID: 12\nl2l3_4_spill)\n Buffer dim : {1,8,184,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 942080\n DataType : BF16", shape="rect", color="red"];
+"13" [label="(Node ID: 4\nTopoID: 13\nl2l3_scratch_0_5_spill)\n Buffer dim : {921600}\n Buffer bound : {921600}\n Buffer Size : 921600\n DataType : INT8", shape="rect", color="red"];
+"14" [label="(Node ID: 5\nTopoID: 14\nGenerated-#4)\n(BufferUnpadAdf)\n(L-5)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"15" [label="(Node ID: 5\nTopoID: 15\nl2l3_5_spill)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"16" [label="(Node ID: 0\nTopoID: 16\nconst_ifm_ddr_5)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"17" [label="(Node ID: 6\nTopoID: 17\nL2_CONST_IFM_Buffer_for_input5_0_port1)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"18" [label="(Node ID: 6\nTopoID: 18\nL2_IFM_Buffer_from_layer_5_for_layer_6_port0)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"19" [label="(Node ID: 6\nTopoID: 19\nSub_14)\n(L-6)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"20" [label="(Node ID: 6\nTopoID: 20\nl2_6)\n Buffer dim : {1,32,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 819200\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"21" [label="(Node ID: 6\nTopoID: 21\nl2l3_6_spill)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"22" [label="(Node ID: 0\nTopoID: 22\nconst_ifm_ddr_4)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"23" [label="(Node ID: 7\nTopoID: 23\nL2_CONST_IFM_Buffer_for_input4_0_port1)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"24" [label="(Node ID: 7\nTopoID: 24\nL2_IFM_Buffer_from_layer_6_for_layer_7_port0)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"25" [label="(Node ID: 7\nTopoID: 25\nDiv_16)\n(L-7)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"27" [label="(Node ID: 7\nTopoID: 27\nl2l3_7_spill)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"28" [label="(Node ID: 8\nTopoID: 28\nL2_IFM_Buffer_from_layer_7_for_layer_8_port0)\n Buffer dim : {1,8,61,320}\n Buffer bound : {1,8,61,320}\n Buffer Size : 624640\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"29" [label="(Node ID: 8\nTopoID: 29\nConv_17)\n(L-8)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"30" [label="(Node ID: 8\nTopoID: 30\nl2_8)\n Buffer dim : {1,32,32,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 655360\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"31" [label="(Node ID: 8\nTopoID: 31\nl2l3_8_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"32" [label="(Node ID: 9\nTopoID: 32\nL2_IFM_Buffer_from_layer_8_for_layer_9_port0)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"33" [label="(Node ID: 9\nTopoID: 33\nAdd_19)\n(L-9)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"34" [label="(Node ID: 9\nTopoID: 34\nl2_9)\n Buffer dim : {1,32,92,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 942080\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"35" [label="(Node ID: 9\nTopoID: 35\nl2l3_9_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"36" [label="(Node ID: 10\nTopoID: 36\nL2_IFM_Buffer_from_layer_9_for_layer_10_port0)\n Buffer dim : {1,16,45,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 230400\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"37" [label="(Node ID: 10\nTopoID: 37\nClip_22)\n(L-10)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"38" [label="(Node ID: 10\nTopoID: 38\nl2_10)\n Buffer dim : {1,32,48,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 491520\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"39" [label="(Node ID: 10\nTopoID: 39\nl2l3_10_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"40" [label="(Node ID: 11\nTopoID: 40\nL2_IFM_Buffer_from_layer_10_for_layer_11_port0)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"41" [label="(Node ID: 11\nTopoID: 41\nDiv_24)\n(L-11)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"42" [label="(Node ID: 11\nTopoID: 42\nl2_11)\n Buffer dim : {1,32,92,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 942080\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"43" [label="(Node ID: 11\nTopoID: 43\nl2l3_11_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"44" [label="(Node ID: 12\nTopoID: 44\nL2_IFM_Buffer_from_layer_8_for_layer_12_port0)\n Buffer dim : {1,16,30,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 307200\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"45" [label="(Node ID: 12\nTopoID: 45\nL2_IFM_Buffer_from_layer_11_for_layer_12_port1)\n Buffer dim : {1,16,30,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 307200\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"46" [label="(Node ID: 12\nTopoID: 46\nMul_25)\n(L-12)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"47" [label="(Node ID: 12\nTopoID: 47\nl2_12)\n Buffer dim : {1,32,32,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 655360\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"48" [label="(Node ID: 12\nTopoID: 48\nl2l3_12_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"49" [label="(Node ID: 13\nTopoID: 49\nL2_IFM_Buffer_from_layer_12_for_layer_13_port0)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"50" [label="(Node ID: 13\nTopoID: 50\nConv_26)\n(L-13)\n TG Layer : False\n IncoreChain Kernels Type : DepthwiseConv2d", shape="ellipse"];
+"51" [label="(Node ID: 13\nTopoID: 51\nl2_13)\n Buffer dim : {1,32,96,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 983040\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"52" [label="(Node ID: 13\nTopoID: 52\nl2l3_13_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"53" [label="(Node ID: 14\nTopoID: 53\nL2_IFM_Buffer_from_layer_12_for_layer_14_port1)\n Buffer dim : {1,32,48,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 491520\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"54" [label="(Node ID: 14\nTopoID: 54\nL2_IFM_Buffer_from_layer_13_for_layer_14_port0)\n Buffer dim : {1,16,45,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 230400\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"55" [label="(Node ID: 14\nTopoID: 55\nConv_28)\n(L-14)\n TG Layer : False\n IncoreChain Kernels Type : Conv2dElementwiseBinary", shape="ellipse"];
+"56" [label="(Node ID: 14\nTopoID: 56\nl2_14)\n Buffer dim : {1,32,48,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 491520\n Buffer concat offset : { spill_L3_Concat_Buffer_layer_275 : {0,40,0,0}, l2l3_14_spill : {0,0,0,0} }\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"57" [label="(Node ID: 14\nTopoID: 57\nl2l3_14_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"58" [label="(Node ID: 15\nTopoID: 58\nL2_IFM_Buffer_from_layer_14_for_layer_15_port0)\n Buffer dim : {1,16,18,160}\n Buffer bound : {1,16,18,160}\n Buffer Size : 184320\n Tiling Factor : {1,1,5,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"59" [label="(Node ID: 15\nTopoID: 59\nConv_30)\n(L-15)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"60" [label="(Node ID: 15\nTopoID: 60\nl2_15)\n Buffer dim : {1,64,18,160}\n Buffer bound : {1,64,18,160}\n Buffer Size : 737280\n Tiling Factor : {1,1,5,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"61" [label="(Node ID: 15\nTopoID: 61\nl2l3_15_spill)\n Buffer dim : {1,64,90,160}\n Buffer bound : {1,64,90,160}\n Buffer Size : 1843200\n DataType : BF16", shape="rect", color="red"];
+"62" [label="(Node ID: 16\nTopoID: 62\nL2_IFM_Buffer_from_layer_15_for_layer_16_port0)\n Buffer dim : {1,64,17,160}\n Buffer bound : {1,64,17,160}\n Buffer Size : 696320\n Tiling Factor : {1,1,6,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"63" [label="(Node ID: 16\nTopoID: 63\nConv_32)\n(L-16)\n TG Layer : False\n IncoreChain Kernels Type : DepthwiseConv2d", shape="ellipse"];
+"64" [label="(Node ID: 16\nTopoID: 64\nl2_16)\n Buffer dim : {1,64,8,84}\n Buffer bound : {1,64,8,80}\n Buffer Size : 172032\n Tiling Factor : {1,1,6,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"65" [label="(Node ID: 16\nTopoID: 65\nl2l3_16_spill)\n Buffer dim : {1,64,48,80}\n Buffer bound : {1,64,45,80}\n Buffer Size : 491520\n DataType : BF16", shape="rect", color="red"];
+"66" [label="(Node ID: 16\nTopoID: 66\nl2l3_scratch_0_17_spill)\n Buffer dim : {460800}\n Buffer bound : {460800}\n Buffer Size : 460800\n DataType : INT8", shape="rect", color="red"];
+"67" [label="(Node ID: 17\nTopoID: 67\nGenerated-#60)\n(BufferUnpadAdf)\n(L-17)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"68" [label="(Node ID: 17\nTopoID: 68\nl2l3_17_spill)\n Buffer dim : {1,64,45,80}\n Buffer bound : {1,64,45,80}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"69" [label="(Node ID: 18\nTopoID: 69\nL2_IFM_Buffer_from_layer_17_for_layer_18_port0)\n Buffer dim : {1,64,45,80}\n Buffer bound : {1,64,45,80}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"70" [label="(Node ID: 18\nTopoID: 70\nConv_34)\n(L-18)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"71" [label="(Node ID: 18\nTopoID: 71\nl2_18)\n OFM_MEM_SHARE : 1\n Buffer dim : {1,64,48,80}\n Buffer bound : {1,24,45,80}\n Buffer Size : 491520\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"72" [label="(Node ID: 18\nTopoID: 72\nL3_OFM_Buffer_layer_TGSpilling_1818)\n Buffer dim : {1,24,45,80}\n Buffer bound : {1,24,45,80}\n Buffer Size : 172800\n DataType : BF16", shape="rect", color="red"];
+"73" [label="(Node ID: 19\nTopoID: 73\nConv_35)\n(L-19)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"74" [label="(Node ID: 19\nTopoID: 74\nl2_19)\n Buffer dim : {1,96,48,96}\n Buffer bound : {1,72,45,80}\n Buffer Size : 884736\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"75" [label="(Node ID: 19\nTopoID: 75\nl2l3_19_spill)\n Buffer dim : {1,72,45,80}\n Buffer bound : {1,72,45,80}\n Buffer Size : 518400\n DataType : BF16", shape="rect", color="red"];
+"76" [label="(Node ID: 20\nTopoID: 76\nL2_IFM_Buffer_from_layer_19_for_layer_20_port0)\n Buffer dim : {1,72,25,80}\n Buffer bound : {1,72,25,80}\n Buffer Size : 288000\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"77" [label="(Node ID: 20\nTopoID: 77\nConv_37)\n(L-20)\n TG Layer : False\n IncoreChain Kernels Type : DepthwiseConv2d", shape="ellipse"];
+"78" [label="(Node ID: 20\nTopoID: 78\nl2_20)\n Buffer dim : {1,96,24,80}\n Buffer bound : {1,72,23,80}\n Buffer Size : 368640\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"79" [label="(Node ID: 20\nTopoID: 79\nl2l3_20_spill)\n Buffer dim : {1,72,46,80}\n Buffer bound : {1,72,45,80}\n Buffer Size : 529920\n DataType : BF16", shape="rect", color="red"];
+"80" [label="(Node ID: 20\nTopoID: 80\nl2l3_scratch_0_21_spill)\n Buffer dim : {518400}\n Buffer bound : {518400}\n Buffer Size : 518400\n DataType : INT8", shape="rect", color="red"];
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+"687" [label="(Node ID: 254\nTopoID: 687\nResize_391)\n(ResizeAdf)\n(L-254)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"720" [label="(Node ID: 266\nTopoID: 720\nSplit_405_Duplicated#0)\n(SliceHCWC8Adf)\n(L-266)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"745" [label="(Node ID: 276\nTopoID: 745\nConv_419)\n(L-276)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"757" [label="(Node ID: 280\nTopoID: 757\nConv_423)\n(L-280)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"761" [label="(Node ID: 281\nTopoID: 761\nSigmoid_424)\n(L-281)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
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+"763" [label="(Node ID: 281\nTopoID: 763\nl2l3_281_spill)\n Buffer dim : {1,32,90,160}\n Buffer bound : {1,32,90,160}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"764" [label="(Node ID: 282\nTopoID: 764\nSplit_425_Duplicated#1)\n(SliceHCWC8Adf)\n(L-282)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"769" [label="(Node ID: 283\nTopoID: 769\nSub_431)\n(L-283)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_7.dot b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_7.dot
new file mode 100644
index 0000000000000000000000000000000000000000..1f83cc393fdc61a52fedb59e2ba4aac3f78ecbc7
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_7.dot
@@ -0,0 +1,1864 @@
+digraph G {
+"0" [label="(START)"];
+"1" [label="(Node ID: 0\nTopoID: 1\nifm_ddr)\n Buffer dim : {1,184,320,4}\n Buffer bound : {1,180,320,4}\n Buffer Size : 471040\n DataType : BF16", shape="rect", color="red"];
+"2" [label="(Node ID: 1\nTopoID: 2\nL2_IFM_Buffer_for_input0_0_port0)\n Buffer dim : {1,184,320,4}\n Buffer bound : {1,184,320,4}\n Buffer Size : 471040\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"3" [label="(Node ID: 1\nTopoID: 3\nDiv_2)\n(L-1)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
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+"5" [label="(Node ID: 2\nTopoID: 5\nl2l3_1_spill)\n Buffer dim : {1,184,320,4}\n Buffer bound : {1,180,320,4}\n Buffer Size : 471040\n DataType : BF16", shape="rect", color="red"];
+"6" [label="(Node ID: 2\nTopoID: 6\nSlice_7)\n(SliceHCWC8Adf)\n(L-2)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"8" [label="(Node ID: 2\nTopoID: 8\nl2l3_scratch_0_3_spill)\n Buffer dim : {942080}\n Buffer bound : {942080}\n Buffer Size : 942080\n DataType : INT8", shape="rect", color="red"];
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+"11" [label="(Node ID: 4\nTopoID: 11\nGenerated-#2)\n(Transpose4dAdf)\n(L-4)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"13" [label="(Node ID: 4\nTopoID: 13\nl2l3_scratch_0_5_spill)\n Buffer dim : {921600}\n Buffer bound : {921600}\n Buffer Size : 921600\n DataType : INT8", shape="rect", color="red"];
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+"16" [label="(Node ID: 0\nTopoID: 16\nconst_ifm_ddr_5)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"17" [label="(Node ID: 6\nTopoID: 17\nL2_CONST_IFM_Buffer_for_input5_0_port1)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"18" [label="(Node ID: 6\nTopoID: 18\nL2_IFM_Buffer_from_layer_5_for_layer_6_port0)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
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+"23" [label="(Node ID: 7\nTopoID: 23\nL2_CONST_IFM_Buffer_for_input4_0_port1)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
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+"31" [label="(Node ID: 8\nTopoID: 31\nl2l3_8_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"32" [label="(Node ID: 9\nTopoID: 32\nL2_IFM_Buffer_from_layer_8_for_layer_9_port0)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"33" [label="(Node ID: 9\nTopoID: 33\nAdd_19)\n(L-9)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
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+"35" [label="(Node ID: 9\nTopoID: 35\nl2l3_9_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"36" [label="(Node ID: 10\nTopoID: 36\nL2_IFM_Buffer_from_layer_9_for_layer_10_port0)\n Buffer dim : {1,16,45,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 230400\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"37" [label="(Node ID: 10\nTopoID: 37\nClip_22)\n(L-10)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"38" [label="(Node ID: 10\nTopoID: 38\nl2_10)\n Buffer dim : {1,32,48,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 491520\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"39" [label="(Node ID: 10\nTopoID: 39\nl2l3_10_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"40" [label="(Node ID: 11\nTopoID: 40\nL2_IFM_Buffer_from_layer_10_for_layer_11_port0)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"41" [label="(Node ID: 11\nTopoID: 41\nDiv_24)\n(L-11)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"42" [label="(Node ID: 11\nTopoID: 42\nl2_11)\n Buffer dim : {1,32,92,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 942080\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"43" [label="(Node ID: 11\nTopoID: 43\nl2l3_11_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"44" [label="(Node ID: 12\nTopoID: 44\nL2_IFM_Buffer_from_layer_8_for_layer_12_port0)\n Buffer dim : {1,16,30,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 307200\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"45" [label="(Node ID: 12\nTopoID: 45\nL2_IFM_Buffer_from_layer_11_for_layer_12_port1)\n Buffer dim : {1,16,30,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 307200\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"46" [label="(Node ID: 12\nTopoID: 46\nMul_25)\n(L-12)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"47" [label="(Node ID: 12\nTopoID: 47\nl2_12)\n Buffer dim : {1,32,32,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 655360\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"48" [label="(Node ID: 12\nTopoID: 48\nl2l3_12_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"49" [label="(Node ID: 13\nTopoID: 49\nL2_IFM_Buffer_from_layer_12_for_layer_13_port0)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"50" [label="(Node ID: 13\nTopoID: 50\nConv_26)\n(L-13)\n TG Layer : False\n IncoreChain Kernels Type : DepthwiseConv2d", shape="ellipse"];
+"51" [label="(Node ID: 13\nTopoID: 51\nl2_13)\n Buffer dim : {1,32,96,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 983040\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"52" [label="(Node ID: 13\nTopoID: 52\nl2l3_13_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"53" [label="(Node ID: 14\nTopoID: 53\nL2_IFM_Buffer_from_layer_12_for_layer_14_port1)\n Buffer dim : {1,32,48,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 491520\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"54" [label="(Node ID: 14\nTopoID: 54\nL2_IFM_Buffer_from_layer_13_for_layer_14_port0)\n Buffer dim : {1,16,45,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 230400\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_8.dot b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_8.dot
new file mode 100644
index 0000000000000000000000000000000000000000..b3648a0820351475e25d09a58cc5e87e7504d1da
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_8.dot
@@ -0,0 +1,1870 @@
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+"627" [label="(Node ID: 231\nTopoID: 627\nResize_365)\n(ResizeAdf)\n(L-231)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"635" [label="(Node ID: 233\nTopoID: 635\nl2l3_233_spill)\n Buffer dim : {1,8,90,160}\n Buffer bound : {1,3,90,160}\n Buffer Size : 230400\n DataType : BF16", shape="rect", color="red"];
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+"637" [label="(Node ID: 234\nTopoID: 637\nAveragePool_347)\n(L-234)\n TG Layer : False\n IncoreChain Kernels Type : AvgPool2d", shape="ellipse"];
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+"639" [label="(Node ID: 235\nTopoID: 639\nAveragePool_348)\n(L-235)\n TG Layer : False\n IncoreChain Kernels Type : AvgPool2d", shape="ellipse"];
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+"643" [label="(Node ID: 237\nTopoID: 643\nConv_373)\n(L-237)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"645" [label="(Node ID: 237\nTopoID: 645\nl2l3_237_spill)\n Buffer dim : {1,80,23,40}\n Buffer bound : {1,80,23,40}\n Buffer Size : 147200\n DataType : BF16", shape="rect", color="red"];
+"646" [label="(Node ID: 238\nTopoID: 646\nSplit_375_Duplicated#0)\n(SliceHCWC8Adf)\n(L-238)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"655" [label="(Node ID: 241\nTopoID: 655\nConv_377)\n(L-241)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"660" [label="(Node ID: 243\nTopoID: 660\nSplit_379_Duplicated#1)\n(SliceHCWC8Adf)\n(L-243)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"670" [label="(Node ID: 246\nTopoID: 670\nSplit_379_Duplicated#0)\n(SliceHCWC8Adf)\n(L-246)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"691" [label="(Node ID: 254\nTopoID: 691\nResize_391)\n(ResizeAdf)\n(L-254)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"693" [label="(Node ID: 255\nTopoID: 693\nSlice_397)\n(SliceHCWC8Adf)\n(L-255)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"698" [label="(Node ID: 257\nTopoID: 698\nConv_399)\n(L-257)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"700" [label="(Node ID: 257\nTopoID: 700\nl2l3_257_spill)\n Buffer dim : {1,40,45,80}\n Buffer bound : {1,40,45,80}\n Buffer Size : 288000\n DataType : BF16", shape="rect", color="red"];
+"701" [label="(Node ID: 258\nTopoID: 701\nSplit_401_Duplicated#0)\n(SliceHCWC8Adf)\n(L-258)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"703" [label="(Node ID: 259\nTopoID: 703\nSplit_401_Duplicated#1)\n(SliceHCWC8Adf)\n(L-259)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"706" [label="(Node ID: 260\nTopoID: 706\nConcat_402)\n(ConcatC8Adf)\n(L-260)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"709" [label="(Node ID: 261\nTopoID: 709\nConv_403)\n(L-261)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"711" [label="(Node ID: 262\nTopoID: 711\nSigmoid_404)\n(L-262)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
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+"713" [label="(Node ID: 262\nTopoID: 713\nl2l3_262_spill)\n Buffer dim : {1,40,45,80}\n Buffer bound : {1,40,45,80}\n Buffer Size : 288000\n DataType : BF16", shape="rect", color="red"];
+"714" [label="(Node ID: 263\nTopoID: 714\nSplit_405_Duplicated#1)\n(SliceHCWC8Adf)\n(L-263)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_9.dot b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_9.dot
new file mode 100644
index 0000000000000000000000000000000000000000..e444ea4fb091038546433f74d2a0c3b30a096fa6
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/TGNodeSpilling_Dump_9.dot
@@ -0,0 +1,1876 @@
+digraph G {
+"0" [label="(START)"];
+"1" [label="(Node ID: 0\nTopoID: 1\nifm_ddr)\n Buffer dim : {1,184,320,4}\n Buffer bound : {1,180,320,4}\n Buffer Size : 471040\n DataType : BF16", shape="rect", color="red"];
+"2" [label="(Node ID: 1\nTopoID: 2\nL2_IFM_Buffer_for_input0_0_port0)\n Buffer dim : {1,184,320,4}\n Buffer bound : {1,184,320,4}\n Buffer Size : 471040\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"3" [label="(Node ID: 1\nTopoID: 3\nDiv_2)\n(L-1)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"4" [label="(Node ID: 1\nTopoID: 4\nl2_1)\n Buffer dim : {1,192,320,4}\n Buffer bound : {1,184,320,4}\n Buffer Size : 491520\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"5" [label="(Node ID: 2\nTopoID: 5\nl2l3_1_spill)\n Buffer dim : {1,184,320,4}\n Buffer bound : {1,180,320,4}\n Buffer Size : 471040\n DataType : BF16", shape="rect", color="red"];
+"6" [label="(Node ID: 2\nTopoID: 6\nSlice_7)\n(SliceHCWC8Adf)\n(L-2)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"7" [label="(Node ID: 2\nTopoID: 7\nl2l3_2_spill)\n Buffer dim : {1,184,320,3}\n Buffer bound : {1,180,320,3}\n Buffer Size : 353280\n DataType : BF16", shape="rect", color="red"];
+"8" [label="(Node ID: 2\nTopoID: 8\nl2l3_scratch_0_3_spill)\n Buffer dim : {942080}\n Buffer bound : {942080}\n Buffer Size : 942080\n DataType : INT8", shape="rect", color="red"];
+"9" [label="(Node ID: 3\nTopoID: 9\nGenerated-#0)\n(BufferPadAdf)\n(L-3)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"10" [label="(Node ID: 4\nTopoID: 10\nl2l3_3_spill)\n Buffer dim : {1,184,320,8}\n Buffer bound : {1,180,320,3}\n Buffer Size : 942080\n DataType : BF16", shape="rect", color="red"];
+"11" [label="(Node ID: 4\nTopoID: 11\nGenerated-#2)\n(Transpose4dAdf)\n(L-4)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"12" [label="(Node ID: 4\nTopoID: 12\nl2l3_4_spill)\n Buffer dim : {1,8,184,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 942080\n DataType : BF16", shape="rect", color="red"];
+"13" [label="(Node ID: 4\nTopoID: 13\nl2l3_scratch_0_5_spill)\n Buffer dim : {921600}\n Buffer bound : {921600}\n Buffer Size : 921600\n DataType : INT8", shape="rect", color="red"];
+"14" [label="(Node ID: 5\nTopoID: 14\nGenerated-#4)\n(BufferUnpadAdf)\n(L-5)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"15" [label="(Node ID: 5\nTopoID: 15\nl2l3_5_spill)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"16" [label="(Node ID: 0\nTopoID: 16\nconst_ifm_ddr_5)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"17" [label="(Node ID: 6\nTopoID: 17\nL2_CONST_IFM_Buffer_for_input5_0_port1)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"18" [label="(Node ID: 6\nTopoID: 18\nL2_IFM_Buffer_from_layer_5_for_layer_6_port0)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"19" [label="(Node ID: 6\nTopoID: 19\nSub_14)\n(L-6)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"20" [label="(Node ID: 6\nTopoID: 20\nl2_6)\n Buffer dim : {1,32,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 819200\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"21" [label="(Node ID: 6\nTopoID: 21\nl2l3_6_spill)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"22" [label="(Node ID: 0\nTopoID: 22\nconst_ifm_ddr_4)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"23" [label="(Node ID: 7\nTopoID: 23\nL2_CONST_IFM_Buffer_for_input4_0_port1)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"24" [label="(Node ID: 7\nTopoID: 24\nL2_IFM_Buffer_from_layer_6_for_layer_7_port0)\n Buffer dim : {1,8,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 204800\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"25" [label="(Node ID: 7\nTopoID: 25\nDiv_16)\n(L-7)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"26" [label="(Node ID: 7\nTopoID: 26\nl2_7)\n Buffer dim : {1,32,20,320}\n Buffer bound : {1,8,20,320}\n Buffer Size : 819200\n Tiling Factor : {1,1,9,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"27" [label="(Node ID: 7\nTopoID: 27\nl2l3_7_spill)\n Buffer dim : {1,8,180,320}\n Buffer bound : {1,3,180,320}\n Buffer Size : 921600\n DataType : BF16", shape="rect", color="red"];
+"28" [label="(Node ID: 8\nTopoID: 28\nL2_IFM_Buffer_from_layer_7_for_layer_8_port0)\n Buffer dim : {1,8,61,320}\n Buffer bound : {1,8,61,320}\n Buffer Size : 624640\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"29" [label="(Node ID: 8\nTopoID: 29\nConv_17)\n(L-8)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"30" [label="(Node ID: 8\nTopoID: 30\nl2_8)\n Buffer dim : {1,32,32,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 655360\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"31" [label="(Node ID: 8\nTopoID: 31\nl2l3_8_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"32" [label="(Node ID: 9\nTopoID: 32\nL2_IFM_Buffer_from_layer_8_for_layer_9_port0)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"33" [label="(Node ID: 9\nTopoID: 33\nAdd_19)\n(L-9)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"34" [label="(Node ID: 9\nTopoID: 34\nl2_9)\n Buffer dim : {1,32,92,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 942080\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"35" [label="(Node ID: 9\nTopoID: 35\nl2l3_9_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"36" [label="(Node ID: 10\nTopoID: 36\nL2_IFM_Buffer_from_layer_9_for_layer_10_port0)\n Buffer dim : {1,16,45,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 230400\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"37" [label="(Node ID: 10\nTopoID: 37\nClip_22)\n(L-10)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"38" [label="(Node ID: 10\nTopoID: 38\nl2_10)\n Buffer dim : {1,32,48,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 491520\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"39" [label="(Node ID: 10\nTopoID: 39\nl2l3_10_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"40" [label="(Node ID: 11\nTopoID: 40\nL2_IFM_Buffer_from_layer_10_for_layer_11_port0)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"41" [label="(Node ID: 11\nTopoID: 41\nDiv_24)\n(L-11)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"42" [label="(Node ID: 11\nTopoID: 42\nl2_11)\n Buffer dim : {1,32,92,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 942080\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"43" [label="(Node ID: 11\nTopoID: 43\nl2l3_11_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"44" [label="(Node ID: 12\nTopoID: 44\nL2_IFM_Buffer_from_layer_8_for_layer_12_port0)\n Buffer dim : {1,16,30,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 307200\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"45" [label="(Node ID: 12\nTopoID: 45\nL2_IFM_Buffer_from_layer_11_for_layer_12_port1)\n Buffer dim : {1,16,30,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 307200\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"46" [label="(Node ID: 12\nTopoID: 46\nMul_25)\n(L-12)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"47" [label="(Node ID: 12\nTopoID: 47\nl2_12)\n Buffer dim : {1,32,32,160}\n Buffer bound : {1,16,30,160}\n Buffer Size : 655360\n Tiling Factor : {1,1,3,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"48" [label="(Node ID: 12\nTopoID: 48\nl2l3_12_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"49" [label="(Node ID: 13\nTopoID: 49\nL2_IFM_Buffer_from_layer_12_for_layer_13_port0)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"50" [label="(Node ID: 13\nTopoID: 50\nConv_26)\n(L-13)\n TG Layer : False\n IncoreChain Kernels Type : DepthwiseConv2d", shape="ellipse"];
+"51" [label="(Node ID: 13\nTopoID: 51\nl2_13)\n Buffer dim : {1,32,96,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 983040\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"52" [label="(Node ID: 13\nTopoID: 52\nl2l3_13_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"53" [label="(Node ID: 14\nTopoID: 53\nL2_IFM_Buffer_from_layer_12_for_layer_14_port1)\n Buffer dim : {1,32,48,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 491520\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"54" [label="(Node ID: 14\nTopoID: 54\nL2_IFM_Buffer_from_layer_13_for_layer_14_port0)\n Buffer dim : {1,16,45,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 230400\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"55" [label="(Node ID: 14\nTopoID: 55\nConv_28)\n(L-14)\n TG Layer : False\n IncoreChain Kernels Type : Conv2dElementwiseBinary", shape="ellipse"];
+"56" [label="(Node ID: 14\nTopoID: 56\nl2_14)\n Buffer dim : {1,32,48,160}\n Buffer bound : {1,16,45,160}\n Buffer Size : 491520\n Buffer concat offset : { spill_L3_Concat_Buffer_layer_275 : {0,40,0,0}, l2l3_14_spill : {0,0,0,0} }\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"57" [label="(Node ID: 14\nTopoID: 57\nl2l3_14_spill)\n Buffer dim : {1,16,90,160}\n Buffer bound : {1,16,90,160}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"58" [label="(Node ID: 15\nTopoID: 58\nL2_IFM_Buffer_from_layer_14_for_layer_15_port0)\n Buffer dim : {1,16,18,160}\n Buffer bound : {1,16,18,160}\n Buffer Size : 184320\n Tiling Factor : {1,1,5,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"59" [label="(Node ID: 15\nTopoID: 59\nConv_30)\n(L-15)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"60" [label="(Node ID: 15\nTopoID: 60\nl2_15)\n Buffer dim : {1,64,18,160}\n Buffer bound : {1,64,18,160}\n Buffer Size : 737280\n Tiling Factor : {1,1,5,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"61" [label="(Node ID: 15\nTopoID: 61\nl2l3_15_spill)\n Buffer dim : {1,64,90,160}\n Buffer bound : {1,64,90,160}\n Buffer Size : 1843200\n DataType : BF16", shape="rect", color="red"];
+"62" [label="(Node ID: 16\nTopoID: 62\nL2_IFM_Buffer_from_layer_15_for_layer_16_port0)\n Buffer dim : {1,64,17,160}\n Buffer bound : {1,64,17,160}\n Buffer Size : 696320\n Tiling Factor : {1,1,6,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"63" [label="(Node ID: 16\nTopoID: 63\nConv_32)\n(L-16)\n TG Layer : False\n IncoreChain Kernels Type : DepthwiseConv2d", shape="ellipse"];
+"64" [label="(Node ID: 16\nTopoID: 64\nl2_16)\n Buffer dim : {1,64,8,84}\n Buffer bound : {1,64,8,80}\n Buffer Size : 172032\n Tiling Factor : {1,1,6,1}\n DataType : BF16\n DoubleBuffer : True", shape="rect"];
+"65" [label="(Node ID: 16\nTopoID: 65\nl2l3_16_spill)\n Buffer dim : {1,64,48,80}\n Buffer bound : {1,64,45,80}\n Buffer Size : 491520\n DataType : BF16", shape="rect", color="red"];
+"66" [label="(Node ID: 16\nTopoID: 66\nl2l3_scratch_0_17_spill)\n Buffer dim : {460800}\n Buffer bound : {460800}\n Buffer Size : 460800\n DataType : INT8", shape="rect", color="red"];
+"67" [label="(Node ID: 17\nTopoID: 67\nGenerated-#60)\n(BufferUnpadAdf)\n(L-17)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"68" [label="(Node ID: 17\nTopoID: 68\nl2l3_17_spill)\n Buffer dim : {1,64,45,80}\n Buffer bound : {1,64,45,80}\n Buffer Size : 460800\n DataType : BF16", shape="rect", color="red"];
+"69" [label="(Node ID: 18\nTopoID: 69\nL2_IFM_Buffer_from_layer_17_for_layer_18_port0)\n Buffer dim : {1,64,45,80}\n Buffer bound : {1,64,45,80}\n Buffer Size : 460800\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"70" [label="(Node ID: 18\nTopoID: 70\nConv_34)\n(L-18)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"71" [label="(Node ID: 18\nTopoID: 71\nl2_18)\n OFM_MEM_SHARE : 1\n Buffer dim : {1,64,48,80}\n Buffer bound : {1,24,45,80}\n Buffer Size : 491520\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"72" [label="(Node ID: 18\nTopoID: 72\nL3_OFM_Buffer_layer_TGSpilling_1818)\n Buffer dim : {1,24,45,80}\n Buffer bound : {1,24,45,80}\n Buffer Size : 172800\n DataType : BF16", shape="rect", color="red"];
+"73" [label="(Node ID: 19\nTopoID: 73\nConv_35)\n(L-19)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"74" [label="(Node ID: 19\nTopoID: 74\nl2_19)\n Buffer dim : {1,96,48,96}\n Buffer bound : {1,72,45,80}\n Buffer Size : 884736\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"75" [label="(Node ID: 19\nTopoID: 75\nl2l3_19_spill)\n Buffer dim : {1,72,45,80}\n Buffer bound : {1,72,45,80}\n Buffer Size : 518400\n DataType : BF16", shape="rect", color="red"];
+"76" [label="(Node ID: 20\nTopoID: 76\nL2_IFM_Buffer_from_layer_19_for_layer_20_port0)\n Buffer dim : {1,72,25,80}\n Buffer bound : {1,72,25,80}\n Buffer Size : 288000\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"77" [label="(Node ID: 20\nTopoID: 77\nConv_37)\n(L-20)\n TG Layer : False\n IncoreChain Kernels Type : DepthwiseConv2d", shape="ellipse"];
+"78" [label="(Node ID: 20\nTopoID: 78\nl2_20)\n Buffer dim : {1,96,24,80}\n Buffer bound : {1,72,23,80}\n Buffer Size : 368640\n Tiling Factor : {1,1,2,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
+"79" [label="(Node ID: 20\nTopoID: 79\nl2l3_20_spill)\n Buffer dim : {1,72,46,80}\n Buffer bound : {1,72,45,80}\n Buffer Size : 529920\n DataType : BF16", shape="rect", color="red"];
+"80" [label="(Node ID: 20\nTopoID: 80\nl2l3_scratch_0_21_spill)\n Buffer dim : {518400}\n Buffer bound : {518400}\n Buffer Size : 518400\n DataType : INT8", shape="rect", color="red"];
+"81" [label="(Node ID: 21\nTopoID: 81\nGenerated-#62)\n(BufferUnpadAdf)\n(L-21)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"82" [label="(Node ID: 21\nTopoID: 82\nl2l3_21_spill)\n Buffer dim : {1,72,45,80}\n Buffer bound : {1,72,45,80}\n Buffer Size : 518400\n DataType : BF16", shape="rect", color="red"];
+"83" [label="(Node ID: 22\nTopoID: 83\nL2_OFM_Buffer_layer_TGSpilling_1818)\n OFM_MEM_SHARE : 1\n Buffer dim : {1,64,48,80}\n Buffer bound : {1,24,45,80}\n Buffer Size : 491520\n Tiling Factor : {1,1,1,1}\n DataType : BF16\n DoubleBuffer : False", shape="rect"];
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+"726" [label="(Node ID: 266\nTopoID: 726\nSplit_405_Duplicated#0)\n(SliceHCWC8Adf)\n(L-266)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"767" [label="(Node ID: 281\nTopoID: 767\nSigmoid_424)\n(L-281)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
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+"770" [label="(Node ID: 282\nTopoID: 770\nSplit_425_Duplicated#1)\n(SliceHCWC8Adf)\n(L-282)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/buffer_info.json b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/buffer_info.json
new file mode 100644
index 0000000000000000000000000000000000000000..c4cbe536d80c45179140093a512b088ef936ee1a
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/buffer_info.json
@@ -0,0 +1,40268 @@
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+        "compute_graph.flexml_layers[236].compute_node[1][2].out[0]",
+        "compute_graph.flexml_layers[236].compute_node[1][3].out[0]",
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+        "compute_graph.flexml_layers[236].compute_node[2][1].out[0]",
+        "compute_graph.flexml_layers[236].compute_node[2][2].out[0]",
+        "compute_graph.flexml_layers[236].compute_node[2][3].out[0]",
+        "compute_graph.flexml_layers[236].compute_node[3][0].out[0]",
+        "compute_graph.flexml_layers[236].compute_node[3][1].out[0]",
+        "compute_graph.flexml_layers[236].compute_node[3][2].out[0]",
+        "compute_graph.flexml_layers[236].compute_node[3][3].out[0]"
+      ],
+      "l1_ping": [
+        "0xa600",
+        1600
+      ],
+      "l1_pong": [
+        "0xcd80",
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+          0,
+          0,
+          204800,
+          51200
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+      ],
+      "l2_buffer_names": [
+        "compute_graph.L2_OFM_Buffer_layer_302"
+      ],
+      "l3": {
+        "ofm_ddr_5": {
+          "size": 460800
+        }
+      },
+      "l3_buffer_names": [
+        "compute_graph.ofm_ddr_5"
+      ]
+    },
+    "super_iter": 9
+  }
+}
diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/dag_AfterL3concat_fanout.dot b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/dag_AfterL3concat_fanout.dot
new file mode 100644
index 0000000000000000000000000000000000000000..d770809209fc242ab4c898fe6caddfe453a26d3c
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/dag_AfterL3concat_fanout.dot
@@ -0,0 +1,2607 @@
+digraph G {
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/dag_After_L2flushout.dot b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/dag_After_L2flushout.dot
new file mode 100644
index 0000000000000000000000000000000000000000..a80233c645cddbdf919ef8ca5c81f2b36ad9254a
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/dag_After_L2flushout.dot
@@ -0,0 +1,1888 @@
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+"645" [label="(Node ID: 237\nTopoID: 645\nConv_373)\n(L-237)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"695" [label="(Node ID: 254\nTopoID: 695\nResize_391)\n(ResizeAdf)\n(L-254)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"713" [label="(Node ID: 261\nTopoID: 713\nConv_403)\n(L-261)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
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+"718" [label="(Node ID: 263\nTopoID: 718\nSplit_405_Duplicated#1)\n(SliceHCWC8Adf)\n(L-263)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"726" [label="(Node ID: 265\nTopoID: 726\nMul_412)\n(L-265)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"728" [label="(Node ID: 265\nTopoID: 728\nL3_OFM_Buffer_layer_TGSpilling_265265)\n Buffer dim : {1,24,45,80}\n Buffer bound : {1,20,45,80}\n Buffer Size : 172800\n DataType : BF16", shape="rect", color="red"];
+"729" [label="(Node ID: 266\nTopoID: 729\nSplit_405_Duplicated#0)\n(SliceHCWC8Adf)\n(L-266)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/dag_init.dot b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/dag_init.dot
new file mode 100644
index 0000000000000000000000000000000000000000..1cb059cdb2ddf4a0bd23a7645a60f40267e78fe8
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/dag_init.dot
@@ -0,0 +1,695 @@
+digraph G {
+"0" [label="(START)"];
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+"4" [label="(Node ID: 4\nTopoID: 4\nGenerated-#2)\n(Transpose4dAdf)\n(L-4)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"50" [label="(Node ID: 50\nTopoID: 50\nGenerated-#20)\n(L-50)\n TG Layer : False\n IncoreChain Kernels Type : Reduce", shape="ellipse"];
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+"52" [label="(Node ID: 52\nTopoID: 52\nConv_83)\n(L-52)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"53" [label="(Node ID: 53\nTopoID: 53\nAdd_85)\n(L-53)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
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+"55" [label="(Node ID: 55\nTopoID: 55\nDiv_90)\n(L-55)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
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+"63" [label="(Node ID: 63\nTopoID: 63\nMul_102)\n(L-63)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"64" [label="(Node ID: 64\nTopoID: 64\nGenerated-#64)\n(BufferUnpadAdf)\n(L-64)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
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+"67" [label="(Node ID: 67\nTopoID: 67\nClip_108)\n(L-67)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
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+"72" [label="(Node ID: 72\nTopoID: 72\nAdd_115)\n(L-72)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"73" [label="(Node ID: 73\nTopoID: 73\nClip_118)\n(L-73)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"74" [label="(Node ID: 74\nTopoID: 74\nDiv_120)\n(L-74)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"75" [label="(Node ID: 75\nTopoID: 75\nMul_121)\n(L-75)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"77" [label="(Node ID: 77\nTopoID: 77\nAdd_124)\n(L-77)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
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+"86" [label="(Node ID: 86\nTopoID: 86\nMul_141)\n(L-86)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"95" [label="(Node ID: 95\nTopoID: 95\nClip_158)\n(L-95)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
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+"105" [label="(Node ID: 105\nTopoID: 105\nAdd_175)\n(L-105)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
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+"107" [label="(Node ID: 107\nTopoID: 107\nDiv_180)\n(L-107)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"108" [label="(Node ID: 108\nTopoID: 108\nMul_181)\n(L-108)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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+"135" [label="(Node ID: 135\nTopoID: 135\nGenerated-#32)\n(L-135)\n TG Layer : False\n IncoreChain Kernels Type : Reduce", shape="ellipse"];
+"136" [label="(Node ID: 136\nTopoID: 136\nConv_223)\n(L-136)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"137" [label="(Node ID: 137\nTopoID: 137\nConv_225)\n(L-137)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"138" [label="(Node ID: 138\nTopoID: 138\nAdd_227)\n(L-138)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"139" [label="(Node ID: 139\nTopoID: 139\nClip_230)\n(L-139)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"140" [label="(Node ID: 140\nTopoID: 140\nDiv_232)\n(L-140)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"141" [label="(Node ID: 141\nTopoID: 141\nGenerated-#34)\n(TileAdf)\n(L-141)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"142" [label="(Node ID: 142\nTopoID: 142\nMul_233)\n(L-142)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"143" [label="(Node ID: 143\nTopoID: 143\nConv_234)\n(L-143)\n OFM_MEM_SHARE : 1\n TG Layer : False\n IncoreChain Kernels Type : Conv2dElementwiseBinary", shape="ellipse"];
+"144" [label="(Node ID: 144\nTopoID: 144\nConv_236)\n(L-144)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"145" [label="(Node ID: 145\nTopoID: 145\nAdd_238)\n(L-145)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"146" [label="(Node ID: 146\nTopoID: 146\nClip_241)\n(L-146)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"147" [label="(Node ID: 147\nTopoID: 147\nDiv_243)\n(L-147)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"148" [label="(Node ID: 148\nTopoID: 148\nMul_244)\n(L-148)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"149" [label="(Node ID: 149\nTopoID: 149\nConv_245)\n(L-149)\n TG Layer : False\n IncoreChain Kernels Type : DepthwiseConv2d", shape="ellipse"];
+"150" [label="(Node ID: 150\nTopoID: 150\nAdd_247)\n(L-150)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"151" [label="(Node ID: 151\nTopoID: 151\nClip_250)\n(L-151)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"152" [label="(Node ID: 152\nTopoID: 152\nDiv_252)\n(L-152)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"153" [label="(Node ID: 153\nTopoID: 153\nMul_253)\n(L-153)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"154" [label="(Node ID: 154\nTopoID: 154\nGenerated-#36)\n(Transpose4dAdf)\n(L-154)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"155" [label="(Node ID: 155\nTopoID: 155\nGenerated-#38)\n(L-155)\n TG Layer : False\n IncoreChain Kernels Type : Reduce", shape="ellipse"];
+"156" [label="(Node ID: 156\nTopoID: 156\nConv_255)\n(L-156)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"157" [label="(Node ID: 157\nTopoID: 157\nConv_257)\n(L-157)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"158" [label="(Node ID: 158\nTopoID: 158\nAdd_259)\n(L-158)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"159" [label="(Node ID: 159\nTopoID: 159\nClip_262)\n(L-159)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"160" [label="(Node ID: 160\nTopoID: 160\nDiv_264)\n(L-160)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"161" [label="(Node ID: 161\nTopoID: 161\nGenerated-#40)\n(TileAdf)\n(L-161)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"162" [label="(Node ID: 162\nTopoID: 162\nMul_265)\n(L-162)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"163" [label="(Node ID: 163\nTopoID: 163\nConv_266)\n(L-163)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"164" [label="(Node ID: 164\nTopoID: 164\nConv_267)\n(L-164)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"165" [label="(Node ID: 165\nTopoID: 165\nAdd_269)\n(L-165)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"166" [label="(Node ID: 166\nTopoID: 166\nClip_272)\n(L-166)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"167" [label="(Node ID: 167\nTopoID: 167\nDiv_274)\n(L-167)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"168" [label="(Node ID: 168\nTopoID: 168\nMul_275)\n(L-168)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"169" [label="(Node ID: 169\nTopoID: 169\nConv_276)\n(L-169)\n TG Layer : False\n IncoreChain Kernels Type : DepthwiseConv2d", shape="ellipse"];
+"170" [label="(Node ID: 170\nTopoID: 170\nAdd_278)\n(L-170)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"171" [label="(Node ID: 171\nTopoID: 171\nClip_281)\n(L-171)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"172" [label="(Node ID: 172\nTopoID: 172\nDiv_283)\n(L-172)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"173" [label="(Node ID: 173\nTopoID: 173\nMul_284)\n(L-173)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"174" [label="(Node ID: 174\nTopoID: 174\nGenerated-#42)\n(Transpose4dAdf)\n(L-174)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"175" [label="(Node ID: 175\nTopoID: 175\nGenerated-#44)\n(L-175)\n TG Layer : False\n IncoreChain Kernels Type : Reduce", shape="ellipse"];
+"176" [label="(Node ID: 176\nTopoID: 176\nConv_286)\n(L-176)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"177" [label="(Node ID: 177\nTopoID: 177\nConv_288)\n(L-177)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"178" [label="(Node ID: 178\nTopoID: 178\nAdd_290)\n(L-178)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"179" [label="(Node ID: 179\nTopoID: 179\nClip_293)\n(L-179)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"180" [label="(Node ID: 180\nTopoID: 180\nDiv_295)\n(L-180)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"181" [label="(Node ID: 181\nTopoID: 181\nGenerated-#46)\n(TileAdf)\n(L-181)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"182" [label="(Node ID: 182\nTopoID: 182\nMul_296)\n(L-182)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"183" [label="(Node ID: 183\nTopoID: 183\nConv_297)\n(L-183)\n OFM_MEM_SHARE : 1\n TG Layer : False\n IncoreChain Kernels Type : Conv2dElementwiseBinary", shape="ellipse"];
+"184" [label="(Node ID: 184\nTopoID: 184\nConv_299)\n(L-184)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"185" [label="(Node ID: 185\nTopoID: 185\nAdd_301)\n(L-185)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"186" [label="(Node ID: 186\nTopoID: 186\nClip_304)\n(L-186)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"187" [label="(Node ID: 187\nTopoID: 187\nDiv_306)\n(L-187)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"188" [label="(Node ID: 188\nTopoID: 188\nMul_307)\n(L-188)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"189" [label="(Node ID: 189\nTopoID: 189\nConv_308)\n(L-189)\n TG Layer : False\n IncoreChain Kernels Type : DepthwiseConv2d", shape="ellipse"];
+"190" [label="(Node ID: 190\nTopoID: 190\nAdd_310)\n(L-190)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"191" [label="(Node ID: 191\nTopoID: 191\nClip_313)\n(L-191)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"192" [label="(Node ID: 192\nTopoID: 192\nDiv_315)\n(L-192)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"193" [label="(Node ID: 193\nTopoID: 193\nMul_316)\n(L-193)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"194" [label="(Node ID: 194\nTopoID: 194\nGenerated-#48)\n(Transpose4dAdf)\n(L-194)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"195" [label="(Node ID: 195\nTopoID: 195\nGenerated-#50)\n(L-195)\n TG Layer : False\n IncoreChain Kernels Type : Reduce", shape="ellipse"];
+"196" [label="(Node ID: 196\nTopoID: 196\nConv_318)\n(L-196)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"197" [label="(Node ID: 197\nTopoID: 197\nConv_320)\n(L-197)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"198" [label="(Node ID: 198\nTopoID: 198\nAdd_322)\n(L-198)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"199" [label="(Node ID: 199\nTopoID: 199\nClip_325)\n(L-199)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"200" [label="(Node ID: 200\nTopoID: 200\nDiv_327)\n(L-200)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"201" [label="(Node ID: 201\nTopoID: 201\nGenerated-#52)\n(TileAdf)\n(L-201)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"202" [label="(Node ID: 202\nTopoID: 202\nMul_328)\n(L-202)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"203" [label="(Node ID: 203\nTopoID: 203\nConv_329)\n(L-203)\n OFM_MEM_SHARE : 1\n TG Layer : False\n IncoreChain Kernels Type : Conv2dElementwiseBinary", shape="ellipse"];
+"204" [label="(Node ID: 204\nTopoID: 204\nConv_331)\n(L-204)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"205" [label="(Node ID: 205\nTopoID: 205\nAdd_333)\n(L-205)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"206" [label="(Node ID: 206\nTopoID: 206\nClip_336)\n(L-206)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"207" [label="(Node ID: 207\nTopoID: 207\nDiv_338)\n(L-207)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"208" [label="(Node ID: 208\nTopoID: 208\nMul_339)\n(L-208)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"209" [label="(Node ID: 209\nTopoID: 209\nGenerated-#54)\n(Transpose4dAdf)\n(L-209)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"210" [label="(Node ID: 210\nTopoID: 210\nGenerated-#56)\n(L-210)\n TG Layer : False\n IncoreChain Kernels Type : Reduce", shape="ellipse"];
+"211" [label="(Node ID: 211\nTopoID: 211\nConv_343)\n(L-211)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"212" [label="(Node ID: 212\nTopoID: 212\nSigmoid_344)\n(L-212)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"213" [label="(Node ID: 213\nTopoID: 213\nGenerated-#58)\n(TileAdf)\n(L-213)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"214" [label="(Node ID: 214\nTopoID: 214\nConv_340)\n(L-214)\n OFM_MEM_SHARE : 1\n TG Layer : False\n IncoreChain Kernels Type : Conv2dElementwiseBinary", shape="ellipse"];
+"215" [label="(Node ID: 215\nTopoID: 215\nSplit_349_Duplicated#0)\n(SliceHCWC8Adf)\n(L-215)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"216" [label="(Node ID: 216\nTopoID: 216\nSplit_349_Duplicated#1)\n(SliceHCWC8Adf)\n(L-216)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"217" [label="(Node ID: 217\nTopoID: 217\nConcat_350)\n(L-217)\n TG Layer : False\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"218" [label="(Node ID: 218\nTopoID: 218\nConv_351)\n(L-218)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"219" [label="(Node ID: 219\nTopoID: 219\nSigmoid_352)\n(L-219)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"220" [label="(Node ID: 220\nTopoID: 220\nSplit_353_Duplicated#1)\n(SliceHCWC8Adf)\n(L-220)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"221" [label="(Node ID: 221\nTopoID: 221\nSub_359)\n(L-221)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"222" [label="(Node ID: 222\nTopoID: 222\nMul_360)\n(L-222)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"223" [label="(Node ID: 223\nTopoID: 223\nSplit_353_Duplicated#0)\n(SliceHCWC8Adf)\n(L-223)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"224" [label="(Node ID: 224\nTopoID: 224\nMul_354)\n(L-224)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"225" [label="(Node ID: 225\nTopoID: 225\nConcat_355)\n(L-225)\n TG Layer : False\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"226" [label="(Node ID: 226\nTopoID: 226\nConv_356)\n(L-226)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"227" [label="(Node ID: 227\nTopoID: 227\nTanh_357)\n(L-227)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"228" [label="(Node ID: 228\nTopoID: 228\nMul_361)\n(L-228)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"229" [label="(Node ID: 229\nTopoID: 229\nAdd_362)\n(L-229)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"230" [label="(Node ID: 230\nTopoID: 230\nConcat_363)\n(L-230)\n TG Layer : False\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"231" [label="(Node ID: 231\nTopoID: 231\nResize_365)\n(ResizeAdf)\n(L-231)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"232" [label="(Node ID: 232\nTopoID: 232\nSlice_371)\n(SliceHCWC8Adf)\n(L-232)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"233" [label="(Node ID: 233\nTopoID: 233\nAveragePool_346)\n(L-233)\n TG Layer : False\n IncoreChain Kernels Type : AvgPool2d", shape="ellipse"];
+"234" [label="(Node ID: 234\nTopoID: 234\nAveragePool_347)\n(L-234)\n TG Layer : False\n IncoreChain Kernels Type : AvgPool2d", shape="ellipse"];
+"235" [label="(Node ID: 235\nTopoID: 235\nAveragePool_348)\n(L-235)\n TG Layer : False\n IncoreChain Kernels Type : AvgPool2d", shape="ellipse"];
+"236" [label="(Node ID: 236\nTopoID: 236\nConcat_372)\n(L-236)\n TG Layer : False\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"237" [label="(Node ID: 237\nTopoID: 237\nConv_373)\n(L-237)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"238" [label="(Node ID: 238\nTopoID: 238\nSplit_375_Duplicated#0)\n(SliceHCWC8Adf)\n(L-238)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"239" [label="(Node ID: 239\nTopoID: 239\nSplit_375_Duplicated#1)\n(SliceHCWC8Adf)\n(L-239)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"240" [label="(Node ID: 240\nTopoID: 240\nConcat_376)\n(L-240)\n TG Layer : False\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"241" [label="(Node ID: 241\nTopoID: 241\nConv_377)\n(L-241)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"242" [label="(Node ID: 242\nTopoID: 242\nSigmoid_378)\n(L-242)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"243" [label="(Node ID: 243\nTopoID: 243\nSplit_379_Duplicated#1)\n(SliceHCWC8Adf)\n(L-243)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"244" [label="(Node ID: 244\nTopoID: 244\nSub_385)\n(L-244)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"245" [label="(Node ID: 245\nTopoID: 245\nMul_386)\n(L-245)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"246" [label="(Node ID: 246\nTopoID: 246\nSplit_379_Duplicated#0)\n(SliceHCWC8Adf)\n(L-246)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"247" [label="(Node ID: 247\nTopoID: 247\nMul_380)\n(L-247)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"248" [label="(Node ID: 248\nTopoID: 248\nConcat_381)\n(L-248)\n TG Layer : False\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"249" [label="(Node ID: 249\nTopoID: 249\nConv_382)\n(L-249)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"250" [label="(Node ID: 250\nTopoID: 250\nTanh_383)\n(L-250)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"251" [label="(Node ID: 251\nTopoID: 251\nMul_387)\n(L-251)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"252" [label="(Node ID: 252\nTopoID: 252\nAdd_388)\n(L-252)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"253" [label="(Node ID: 253\nTopoID: 253\nConcat_389)\n(L-253)\n TG Layer : False\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"254" [label="(Node ID: 254\nTopoID: 254\nResize_391)\n(ResizeAdf)\n(L-254)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"255" [label="(Node ID: 255\nTopoID: 255\nSlice_397)\n(SliceHCWC8Adf)\n(L-255)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"256" [label="(Node ID: 256\nTopoID: 256\nConcat_398)\n(L-256)\n TG Layer : False\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"257" [label="(Node ID: 257\nTopoID: 257\nConv_399)\n(L-257)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"258" [label="(Node ID: 258\nTopoID: 258\nSplit_401_Duplicated#0)\n(SliceHCWC8Adf)\n(L-258)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"259" [label="(Node ID: 259\nTopoID: 259\nSplit_401_Duplicated#1)\n(SliceHCWC8Adf)\n(L-259)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"260" [label="(Node ID: 260\nTopoID: 260\nConcat_402)\n(ConcatC8Adf)\n(L-260)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"261" [label="(Node ID: 261\nTopoID: 261\nConv_403)\n(L-261)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"262" [label="(Node ID: 262\nTopoID: 262\nSigmoid_404)\n(L-262)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"263" [label="(Node ID: 263\nTopoID: 263\nSplit_405_Duplicated#1)\n(SliceHCWC8Adf)\n(L-263)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"264" [label="(Node ID: 264\nTopoID: 264\nSub_411)\n(L-264)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"265" [label="(Node ID: 265\nTopoID: 265\nMul_412)\n(L-265)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"266" [label="(Node ID: 266\nTopoID: 266\nSplit_405_Duplicated#0)\n(SliceHCWC8Adf)\n(L-266)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"267" [label="(Node ID: 267\nTopoID: 267\nMul_406)\n(L-267)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
+"268" [label="(Node ID: 268\nTopoID: 268\nConcat_407)\n(ConcatC8Adf)\n(L-268)\n TG Layer : True\n IncoreChain Kernels Type : Invalid", shape="ellipse"];
+"269" [label="(Node ID: 269\nTopoID: 269\nConv_408)\n(L-269)\n TG Layer : False\n IncoreChain Kernels Type : Conv2d", shape="ellipse"];
+"270" [label="(Node ID: 270\nTopoID: 270\nTanh_409)\n(L-270)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseUnary", shape="ellipse"];
+"271" [label="(Node ID: 271\nTopoID: 271\nMul_413)\n(L-271)\n TG Layer : False\n IncoreChain Kernels Type : ElementwiseBinary", shape="ellipse"];
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/dump_module_after_l3_extend_fixup.mlir b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/dump_module_after_l3_extend_fixup.mlir
new file mode 100644
index 0000000000000000000000000000000000000000..d51caad3174475bc8de91841f946be66bd990dc1
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/dump_module_after_l3_extend_fixup.mlir
@@ -0,0 +1,32556 @@
+#loc = loc(unknown)
+module attributes {
+  llvm.data_layout = "e-m:e-p270:32:32-p271:32:32-p272:64:64-i64:64-i128:128-f80:128-n8:16:32:64-S128",
+  llvm.target_triple = "x86_64-unknown-linux-gnu",
+  "onnx-mlir.symbol-postfix" = "onnxmodel.onnx.mlir",
+  vaimlconf.device = "stx",
+  vaimlconf.device_models = "${vaimlconf.install_dir}/data/deviceModels",
+  vaimlconf.install_dir = "/usr/local/lib/python3.10/dist-packages/flexml/flexml_extras",
+  vaimlconf.library_metadata = ["${vaimlconf.install_dir}/data/libraryMetadata/L1", "${vaimlconf.install_dir}/data/libraryMetadata/L2", "${vaimlconf.install_dir}/../../vitis_mllib/L1/metadata", "${vaimlconf.install_dir}/../../vitis_mllib/L2/metadata", "${vaimlconf.install_dir}/share/microkernel-tiling/tiling-recipe-specs"],
+  vaimlconf.single_core_compiler = "chess"} {
+  func.func private @forward(%arg0: tensor<1x180x320x4xbf16> loc(unknown), %arg1: tensor<1x16x90x160xbf16> loc(unknown), %arg2: tensor<1x20x45x80xbf16> loc(unknown), %arg3: tensor<1x40x23x40xbf16> loc(unknown), %arg4: tensor<1x64x12x20xbf16> loc(unknown)) -> (tensor<1x16x90x160xbf16>, tensor<1x20x45x80xbf16>, tensor<1x40x23x40xbf16>, tensor<1x64x12x20xbf16>, tensor<1x3x180x320xbf16>, tensor<1x1x180x320xbf16>) attributes {
+    max_heap_size = 2240 : ui32,
+    max_stack_size = 2368 : ui32,
+    stack_heap_start_address = 45696 : ui32,
+    total_stack_heap_region_size = 6912 : ui32} {
+    %0 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_443/biases"} -> tensor<4xbf16> loc(#loc)
+    %1 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_443/weights"} -> tensor<4x16x1x1xbf16> loc(#loc)
+    %2 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_441/biases"} -> tensor<16xbf16> loc(#loc)
+    %3 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_441/weights"} -> tensor<16x16x3x3xbf16> loc(#loc)
+    %4 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_439/biases"} -> tensor<16xbf16> loc(#loc)
+    %5 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_439/weights"} -> tensor<16x35x3x3xbf16> loc(#loc)
+    %6 = xten_nn.load_external_const {file = "constants.h5", key = "Sub_431/Constant_0_0"} -> tensor<1x16x90x160xbf16> loc(#loc2)
+    %7 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_428/biases"} -> tensor<16xbf16> loc(#loc)
+    %8 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_428/weights"} -> tensor<16x32x3x3xbf16> loc(#loc)
+    %9 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_423/biases"} -> tensor<32xbf16> loc(#loc)
+    %10 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_423/weights"} -> tensor<32x32x3x3xbf16> loc(#loc)
+    %11 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_419/biases"} -> tensor<32xbf16> loc(#loc)
+    %12 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_419/weights"} -> tensor<32x59x3x3xbf16> loc(#loc)
+    %13 = xten_nn.load_external_const {file = "constants.h5", key = "Sub_411/Constant_0_0"} -> tensor<1x20x45x80xbf16> loc(#loc3)
+    %14 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_408/biases"} -> tensor<20xbf16> loc(#loc)
+    %15 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_408/weights"} -> tensor<20x40x3x3xbf16> loc(#loc)
+    %16 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_403/biases"} -> tensor<40xbf16> loc(#loc)
+    %17 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_403/weights"} -> tensor<40x40x3x3xbf16> loc(#loc)
+    %18 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_399/biases"} -> tensor<40xbf16> loc(#loc)
+    %19 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_399/weights"} -> tensor<40x107x3x3xbf16> loc(#loc)
+    %20 = xten_nn.load_external_const {file = "constants.h5", key = "Sub_385/Constant_0_0"} -> tensor<1x40x23x40xbf16> loc(#loc4)
+    %21 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_382/biases"} -> tensor<40xbf16> loc(#loc)
+    %22 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_382/weights"} -> tensor<40x80x3x3xbf16> loc(#loc)
+    %23 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_377/biases"} -> tensor<80xbf16> loc(#loc)
+    %24 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_377/weights"} -> tensor<80x80x3x3xbf16> loc(#loc)
+    %25 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_373/biases"} -> tensor<80xbf16> loc(#loc)
+    %26 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_373/weights"} -> tensor<80x171x3x3xbf16> loc(#loc)
+    %27 = xten_nn.load_external_const {file = "constants.h5", key = "Sub_359/Constant_0_0"} -> tensor<1x64x12x20xbf16> loc(#loc5)
+    %28 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_356/biases"} -> tensor<64xbf16> loc(#loc)
+    %29 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_356/weights"} -> tensor<64x128x3x3xbf16> loc(#loc)
+    %30 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_351/biases"} -> tensor<128xbf16> loc(#loc)
+    %31 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_351/weights"} -> tensor<128x128x3x3xbf16> loc(#loc)
+    %32 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_340/biases"} -> tensor<128xbf16> loc(#loc)
+    %33 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_340/weights"} -> tensor<128x960x1x1xbf16> loc(#loc)
+    %34 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_343/biases"} -> tensor<128xbf16> loc(#loc)
+    %35 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_343/weights"} -> tensor<128x960x1x1xbf16> loc(#loc)
+    %36 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_331/biases"} -> tensor<960xbf16> loc(#loc)
+    %37 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_331/weights"} -> tensor<960x160x1x1xbf16> loc(#loc)
+    %38 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_329/biases"} -> tensor<160xbf16> loc(#loc)
+    %39 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_329/weights"} -> tensor<160x960x1x1xbf16> loc(#loc)
+    %40 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_320/biases"} -> tensor<960xbf16> loc(#loc)
+    %41 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_320/weights"} -> tensor<960x240x1x1xbf16> loc(#loc)
+    %42 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_318/biases"} -> tensor<240xbf16> loc(#loc)
+    %43 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_318/weights"} -> tensor<240x960x1x1xbf16> loc(#loc)
+    %44 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_308/biases"} -> tensor<960xbf16> loc(#loc)
+    %45 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_308/weights"} -> tensor<960x1x9x9xbf16> loc(#loc)
+    %46 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_299/biases"} -> tensor<960xbf16> loc(#loc)
+    %47 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_299/weights"} -> tensor<960x160x1x1xbf16> loc(#loc)
+    %48 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_297/biases"} -> tensor<160xbf16> loc(#loc)
+    %49 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_297/weights"} -> tensor<160x960x1x1xbf16> loc(#loc)
+    %50 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_288/biases"} -> tensor<960xbf16> loc(#loc)
+    %51 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_288/weights"} -> tensor<960x240x1x1xbf16> loc(#loc)
+    %52 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_286/biases"} -> tensor<240xbf16> loc(#loc)
+    %53 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_286/weights"} -> tensor<240x960x1x1xbf16> loc(#loc)
+    %54 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_276/biases"} -> tensor<960xbf16> loc(#loc)
+    %55 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_276/weights"} -> tensor<960x1x9x9xbf16> loc(#loc)
+    %56 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_267/biases"} -> tensor<960xbf16> loc(#loc)
+    %57 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_267/weights"} -> tensor<960x160x1x1xbf16> loc(#loc)
+    %58 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_266/biases"} -> tensor<160xbf16> loc(#loc)
+    %59 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_266/weights"} -> tensor<160x672x1x1xbf16> loc(#loc)
+    %60 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_257/biases"} -> tensor<672xbf16> loc(#loc)
+    %61 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_257/weights"} -> tensor<672x168x1x1xbf16> loc(#loc)
+    %62 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_255/biases"} -> tensor<168xbf16> loc(#loc)
+    %63 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_255/weights"} -> tensor<168x672x1x1xbf16> loc(#loc)
+    %64 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_245/biases"} -> tensor<672xbf16> loc(#loc)
+    %65 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_245/weights"} -> tensor<672x1x9x9xbf16> loc(#loc)
+    %66 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_236/biases"} -> tensor<672xbf16> loc(#loc)
+    %67 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_236/weights"} -> tensor<672x112x1x1xbf16> loc(#loc)
+    %68 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_234/biases"} -> tensor<112xbf16> loc(#loc)
+    %69 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_234/weights"} -> tensor<112x672x1x1xbf16> loc(#loc)
+    %70 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_225/biases"} -> tensor<672xbf16> loc(#loc)
+    %71 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_225/weights"} -> tensor<672x168x1x1xbf16> loc(#loc)
+    %72 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_223/biases"} -> tensor<168xbf16> loc(#loc)
+    %73 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_223/weights"} -> tensor<168x672x1x1xbf16> loc(#loc)
+    %74 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_213/biases"} -> tensor<672xbf16> loc(#loc)
+    %75 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_213/weights"} -> tensor<672x1x3x3xbf16> loc(#loc)
+    %76 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_204/biases"} -> tensor<672xbf16> loc(#loc)
+    %77 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_204/weights"} -> tensor<672x112x1x1xbf16> loc(#loc)
+    %78 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_203/biases"} -> tensor<112xbf16> loc(#loc)
+    %79 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_203/weights"} -> tensor<112x480x1x1xbf16> loc(#loc)
+    %80 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_194/biases"} -> tensor<480xbf16> loc(#loc)
+    %81 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_194/weights"} -> tensor<480x120x1x1xbf16> loc(#loc)
+    %82 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_192/biases"} -> tensor<120xbf16> loc(#loc)
+    %83 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_192/weights"} -> tensor<120x480x1x1xbf16> loc(#loc)
+    %84 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_182/biases"} -> tensor<480xbf16> loc(#loc)
+    %85 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_182/weights"} -> tensor<480x1x3x3xbf16> loc(#loc)
+    %86 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_173/biases"} -> tensor<480xbf16> loc(#loc)
+    %87 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_173/weights"} -> tensor<480x80x1x1xbf16> loc(#loc)
+    %88 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_171/biases"} -> tensor<80xbf16> loc(#loc)
+    %89 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_171/weights"} -> tensor<80x184x1x1xbf16> loc(#loc)
+    %90 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_162/biases"} -> tensor<184xbf16> loc(#loc)
+    %91 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_162/weights"} -> tensor<184x1x3x3xbf16> loc(#loc)
+    %92 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_153/biases"} -> tensor<184xbf16> loc(#loc)
+    %93 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_153/weights"} -> tensor<184x80x1x1xbf16> loc(#loc)
+    %94 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_151/biases"} -> tensor<80xbf16> loc(#loc)
+    %95 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_151/weights"} -> tensor<80x184x1x1xbf16> loc(#loc)
+    %96 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_142/biases"} -> tensor<184xbf16> loc(#loc)
+    %97 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_142/weights"} -> tensor<184x1x3x3xbf16> loc(#loc)
+    %98 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_133/biases"} -> tensor<184xbf16> loc(#loc)
+    %99 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_133/weights"} -> tensor<184x80x1x1xbf16> loc(#loc)
+    %100 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_131/biases"} -> tensor<80xbf16> loc(#loc)
+    %101 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_131/weights"} -> tensor<80x200x1x1xbf16> loc(#loc)
+    %102 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_122/biases"} -> tensor<200xbf16> loc(#loc)
+    %103 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_122/weights"} -> tensor<200x1x3x3xbf16> loc(#loc)
+    %104 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_113/biases"} -> tensor<200xbf16> loc(#loc)
+    %105 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_113/weights"} -> tensor<200x80x1x1xbf16> loc(#loc)
+    %106 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_112/biases"} -> tensor<80xbf16> loc(#loc)
+    %107 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_112/weights"} -> tensor<80x240x1x1xbf16> loc(#loc)
+    %108 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_103/biases"} -> tensor<240xbf16> loc(#loc)
+    %109 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_103/weights"} -> tensor<240x1x3x3xbf16> loc(#loc)
+    %110 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_94/biases"} -> tensor<240xbf16> loc(#loc)
+    %111 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_94/weights"} -> tensor<240x40x1x1xbf16> loc(#loc)
+    %112 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_92/biases"} -> tensor<40xbf16> loc(#loc)
+    %113 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_92/weights"} -> tensor<40x120x1x1xbf16> loc(#loc)
+    %114 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_83/biases"} -> tensor<120xbf16> loc(#loc)
+    %115 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_83/weights"} -> tensor<120x32x1x1xbf16> loc(#loc)
+    %116 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_81/biases"} -> tensor<32xbf16> loc(#loc)
+    %117 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_81/weights"} -> tensor<32x120x1x1xbf16> loc(#loc)
+    %118 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_78/biases"} -> tensor<120xbf16> loc(#loc)
+    %119 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_78/weights"} -> tensor<120x1x5x5xbf16> loc(#loc)
+    %120 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_76/biases"} -> tensor<120xbf16> loc(#loc)
+    %121 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_76/weights"} -> tensor<120x40x1x1xbf16> loc(#loc)
+    %122 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_74/biases"} -> tensor<40xbf16> loc(#loc)
+    %123 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_74/weights"} -> tensor<40x120x1x1xbf16> loc(#loc)
+    %124 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_65/biases"} -> tensor<120xbf16> loc(#loc)
+    %125 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_65/weights"} -> tensor<120x32x1x1xbf16> loc(#loc)
+    %126 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_63/biases"} -> tensor<32xbf16> loc(#loc)
+    %127 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_63/weights"} -> tensor<32x120x1x1xbf16> loc(#loc)
+    %128 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_60/biases"} -> tensor<120xbf16> loc(#loc)
+    %129 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_60/weights"} -> tensor<120x1x5x5xbf16> loc(#loc)
+    %130 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_58/biases"} -> tensor<120xbf16> loc(#loc)
+    %131 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_58/weights"} -> tensor<120x40x1x1xbf16> loc(#loc)
+    %132 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_57/biases"} -> tensor<40xbf16> loc(#loc)
+    %133 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_57/weights"} -> tensor<40x72x1x1xbf16> loc(#loc)
+    %134 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_48/biases"} -> tensor<72xbf16> loc(#loc)
+    %135 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_48/weights"} -> tensor<72x24x1x1xbf16> loc(#loc)
+    %136 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_46/biases"} -> tensor<24xbf16> loc(#loc)
+    %137 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_46/weights"} -> tensor<24x72x1x1xbf16> loc(#loc)
+    %138 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_43/biases"} -> tensor<72xbf16> loc(#loc)
+    %139 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_43/weights"} -> tensor<72x1x5x5xbf16> loc(#loc)
+    %140 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_41/biases"} -> tensor<72xbf16> loc(#loc)
+    %141 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_41/weights"} -> tensor<72x24x1x1xbf16> loc(#loc)
+    %142 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_39/biases"} -> tensor<24xbf16> loc(#loc)
+    %143 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_39/weights"} -> tensor<24x72x1x1xbf16> loc(#loc)
+    %144 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_37/biases"} -> tensor<72xbf16> loc(#loc)
+    %145 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_37/weights"} -> tensor<72x1x3x3xbf16> loc(#loc)
+    %146 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_35/biases"} -> tensor<72xbf16> loc(#loc)
+    %147 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_35/weights"} -> tensor<72x24x1x1xbf16> loc(#loc)
+    %148 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_34/biases"} -> tensor<24xbf16> loc(#loc)
+    %149 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_34/weights"} -> tensor<24x64x1x1xbf16> loc(#loc)
+    %150 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_32/biases"} -> tensor<64xbf16> loc(#loc)
+    %151 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_32/weights"} -> tensor<64x1x3x3xbf16> loc(#loc)
+    %152 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_30/biases"} -> tensor<64xbf16> loc(#loc)
+    %153 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_30/weights"} -> tensor<64x16x1x1xbf16> loc(#loc)
+    %154 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_28/biases"} -> tensor<16xbf16> loc(#loc)
+    %155 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_28/weights"} -> tensor<16x16x1x1xbf16> loc(#loc)
+    %156 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_26/biases"} -> tensor<16xbf16> loc(#loc)
+    %157 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_26/weights"} -> tensor<16x1x3x3xbf16> loc(#loc)
+    %158 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_17/biases"} -> tensor<16xbf16> loc(#loc)
+    %159 = xten_nn.load_external_const {file = "constants.h5", key = "Conv_17/weights"} -> tensor<16x3x3x3xbf16> loc(#loc)
+    %160 = xten_nn.load_external_const {file = "constants.h5", key = "Div_16/Constant_1_0"} -> tensor<1x3x180x320xbf16> loc(#loc6)
+    %161 = xten_nn.load_external_const {file = "constants.h5", key = "Sub_14/Constant_1_0"} -> tensor<1x3x180x320xbf16> loc(#loc309)
+    %162 = xten_nn.subgraph (%arg5 = %arg0: tensor<1x180x320x4xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_2",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 24, 20, 4]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 320, 4]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 180, 320, 4]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_2",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 24, 20, 4]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 320, 4]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 180, 320, 4]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 30800 : ui64, ofm = 15440 : ui64},
+        computation_cycles = 2373 : ui64,
+        cycle_count = 30800 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x180x320x4xbf16>)  attributes {
+        LayerName = "Div_2",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 180, 320, 4]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_2",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 180, 320, 4]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 24 : ui32,
+          config.ifmsv_height = 20 : ui32,
+          config.ifmsv_width = 4 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.906250e-03 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 131 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x180x320x4xbf16> loc(#loc1)
+        xten_nn.output %465 : tensor<1x180x320x4xbf16> loc(#loc1)
+      } -> tensor<1x180x320x4xbf16> loc(#loc1)
+      xten_nn.output %464 : tensor<1x180x320x4xbf16> loc(#loc1)
+    } -> tensor<1x180x320x4xbf16> loc(#loc1)
+    %163 = xten_nn.subgraph (%arg5 = %162: tensor<1x180x320x4xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Slice_7",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 180, 320, 4]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Slice_7",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 180, 320, 3]> : vector<4xindex>
+        }
+      ],
+      Specializes = "SliceHCWC8Adf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.axis_letter = "W",
+        config.dim_c = 184 : ui32,
+        config.dim_h = 320 : ui32,
+        config.dim_w = 4 : ui32,
+        config.dtype = "bfloat16",
+        config.end = 3 : ui32,
+        config.num_ifm_shim_ch = 2 : ui32,
+        config.num_ofm_shim_ch = 2 : ui32,
+        config.start = 0 : ui32,
+        config.step = 1 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x180x320x3xbf16> loc(#loc9)
+      xten_nn.output %464 : tensor<1x180x320x3xbf16> loc(#loc9)
+    } -> tensor<1x180x320x3xbf16> loc(#loc9)
+    %164 = xten_nn.subgraph (%arg5 = %163: tensor<1x180x320x3xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#0",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 180, 320, 3]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#1",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<[0, 4, 0, 5]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 180, 320, 3]> : vector<4xindex>
+        }
+      ],
+      Specializes = "BufferPadAdf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.dim_0 = 320 : ui32,
+        config.dim_0_padded = 320 : ui32,
+        config.dim_1 = 23 : ui32,
+        config.dim_1_padded = 23 : ui32,
+        config.dim_2 = 3 : ui32,
+        config.dim_2_padded = 8 : ui32,
+        config.dim_3 = 8 : ui32,
+        config.dim_3_padded = 8 : ui32,
+        config.dtype = "bfloat16"
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x180x320x3xbf16> loc(#loc10)
+      xten_nn.output %464 : tensor<1x180x320x3xbf16> loc(#loc10)
+    } -> tensor<1x180x320x3xbf16> loc(#loc10)
+    %165 = xten_nn.subgraph (%arg5 = %164: tensor<1x180x320x3xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#2",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<[0, 4, 0, 5]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 180, 320, 3]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#3",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<[0, 5, 4, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+        }
+      ],
+      Specializes = "Transpose4dAdf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.dim_0 = 320 : ui32,
+        config.dim_1 = 23 : ui32,
+        config.dim_2 = 8 : ui32,
+        config.dim_3 = 8 : ui32,
+        config.dtype = "bfloat16",
+        config.perm = 10 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x3x180x320xbf16> loc(#loc311)
+      xten_nn.output %464 : tensor<1x3x180x320xbf16> loc(#loc311)
+    } -> tensor<1x3x180x320xbf16> loc(#loc310)
+    %166 = xten_nn.subgraph (%arg5 = %165: tensor<1x3x180x320xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#4",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<[0, 5, 4, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#5",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+        }
+      ],
+      Specializes = "BufferUnpadAdf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.dim_0 = 184 : ui32,
+        config.dim_0_unpadded = 180 : ui32,
+        config.dim_1 = 1 : ui32,
+        config.dim_1_unpadded = 1 : ui32,
+        config.dim_2 = 320 : ui32,
+        config.dim_2_unpadded = 320 : ui32,
+        config.dim_3 = 8 : ui32,
+        config.dim_3_unpadded = 8 : ui32,
+        config.dtype = "bfloat16"
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x3x180x320xbf16> loc(#loc10)
+      xten_nn.output %464 : tensor<1x3x180x320xbf16> loc(#loc10)
+    } -> tensor<1x3x180x320xbf16> loc(#loc10)
+    %167 = xten_nn.subgraph (%arg5 = %166: tensor<1x3x180x320xbf16>, %arg6 = %161: tensor<1x3x180x320xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Sub_14",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 3, 5, 16]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 8, 20, 320]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 3, 5, 16]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 8, 20, 320]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Initializer_398",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 3, 5, 16]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 8, 20, 320]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 232200 : ui64, ofm = 117000 : ui64, wts = 232200 : ui64},
+        computation_cycles = 34045 : ui64,
+        cycle_count = 2089800 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "double", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x3x180x320xbf16>, %arg8 = %arg6: tensor<1x3x180x320xbf16>)  attributes {
+        LayerName = "Sub_14",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Initializer_398",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.act = 0 : ui8,
+          config.act_type = "LINEAR",
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 8 : ui32,
+          config.ifmsv_height = 5 : ui32,
+          config.ifmsv_width = 16 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 51 : ui64,
+          startup_cycles = 22 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x3x180x320xbf16> loc(#loc309)
+        xten_nn.output %465 : tensor<1x3x180x320xbf16> loc(#loc309)
+      } -> tensor<1x3x180x320xbf16> loc(#loc309)
+      xten_nn.output %464 : tensor<1x3x180x320xbf16> loc(#loc309)
+    } -> tensor<1x3x180x320xbf16> loc(#loc309)
+    %168 = xten_nn.subgraph (%arg5 = %167: tensor<1x3x180x320xbf16>, %arg6 = %160: tensor<1x3x180x320xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_16",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 3, 5, 16]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 8, 20, 320]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 3, 5, 16]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 8, 20, 320]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_16",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 3, 5, 16]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 8, 20, 320]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 232200 : ui64, ofm = 117000 : ui64, wts = 232200 : ui64},
+        computation_cycles = 30988 : ui64,
+        cycle_count = 2089800 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "double", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x3x180x320xbf16>, %arg8 = %arg6: tensor<1x3x180x320xbf16>)  attributes {
+        LayerName = "Div_16",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_16",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 8 : ui32,
+          config.ifmsv_height = 5 : ui32,
+          config.ifmsv_width = 16 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 34 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x3x180x320xbf16> loc(#loc6)
+        xten_nn.output %465 : tensor<1x3x180x320xbf16> loc(#loc6)
+      } -> tensor<1x3x180x320xbf16> loc(#loc6)
+      xten_nn.output %464 : tensor<1x3x180x320xbf16> loc(#loc6)
+    } -> tensor<1x3x180x320xbf16> loc(#loc6)
+    %169 = xten_nn.subgraph (%arg5 = %168: tensor<1x3x180x320xbf16>, %arg6 = %159: tensor<16x3x3x3xbf16>, %arg7 = %158: tensor<16xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_17",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 3, 10, 66]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 8, 61, 320]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[8, 3, 3, 3]> : vector<4xindex>,
+          l2_extend_end = dense<[16, 5, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[16, 3, 3, 3]> : vector<4xindex>,
+          l3_extend_end = dense<[16, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[16, 3, 3, 3]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_17",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 4, 32]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 2, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 30, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 79500 : ui64, ofm = 38700 : ui64, wts = 330 : ui64},
+        computation_cycles = 62525 : ui64,
+        cycle_count = 238500 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "double", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x3x180x320xbf16>, %arg9 = %arg6: tensor<16x3x3x3xbf16>, %arg10 = %arg7: tensor<16xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[1, 0], [1, 0]],
+        LayerName = "Conv_17",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[16, 3, 3, 3]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_17",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 8 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 10 : ui8,
+          config.ifm_sv_width.size = 66 : ui8,
+          config.ksize.height = 3 : ui8,
+          config.ksize.width = 3 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 1 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 8 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 2 : ui8,
+          config.stride_w = 2 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 1935 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x16x90x160xbf16> loc(#loc13)
+        xten_nn.output %465 : tensor<1x16x90x160xbf16> loc(#loc13)
+      } -> tensor<1x16x90x160xbf16> loc(#loc13)
+      xten_nn.output %464 : tensor<1x16x90x160xbf16> loc(#loc13)
+    } -> tensor<1x16x90x160xbf16> loc(#loc13)
+    %170 = xten_nn.subgraph (%arg5 = %169: tensor<1x16x90x160xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_19",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 23, 8]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_19",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 23, 8]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 2, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 59080 : ui64, ofm = 29640 : ui64},
+        computation_cycles = 5029 : ui64,
+        cycle_count = 59080 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x16x90x160xbf16>)  attributes {
+        LayerName = "Add_19",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_19",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 8 : ui32,
+          config.ifmsv_height = 23 : ui32,
+          config.ifmsv_width = 8 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 103 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x16x90x160xbf16> loc(#loc14)
+        xten_nn.output %465 : tensor<1x16x90x160xbf16> loc(#loc14)
+      } -> tensor<1x16x90x160xbf16> loc(#loc14)
+      xten_nn.output %464 : tensor<1x16x90x160xbf16> loc(#loc14)
+    } -> tensor<1x16x90x160xbf16> loc(#loc14)
+    %171 = xten_nn.subgraph (%arg5 = %170: tensor<1x16x90x160xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_22",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 12, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_force_single_buffering = true,
+          l2_tile_count = dense<[1, 16, 45, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_22",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 12, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_force_single_buffering = true,
+          l2_tile_count = dense<[1, 16, 45, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 61600 : ui64, ofm = 30880 : ui64},
+        computation_cycles = 4639 : ui64,
+        cycle_count = 123200 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x16x90x160xbf16>)  attributes {
+        LayerName = "Clip_22",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_22",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 8 : ui32,
+          config.ifmsv_height = 12 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 139 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x16x90x160xbf16> loc(#loc15)
+        xten_nn.output %465 : tensor<1x16x90x160xbf16> loc(#loc15)
+      } -> tensor<1x16x90x160xbf16> loc(#loc15)
+      xten_nn.output %464 : tensor<1x16x90x160xbf16> loc(#loc15)
+    } -> tensor<1x16x90x160xbf16> loc(#loc15)
+    %172 = xten_nn.subgraph (%arg5 = %171: tensor<1x16x90x160xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_24",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 23, 8]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_24",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 23, 8]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 2, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 59080 : ui64, ofm = 29640 : ui64},
+        computation_cycles = 5029 : ui64,
+        cycle_count = 59080 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x16x90x160xbf16>)  attributes {
+        LayerName = "Div_24",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_24",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 8 : ui32,
+          config.ifmsv_height = 23 : ui32,
+          config.ifmsv_width = 8 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 103 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x16x90x160xbf16> loc(#loc16)
+        xten_nn.output %465 : tensor<1x16x90x160xbf16> loc(#loc16)
+      } -> tensor<1x16x90x160xbf16> loc(#loc16)
+      xten_nn.output %464 : tensor<1x16x90x160xbf16> loc(#loc16)
+    } -> tensor<1x16x90x160xbf16> loc(#loc16)
+    %173 = xten_nn.subgraph (%arg5 = %169: tensor<1x16x90x160xbf16>, %arg6 = %172: tensor<1x16x90x160xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_25",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 8, 16]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 30, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 8, 16]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 30, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_25",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 8, 16]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 2, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 30, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 61740 : ui64, ifm2 = 61740 : ui64, ofm = 31020 : ui64},
+        computation_cycles = 5698 : ui64,
+        cycle_count = 185220 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "double", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x16x90x160xbf16>, %arg8 = %arg6: tensor<1x16x90x160xbf16>)  attributes {
+        LayerName = "Mul_25",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_25",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 8 : ui32,
+          config.ifmsv_height = 8 : ui32,
+          config.ifmsv_width = 16 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 46 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x16x90x160xbf16> loc(#loc17)
+        xten_nn.output %465 : tensor<1x16x90x160xbf16> loc(#loc17)
+      } -> tensor<1x16x90x160xbf16> loc(#loc17)
+      xten_nn.output %464 : tensor<1x16x90x160xbf16> loc(#loc17)
+    } -> tensor<1x16x90x160xbf16> loc(#loc17)
+    %174 = xten_nn.subgraph (%arg5 = %173: tensor<1x16x90x160xbf16>, %arg6 = %157: tensor<16x1x3x3xbf16>, %arg7 = %156: tensor<16xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_26",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 2]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 8, 18]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "CMHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 1]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[8, 1, 3, 3]> : vector<4xindex>,
+          l2_extend_end = dense<[16, 0, 0, 1]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[16, 1, 3, 3]> : vector<4xindex>,
+          l3_extend_end = dense<[16, 0, 0, 1]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[16, 1, 3, 3]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Relu_27",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 6, 16]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 6, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 102800 : ui64, ofm = 31120 : ui64, wts = 74 : ui64},
+        computation_cycles = 49653 : ui64,
+        cycle_count = 102800 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 4, 3, 0]> : vector<4xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x16x90x160xbf16>, %arg9 = %arg6: tensor<16x1x3x3xbf16>, %arg10 = %arg7: tensor<16xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[1, 1], [1, 1]],
+        LayerName = "Conv_26",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "CMHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[16, 1, 3, 3]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Relu_27",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          }
+        ],
+        Specializes = "DepthwiseConv2dBf16",
+        Traits = {
+          NonNegativeOut = true
+        },
+        With = {
+          config.act = 1 : ui8,
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.ifm_sv_depth.size = 8 : ui8,
+          config.ifm_sv_height.size = 8 : ui8,
+          config.ifm_sv_width.size = 18 : ui8,
+          config.kernel_height = 3 : ui8,
+          config.kernel_width = 3 : ui8,
+          config.stride = 1 : ui8,
+          data_io.ifm.dimensions.batch.padding = 0 : ui8,
+          data_io.ifm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.batch.padding = 0 : ui8,
+          data_io.ofm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.width.padding = 0 : ui8
+        },
+        estimation = {
+          compute_cycles = 1099 : ui64,
+          startup_cycles = 30 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x16x90x160xbf16> loc(#loc19)
+        xten_nn.output %465 : tensor<1x16x90x160xbf16> loc(#loc19)
+      } -> tensor<1x16x90x160xbf16> loc(#loc312)
+      xten_nn.output %464 : tensor<1x16x90x160xbf16> loc(#loc312)
+    } -> tensor<1x16x90x160xbf16> loc(#loc312)
+    %175 = xten_nn.subgraph (%arg5 = %174: tensor<1x16x90x160xbf16>, %arg6 = %155: tensor<16x16x1x1xbf16>, %arg7 = %154: tensor<16xbf16>, %arg8 = %173: tensor<1x16x90x160xbf16>)  attributes {
+      IfmOperands = [0 : index, 3 : index],
+      LayerName = "Conv_28",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 48, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 2, 32]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_force_single_buffering = true,
+          l2_tile_count = dense<[1, 16, 45, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<[0, 48, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[8, 16, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[16, 48, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[16, 16, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[16, 48, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[16, 16, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 2, 32]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_force_single_buffering = true,
+          l2_tile_count = dense<[1, 16, 45, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_29",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 2, 32]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_force_single_buffering = true,
+          l2_tile_count = dense<[1, 16, 45, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 123480 : ui64, ifm2 = 62040 : ui64, ofm = 31320 : ui64, wts = 298 : ui64},
+        computation_cycles = 76887 : ui64,
+        cycle_count = 246960 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg9 = %arg5: tensor<1x16x90x160xbf16>, %arg10 = %arg6: tensor<16x16x1x1xbf16>, %arg11 = %arg7: tensor<16xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_28",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[16, 16, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_28",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 64 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 2 : ui8,
+          config.ifm_sv_width.size = 32 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 1 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 8 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 1095 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %466 = tensor.empty() : tensor<1x16x90x160xbf16> loc(#loc20)
+        xten_nn.output %466 : tensor<1x16x90x160xbf16> loc(#loc20)
+      } -> tensor<1x16x90x160xbf16> loc(#loc20)
+      %465 = xten_nn.subgraph (%arg9 = %464: tensor<1x16x90x160xbf16>, %arg10 = %arg8: tensor<1x16x90x160xbf16>)  attributes {
+        LayerName = "Add_29",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_29",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.act = 0 : ui8,
+          config.act_type = "LINEAR",
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 8 : ui32,
+          config.ifmsv_height = 2 : ui32,
+          config.ifmsv_width = 32 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 43 : ui64,
+          startup_cycles = 22 : ui64
+        }} {
+        %466 = tensor.empty() : tensor<1x16x90x160xbf16> loc(#loc21)
+        xten_nn.output %466 : tensor<1x16x90x160xbf16> loc(#loc21)
+      } -> tensor<1x16x90x160xbf16> loc(#loc21)
+      xten_nn.output %465 : tensor<1x16x90x160xbf16> loc(#loc21)
+    } -> tensor<1x16x90x160xbf16> loc(#loc313)
+    %176 = xten_nn.subgraph (%arg5 = %175: tensor<1x16x90x160xbf16>, %arg6 = %153: tensor<64x16x1x1xbf16>, %arg7 = %152: tensor<64xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_30",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 48, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 9, 8]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 18, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<[0, 48, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[16, 16, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 48, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[64, 16, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 48, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[64, 16, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Relu_31",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 9, 8]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 64, 18, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 90, 160]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 115700 : ui64, ofm = 122100 : ui64, wts = 586 : ui64},
+        computation_cycles = 124593 : ui64,
+        cycle_count = 622965 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[3, 1, 2, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "double", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x16x90x160xbf16>, %arg9 = %arg6: tensor<64x16x1x1xbf16>, %arg10 = %arg7: tensor<64xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_30",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[64, 16, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Relu_31",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 64, 90, 160]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true,
+          NonNegativeOut = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 1 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 12 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 64 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 9 : ui8,
+          config.ifm_sv_width.size = 8 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 0.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 0.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 1 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 16 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 8 : ui8
+        },
+        estimation = {
+          compute_cycles = 2348 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x64x90x160xbf16> loc(#loc23)
+        xten_nn.output %465 : tensor<1x64x90x160xbf16> loc(#loc23)
+      } -> tensor<1x64x90x160xbf16> loc(#loc314)
+      xten_nn.output %464 : tensor<1x64x90x160xbf16> loc(#loc314)
+    } -> tensor<1x64x90x160xbf16> loc(#loc314)
+    %177 = xten_nn.subgraph (%arg5 = %176: tensor<1x64x90x160xbf16>, %arg6 = %151: tensor<64x1x3x3xbf16>, %arg7 = %150: tensor<64xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_32",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 2]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 6, 26]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 64, 17, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 90, 160]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "CMHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 1]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[8, 1, 3, 3]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 1]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[64, 1, 3, 3]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 0, 0, 1]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[64, 1, 3, 3]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Relu_33",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 2, 12]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 64, 8, 80]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 0, 3, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 45, 80]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 226632 : ui64, ofm = 16968 : ui64, wts = 148 : ui64},
+        computation_cycles = 58677 : ui64,
+        cycle_count = 1359792 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 4, 3, 0]> : vector<4xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "double", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x64x90x160xbf16>, %arg9 = %arg6: tensor<64x1x3x3xbf16>, %arg10 = %arg7: tensor<64xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[1, 0], [1, 0]],
+        LayerName = "Conv_32",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 64, 90, 160]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "CMHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[64, 1, 3, 3]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Relu_33",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 64, 45, 80]> : vector<4xindex>
+          }
+        ],
+        Specializes = "DepthwiseConv2dBf16",
+        Traits = {
+          NonNegativeOut = true
+        },
+        With = {
+          config.act = 1 : ui8,
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.ifm_sv_depth.size = 8 : ui8,
+          config.ifm_sv_height.size = 6 : ui8,
+          config.ifm_sv_width.size = 26 : ui8,
+          config.kernel_height = 3 : ui8,
+          config.kernel_width = 3 : ui8,
+          config.stride = 2 : ui8,
+          data_io.ifm.dimensions.batch.padding = 0 : ui8,
+          data_io.ifm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.batch.padding = 0 : ui8,
+          data_io.ofm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.width.padding = 0 : ui8
+        },
+        estimation = {
+          compute_cycles = 559 : ui64,
+          startup_cycles = 30 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x64x45x80xbf16> loc(#loc25)
+        xten_nn.output %465 : tensor<1x64x45x80xbf16> loc(#loc25)
+      } -> tensor<1x64x45x80xbf16> loc(#loc315)
+      xten_nn.output %464 : tensor<1x64x45x80xbf16> loc(#loc315)
+    } -> tensor<1x64x45x80xbf16> loc(#loc315)
+    %178 = xten_nn.subgraph (%arg5 = %177: tensor<1x64x45x80xbf16>)  attributes {
+      LayerName = "Generated-#60",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<[0, 0, 3, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 45, 80]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#61",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 45, 80]> : vector<4xindex>
+        }
+      ],
+      Specializes = "BufferUnpadAdf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.dim_0 = 48 : ui32,
+        config.dim_0_unpadded = 45 : ui32,
+        config.dim_1 = 8 : ui32,
+        config.dim_1_unpadded = 8 : ui32,
+        config.dim_2 = 80 : ui32,
+        config.dim_2_unpadded = 80 : ui32,
+        config.dim_3 = 8 : ui32,
+        config.dim_3_unpadded = 8 : ui32,
+        config.dtype = "bfloat16"
+      }} {
+      xten_nn.output %arg5 : tensor<1x64x45x80xbf16> loc(#loc10)
+    } -> tensor<1x64x45x80xbf16> loc(#loc10)
+    %179 = xten_nn.subgraph (%arg5 = %178: tensor<1x64x45x80xbf16>, %arg6 = %149: tensor<24x64x1x1xbf16>, %arg7 = %148: tensor<24xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_34",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 64, 4, 16]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 64, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 45, 80]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[16, 64, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[40, 0, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[24, 64, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[40, 0, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[24, 64, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_34",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 4, 16]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 40, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 30870 : ui64, ofm = 32790 : ui64, wts = 586 : ui64},
+        computation_cycles = 24283 : ui64,
+        cycle_count = 32790 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x64x45x80xbf16>, %arg9 = %arg6: tensor<24x64x1x1xbf16>, %arg10 = %arg7: tensor<24xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_34",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 64, 45, 80]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[24, 64, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_34",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 0 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 64 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 4 : ui8,
+          config.ifm_sv_width.size = 16 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 1 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 16 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 16 : ui8
+        },
+        estimation = {
+          compute_cycles = 1459 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x24x45x80xbf16> loc(#loc26)
+        xten_nn.output %465 : tensor<1x24x45x80xbf16> loc(#loc26)
+      } -> tensor<1x24x45x80xbf16> loc(#loc26)
+      xten_nn.output %464 : tensor<1x24x45x80xbf16> loc(#loc26)
+    } -> tensor<1x24x45x80xbf16> loc(#loc26)
+    %180 = xten_nn.subgraph (%arg5 = %179: tensor<1x24x45x80xbf16>, %arg6 = %147: tensor<72x24x1x1xbf16>, %arg7 = %146: tensor<72xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_35",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 40, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 24, 2, 32]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 40, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<[0, 40, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[24, 24, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[24, 40, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[72, 24, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[24, 40, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[72, 24, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Relu_36",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 24, 2, 32]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 3, 16]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 72, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 72, 45, 80]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 37044 : ui64, ofm = 32436 : ui64, wts = 874 : ui64},
+        computation_cycles = 32981 : ui64,
+        cycle_count = 37044 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x24x45x80xbf16>, %arg9 = %arg6: tensor<72x24x1x1xbf16>, %arg10 = %arg7: tensor<72xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_35",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[72, 24, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Relu_36",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 72, 45, 80]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true,
+          NonNegativeOut = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 1 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 64 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 2 : ui8,
+          config.ifm_sv_width.size = 32 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 0.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 0.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 1 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 24 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 1675 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x72x45x80xbf16> loc(#loc28)
+        xten_nn.output %465 : tensor<1x72x45x80xbf16> loc(#loc28)
+      } -> tensor<1x72x45x80xbf16> loc(#loc316)
+      xten_nn.output %464 : tensor<1x72x45x80xbf16> loc(#loc316)
+    } -> tensor<1x72x45x80xbf16> loc(#loc316)
+    %181 = xten_nn.subgraph (%arg5 = %180: tensor<1x72x45x80xbf16>, %arg6 = %145: tensor<72x1x3x3xbf16>, %arg7 = %144: tensor<72xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_37",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 2]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 8, 18]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_force_single_buffering = true,
+          l2_tile_count = dense<[1, 72, 25, 80]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 72, 45, 80]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "CMHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 1]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[8, 1, 3, 3]> : vector<4xindex>,
+          l2_extend_end = dense<[24, 0, 0, 1]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[72, 1, 3, 3]> : vector<4xindex>,
+          l3_extend_end = dense<[24, 0, 0, 1]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[72, 1, 3, 3]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Relu_38",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 6, 16]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_force_single_buffering = true,
+          l2_tile_count = dense<[1, 72, 23, 80]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 0, 1, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 72, 45, 80]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 77100 : ui64, ofm = 23340 : ui64, wts = 222 : ui64},
+        computation_cycles = 37293 : ui64,
+        cycle_count = 154200 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 4, 3, 0]> : vector<4xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x72x45x80xbf16>, %arg9 = %arg6: tensor<72x1x3x3xbf16>, %arg10 = %arg7: tensor<72xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[1, 1], [1, 1]],
+        LayerName = "Conv_37",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 72, 45, 80]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "CMHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[72, 1, 3, 3]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Relu_38",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 72, 45, 80]> : vector<4xindex>
+          }
+        ],
+        Specializes = "DepthwiseConv2dBf16",
+        Traits = {
+          NonNegativeOut = true
+        },
+        With = {
+          config.act = 1 : ui8,
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.ifm_sv_depth.size = 8 : ui8,
+          config.ifm_sv_height.size = 8 : ui8,
+          config.ifm_sv_width.size = 18 : ui8,
+          config.kernel_height = 3 : ui8,
+          config.kernel_width = 3 : ui8,
+          config.stride = 1 : ui8,
+          data_io.ifm.dimensions.batch.padding = 0 : ui8,
+          data_io.ifm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.batch.padding = 0 : ui8,
+          data_io.ofm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.width.padding = 0 : ui8
+        },
+        estimation = {
+          compute_cycles = 1099 : ui64,
+          startup_cycles = 30 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x72x45x80xbf16> loc(#loc30)
+        xten_nn.output %465 : tensor<1x72x45x80xbf16> loc(#loc30)
+      } -> tensor<1x72x45x80xbf16> loc(#loc317)
+      xten_nn.output %464 : tensor<1x72x45x80xbf16> loc(#loc317)
+    } -> tensor<1x72x45x80xbf16> loc(#loc317)
+    %182 = xten_nn.subgraph (%arg5 = %181: tensor<1x72x45x80xbf16>)  attributes {
+      LayerName = "Generated-#62",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<[0, 0, 1, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 72, 45, 80]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#63",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 72, 45, 80]> : vector<4xindex>
+        }
+      ],
+      Specializes = "BufferUnpadAdf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.dim_0 = 46 : ui32,
+        config.dim_0_unpadded = 45 : ui32,
+        config.dim_1 = 9 : ui32,
+        config.dim_1_unpadded = 9 : ui32,
+        config.dim_2 = 80 : ui32,
+        config.dim_2_unpadded = 80 : ui32,
+        config.dim_3 = 8 : ui32,
+        config.dim_3_unpadded = 8 : ui32,
+        config.dtype = "bfloat16"
+      }} {
+      xten_nn.output %arg5 : tensor<1x72x45x80xbf16> loc(#loc10)
+    } -> tensor<1x72x45x80xbf16> loc(#loc10)
+    %183 = xten_nn.subgraph (%arg5 = %182: tensor<1x72x45x80xbf16>, %arg6 = %143: tensor<24x72x1x1xbf16>, %arg7 = %142: tensor<24xbf16>, %arg8 = %179: tensor<1x24x45x80xbf16>)  attributes {
+      IfmOperands = [0 : index, 3 : index],
+      LayerName = "Conv_39",
+      OfmShare = 3 : index,
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 72, 4, 16]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 72, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 72, 45, 80]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[16, 72, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[40, 0, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[24, 72, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[40, 0, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[24, 72, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 4, 16]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 40, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_40",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 4, 16]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 40, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 34710 : ui64, ifm2 = 30870 : ui64, ofm = 15510 : ui64, wts = 650 : ui64},
+        computation_cycles = 27290 : ui64,
+        cycle_count = 34710 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg9 = %arg5: tensor<1x72x45x80xbf16>, %arg10 = %arg6: tensor<24x72x1x1xbf16>, %arg11 = %arg7: tensor<24xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_39",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 72, 45, 80]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[24, 72, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_39",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 0 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 72 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 4 : ui8,
+          config.ifm_sv_width.size = 16 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 1 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 16 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 16 : ui8
+        },
+        estimation = {
+          compute_cycles = 1583 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %466 = tensor.empty() : tensor<1x24x45x80xbf16> loc(#loc31)
+        xten_nn.output %466 : tensor<1x24x45x80xbf16> loc(#loc31)
+      } -> tensor<1x24x45x80xbf16> loc(#loc31)
+      %465 = xten_nn.subgraph (%arg9 = %464: tensor<1x24x45x80xbf16>, %arg10 = %arg8: tensor<1x24x45x80xbf16>)  attributes {
+        LayerName = "Add_40",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_40",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.act = 0 : ui8,
+          config.act_type = "LINEAR",
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 4 : ui32,
+          config.ifmsv_width = 16 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 75 : ui64,
+          startup_cycles = 22 : ui64
+        }} {
+        %466 = tensor.empty() : tensor<1x24x45x80xbf16> loc(#loc32)
+        xten_nn.output %466 : tensor<1x24x45x80xbf16> loc(#loc32)
+      } -> tensor<1x24x45x80xbf16> loc(#loc32)
+      xten_nn.output %465 : tensor<1x24x45x80xbf16> loc(#loc32)
+    } -> tensor<1x24x45x80xbf16> loc(#loc318)
+    %184 = xten_nn.subgraph (%arg5 = %183: tensor<1x24x45x80xbf16>, %arg6 = %141: tensor<72x24x1x1xbf16>, %arg7 = %140: tensor<72xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_41",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 40, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 24, 2, 32]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 40, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<[0, 40, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[24, 24, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[24, 40, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[72, 24, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[24, 40, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[72, 24, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Relu_42",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 24, 2, 32]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 3, 16]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 72, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 72, 45, 80]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 37044 : ui64, ofm = 32436 : ui64, wts = 874 : ui64},
+        computation_cycles = 32981 : ui64,
+        cycle_count = 37044 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x24x45x80xbf16>, %arg9 = %arg6: tensor<72x24x1x1xbf16>, %arg10 = %arg7: tensor<72xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_41",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[72, 24, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Relu_42",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 72, 45, 80]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true,
+          NonNegativeOut = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 1 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 64 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 2 : ui8,
+          config.ifm_sv_width.size = 32 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 0.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 0.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 1 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 24 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 1675 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x72x45x80xbf16> loc(#loc34)
+        xten_nn.output %465 : tensor<1x72x45x80xbf16> loc(#loc34)
+      } -> tensor<1x72x45x80xbf16> loc(#loc319)
+      xten_nn.output %464 : tensor<1x72x45x80xbf16> loc(#loc319)
+    } -> tensor<1x72x45x80xbf16> loc(#loc319)
+    %185 = xten_nn.subgraph (%arg5 = %184: tensor<1x72x45x80xbf16>, %arg6 = %139: tensor<72x1x5x5xbf16>, %arg7 = %138: tensor<72xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_43",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 8, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 3, 16]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 72, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 72, 45, 80]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "CMHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 3]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[8, 1, 5, 5]> : vector<4xindex>,
+          l2_extend_end = dense<[24, 0, 0, 3]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[72, 1, 5, 5]> : vector<4xindex>,
+          l3_extend_end = dense<[24, 0, 0, 3]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[72, 1, 5, 5]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Relu_44",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 2, 8]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 72, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 72, 23, 40]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 115650 : ui64, ofm = 6210 : ui64, wts = 558 : ui64},
+        computation_cycles = 35313 : ui64,
+        cycle_count = 115650 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 4, 3, 0]> : vector<4xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x72x45x80xbf16>, %arg9 = %arg6: tensor<72x1x5x5xbf16>, %arg10 = %arg7: tensor<72xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[2, 2], [2, 1]],
+        LayerName = "Conv_43",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 72, 45, 80]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "CMHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[72, 1, 5, 5]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Relu_44",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 72, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "DepthwiseConv2dBf16",
+        Traits = {
+          NonNegativeOut = true
+        },
+        With = {
+          config.act = 1 : ui8,
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.ifm_sv_depth.size = 8 : ui8,
+          config.ifm_sv_height.size = 8 : ui8,
+          config.ifm_sv_width.size = 20 : ui8,
+          config.kernel_height = 5 : ui8,
+          config.kernel_width = 5 : ui8,
+          config.stride = 2 : ui8,
+          data_io.ifm.dimensions.batch.padding = 0 : ui8,
+          data_io.ifm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.batch.padding = 0 : ui8,
+          data_io.ofm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.width.padding = 0 : ui8
+        },
+        estimation = {
+          compute_cycles = 643 : ui64,
+          startup_cycles = 30 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x72x23x40xbf16> loc(#loc36)
+        xten_nn.output %465 : tensor<1x72x23x40xbf16> loc(#loc36)
+      } -> tensor<1x72x23x40xbf16> loc(#loc320)
+      xten_nn.output %464 : tensor<1x72x23x40xbf16> loc(#loc320)
+    } -> tensor<1x72x23x40xbf16> loc(#loc320)
+    %186 = xten_nn.subgraph (%arg5 = %185: tensor<1x72x23x40xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#6",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 72, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#7",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 72, 1, 920]> : vector<4xindex>
+        }
+      ],
+      Specializes = "Transpose4dAdf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.dim_0 = 23 : ui32,
+        config.dim_1 = 9 : ui32,
+        config.dim_2 = 40 : ui32,
+        config.dim_3 = 8 : ui32,
+        config.dtype = "bfloat16",
+        config.perm = 6 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x72x1x920xbf16> loc(#loc37)
+      xten_nn.output %464 : tensor<1x72x1x920xbf16> loc(#loc37)
+    } -> tensor<1x72x1x920xbf16> loc(#loc37)
+    %187 = xten_nn.subgraph (%arg5 = %186: tensor<1x72x1x920xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#8",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 1, 64]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 72, 1, 920]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 72, 1, 920]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#9",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 56, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 61590 : ui64, ofm = 3990 : ui64},
+        computation_cycles = 66253 : ui64,
+        cycle_count = 66253 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x72x1x920xbf16>)  attributes {
+        LayerName = "Generated-#8",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 72, 1, 920]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Generated-#9",
+        PadValue = 0.000000e+00 : bf16,
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ReduceMeanC8Bf16",
+        Traits = {
+          Reduce = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.full_channel = 72 : ui32,
+          config.full_height = 1 : ui32,
+          config.full_width = 920 : ui32,
+          config.reduce_dim = "W",
+          config.sv_channel = 32 : ui32,
+          config.sv_height = 1 : ui32,
+          config.sv_width = 64 : ui32
+        },
+        estimation = {
+          compute_cycles = 2337 : ui64,
+          startup_cycles = 190 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x72x1x1xbf16> loc(#loc37)
+        xten_nn.output %465 : tensor<1x72x1x1xbf16> loc(#loc37)
+      } -> tensor<1x72x1x1xbf16> loc(#loc37)
+      xten_nn.output %464 : tensor<1x72x1x1xbf16> loc(#loc37)
+    } -> tensor<1x72x1x1xbf16> loc(#loc37)
+    %188 = xten_nn.subgraph (%arg5 = %187: tensor<1x72x1x1xbf16>, %arg6 = %137: tensor<24x72x1x1xbf16>, %arg7 = %136: tensor<24xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_46",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 15]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 56, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[16, 72, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[40, 0, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[24, 72, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[40, 0, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[24, 72, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Relu_47",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 15]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 40, 0, 63]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 24, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 24, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 586 : ui64, ofm = 778 : ui64, wts = 650 : ui64},
+        computation_cycles = 1216 : ui64,
+        cycle_count = 1216 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[3, 1, 2, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x72x1x1xbf16>, %arg9 = %arg6: tensor<24x72x1x1xbf16>, %arg10 = %arg7: tensor<24xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_46",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[24, 72, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Relu_47",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 24, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true,
+          NonNegativeOut = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 1 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 12 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 72 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 16 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 0.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 0.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 1 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 16 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 16 : ui8
+        },
+        estimation = {
+          compute_cycles = 736 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x24x1x1xbf16> loc(#loc39)
+        xten_nn.output %465 : tensor<1x24x1x1xbf16> loc(#loc39)
+      } -> tensor<1x24x1x1xbf16> loc(#loc321)
+      xten_nn.output %464 : tensor<1x24x1x1xbf16> loc(#loc321)
+    } -> tensor<1x24x1x1xbf16> loc(#loc321)
+    %189 = xten_nn.subgraph (%arg5 = %188: tensor<1x24x1x1xbf16>, %arg6 = %135: tensor<72x24x1x1xbf16>, %arg7 = %134: tensor<72xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_48",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 40, 0, 7]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 24, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 40, 0, 63]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 24, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 24, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<[0, 40, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[32, 24, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[56, 40, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[72, 24, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[56, 40, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[72, 24, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_48",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 7]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 56, 0, 31]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 266 : ui64, ofm = 650 : ui64, wts = 1162 : ui64},
+        computation_cycles = 1233 : ui64,
+        cycle_count = 1233 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[3, 1, 2, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x24x1x1xbf16>, %arg9 = %arg6: tensor<72x24x1x1xbf16>, %arg10 = %arg7: tensor<72xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_48",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 24, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[72, 24, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_48",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 12 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 64 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 8 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 1 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 32 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 8 : ui8
+        },
+        estimation = {
+          compute_cycles = 753 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x72x1x1xbf16> loc(#loc40)
+        xten_nn.output %465 : tensor<1x72x1x1xbf16> loc(#loc40)
+      } -> tensor<1x72x1x1xbf16> loc(#loc40)
+      xten_nn.output %464 : tensor<1x72x1x1xbf16> loc(#loc40)
+    } -> tensor<1x72x1x1xbf16> loc(#loc40)
+    %190 = xten_nn.subgraph (%arg5 = %189: tensor<1x72x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_50",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 15, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 24, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 56, 0, 31]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_50",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 15, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 24, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 63, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 778 : ui64, ofm = 394 : ui64},
+        computation_cycles = 401 : ui64,
+        cycle_count = 778 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x72x1x1xbf16>)  attributes {
+        LayerName = "Add_50",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_50",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 24 : ui32,
+          config.ifmsv_height = 16 : ui32,
+          config.ifmsv_width = 1 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 35 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x72x1x1xbf16> loc(#loc41)
+        xten_nn.output %465 : tensor<1x72x1x1xbf16> loc(#loc41)
+      } -> tensor<1x72x1x1xbf16> loc(#loc41)
+      xten_nn.output %464 : tensor<1x72x1x1xbf16> loc(#loc41)
+    } -> tensor<1x72x1x1xbf16> loc(#loc41)
+    %191 = xten_nn.subgraph (%arg5 = %190: tensor<1x72x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_53",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 7, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 63, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_53",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 7, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 56, 31, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 522 : ui64, ofm = 266 : ui64},
+        computation_cycles = 395 : ui64,
+        cycle_count = 522 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x72x1x1xbf16>)  attributes {
+        LayerName = "Clip_53",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_53",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 32 : ui32,
+          config.ifmsv_height = 8 : ui32,
+          config.ifmsv_width = 1 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 35 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x72x1x1xbf16> loc(#loc42)
+        xten_nn.output %465 : tensor<1x72x1x1xbf16> loc(#loc42)
+      } -> tensor<1x72x1x1xbf16> loc(#loc42)
+      xten_nn.output %464 : tensor<1x72x1x1xbf16> loc(#loc42)
+    } -> tensor<1x72x1x1xbf16> loc(#loc42)
+    %192 = xten_nn.subgraph (%arg5 = %191: tensor<1x72x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_55",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 15, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 56, 31, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_55",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 15, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 56, 63, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 1034 : ui64, ofm = 522 : ui64},
+        computation_cycles = 409 : ui64,
+        cycle_count = 1034 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x72x1x1xbf16>)  attributes {
+        LayerName = "Div_55",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_55",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 32 : ui32,
+          config.ifmsv_height = 16 : ui32,
+          config.ifmsv_width = 1 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 43 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x72x1x1xbf16> loc(#loc43)
+        xten_nn.output %465 : tensor<1x72x1x1xbf16> loc(#loc43)
+      } -> tensor<1x72x1x1xbf16> loc(#loc43)
+      xten_nn.output %464 : tensor<1x72x1x1xbf16> loc(#loc43)
+    } -> tensor<1x72x1x1xbf16> loc(#loc43)
+    %193 = xten_nn.subgraph (%arg5 = %192: tensor<1x72x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#10",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 72, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#11",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 72, 23, 40]> : vector<4xindex>
+        }
+      ],
+      Specializes = "TileAdf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.dtype = "bfloat16",
+        config.i_dim_c = 72 : ui32,
+        config.i_dim_h = 1 : ui32,
+        config.i_dim_n = 1 : ui32,
+        config.i_dim_w = 1 : ui32,
+        config.rep_dim_c = 1 : ui32,
+        config.rep_dim_h = 23 : ui32,
+        config.rep_dim_w = 40 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x72x23x40xbf16> loc(#loc44)
+      xten_nn.output %464 : tensor<1x72x23x40xbf16> loc(#loc44)
+    } -> tensor<1x72x23x40xbf16> loc(#loc44)
+    %194 = xten_nn.subgraph (%arg5 = %193: tensor<1x72x23x40xbf16>, %arg6 = %185: tensor<1x72x23x40xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_56",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 6, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 72, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 72, 23, 40]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 6, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 72, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 72, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_56",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 6, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 72, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 72, 23, 40]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 11580 : ui64, ifm2 = 11580 : ui64, ofm = 5820 : ui64},
+        computation_cycles = 1294 : ui64,
+        cycle_count = 11580 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x72x23x40xbf16>, %arg8 = %arg6: tensor<1x72x23x40xbf16>)  attributes {
+        LayerName = "Mul_56",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 72, 23, 40]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 72, 23, 40]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_56",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 72, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 8 : ui32,
+          config.ifmsv_height = 6 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x72x23x40xbf16> loc(#loc44)
+        xten_nn.output %465 : tensor<1x72x23x40xbf16> loc(#loc44)
+      } -> tensor<1x72x23x40xbf16> loc(#loc44)
+      xten_nn.output %464 : tensor<1x72x23x40xbf16> loc(#loc44)
+    } -> tensor<1x72x23x40xbf16> loc(#loc44)
+    %195 = xten_nn.subgraph (%arg5 = %194: tensor<1x72x23x40xbf16>, %arg6 = %133: tensor<40x72x1x1xbf16>, %arg7 = %132: tensor<40xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_57",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 72, 6, 8]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 72, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 72, 23, 40]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[16, 72, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[24, 0, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[40, 72, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[24, 0, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[40, 72, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_57",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 6, 8]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 8690 : ui64, ofm = 8370 : ui64, wts = 650 : ui64},
+        computation_cycles = 9983 : ui64,
+        cycle_count = 9983 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x72x23x40xbf16>, %arg9 = %arg6: tensor<40x72x1x1xbf16>, %arg10 = %arg7: tensor<40xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_57",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 72, 23, 40]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[40, 72, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_57",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 12 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 72 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 6 : ui8,
+          config.ifm_sv_width.size = 8 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 1 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 16 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 8 : ui8
+        },
+        estimation = {
+          compute_cycles = 1791 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x40x23x40xbf16> loc(#loc45)
+        xten_nn.output %465 : tensor<1x40x23x40xbf16> loc(#loc45)
+      } -> tensor<1x40x23x40xbf16> loc(#loc45)
+      xten_nn.output %464 : tensor<1x40x23x40xbf16> loc(#loc45)
+    } -> tensor<1x40x23x40xbf16> loc(#loc45)
+    %196 = xten_nn.subgraph (%arg5 = %195: tensor<1x40x23x40xbf16>, %arg6 = %131: tensor<120x40x1x1xbf16>, %arg7 = %130: tensor<120xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_58",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 24, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 40, 2, 32]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<[0, 24, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[32, 40, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[8, 24, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[120, 40, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[8, 24, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[120, 40, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Relu_59",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 2, 32]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 1, 24]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 12348 : ui64, ofm = 13884 : ui64, wts = 1162 : ui64},
+        computation_cycles = 12977 : ui64,
+        cycle_count = 13884 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x40x23x40xbf16>, %arg9 = %arg6: tensor<120x40x1x1xbf16>, %arg10 = %arg7: tensor<120xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_58",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[120, 40, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Relu_59",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true,
+          NonNegativeOut = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 1 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 64 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 2 : ui8,
+          config.ifm_sv_width.size = 32 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 0.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 0.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 1 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 32 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 1965 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x120x23x40xbf16> loc(#loc47)
+        xten_nn.output %465 : tensor<1x120x23x40xbf16> loc(#loc47)
+      } -> tensor<1x120x23x40xbf16> loc(#loc322)
+      xten_nn.output %464 : tensor<1x120x23x40xbf16> loc(#loc322)
+    } -> tensor<1x120x23x40xbf16> loc(#loc322)
+    %197 = xten_nn.subgraph (%arg5 = %196: tensor<1x120x23x40xbf16>, %arg6 = %129: tensor<120x1x5x5xbf16>, %arg7 = %128: tensor<120xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_60",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 10, 12]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 1, 24]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "CMHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 3]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[8, 1, 5, 5]> : vector<4xindex>,
+          l2_extend_end = dense<[8, 0, 0, 3]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[120, 1, 5, 5]> : vector<4xindex>,
+          l3_extend_end = dense<[8, 0, 0, 3]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[120, 1, 5, 5]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Relu_61",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 6, 8]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 38600 : ui64, ofm = 7880 : ui64, wts = 744 : ui64},
+        computation_cycles = 22053 : ui64,
+        cycle_count = 38600 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 4, 3, 0]> : vector<4xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x120x23x40xbf16>, %arg9 = %arg6: tensor<120x1x5x5xbf16>, %arg10 = %arg7: tensor<120xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[2, 2], [2, 2]],
+        LayerName = "Conv_60",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "CMHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[120, 1, 5, 5]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Relu_61",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "DepthwiseConv2dBf16",
+        Traits = {
+          NonNegativeOut = true
+        },
+        With = {
+          config.act = 1 : ui8,
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.ifm_sv_depth.size = 8 : ui8,
+          config.ifm_sv_height.size = 10 : ui8,
+          config.ifm_sv_width.size = 12 : ui8,
+          config.kernel_height = 5 : ui8,
+          config.kernel_width = 5 : ui8,
+          config.stride = 1 : ui8,
+          data_io.ifm.dimensions.batch.padding = 0 : ui8,
+          data_io.ifm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.batch.padding = 0 : ui8,
+          data_io.ofm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.width.padding = 0 : ui8
+        },
+        estimation = {
+          compute_cycles = 955 : ui64,
+          startup_cycles = 30 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x120x23x40xbf16> loc(#loc49)
+        xten_nn.output %465 : tensor<1x120x23x40xbf16> loc(#loc49)
+      } -> tensor<1x120x23x40xbf16> loc(#loc323)
+      xten_nn.output %464 : tensor<1x120x23x40xbf16> loc(#loc323)
+    } -> tensor<1x120x23x40xbf16> loc(#loc323)
+    %198 = xten_nn.subgraph (%arg5 = %197: tensor<1x120x23x40xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#12",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#13",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 1, 920]> : vector<4xindex>
+        }
+      ],
+      Specializes = "Transpose4dAdf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.dim_0 = 23 : ui32,
+        config.dim_1 = 15 : ui32,
+        config.dim_2 = 40 : ui32,
+        config.dim_3 = 8 : ui32,
+        config.dtype = "bfloat16",
+        config.perm = 6 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x120x1x920xbf16> loc(#loc50)
+      xten_nn.output %464 : tensor<1x120x1x920xbf16> loc(#loc50)
+    } -> tensor<1x120x1x920xbf16> loc(#loc50)
+    %199 = xten_nn.subgraph (%arg5 = %198: tensor<1x120x1x920xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#14",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 1, 64]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 1, 920]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 1, 920]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#15",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 61590 : ui64, ofm = 3990 : ui64},
+        computation_cycles = 66253 : ui64,
+        cycle_count = 66253 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x120x1x920xbf16>)  attributes {
+        LayerName = "Generated-#14",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 1, 920]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Generated-#15",
+        PadValue = 0.000000e+00 : bf16,
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ReduceMeanC8Bf16",
+        Traits = {
+          Reduce = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.full_channel = 120 : ui32,
+          config.full_height = 1 : ui32,
+          config.full_width = 920 : ui32,
+          config.reduce_dim = "W",
+          config.sv_channel = 32 : ui32,
+          config.sv_height = 1 : ui32,
+          config.sv_width = 64 : ui32
+        },
+        estimation = {
+          compute_cycles = 2337 : ui64,
+          startup_cycles = 190 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x120x1x1xbf16> loc(#loc50)
+        xten_nn.output %465 : tensor<1x120x1x1xbf16> loc(#loc50)
+      } -> tensor<1x120x1x1xbf16> loc(#loc50)
+      xten_nn.output %464 : tensor<1x120x1x1xbf16> loc(#loc50)
+    } -> tensor<1x120x1x1xbf16> loc(#loc50)
+    %200 = xten_nn.subgraph (%arg5 = %199: tensor<1x120x1x1xbf16>, %arg6 = %127: tensor<32x120x1x1xbf16>, %arg7 = %126: tensor<32xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_63",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 15]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[16, 120, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[32, 0, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[32, 120, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[32, 0, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[32, 120, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Relu_64",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 15]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 63]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 970 : ui64, ofm = 778 : ui64, wts = 1034 : ui64},
+        computation_cycles = 1498 : ui64,
+        cycle_count = 1498 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[3, 1, 2, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x120x1x1xbf16>, %arg9 = %arg6: tensor<32x120x1x1xbf16>, %arg10 = %arg7: tensor<32xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_63",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[32, 120, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Relu_64",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true,
+          NonNegativeOut = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 1 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 12 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 120 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 16 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 0.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 0.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 1 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 16 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 16 : ui8
+        },
+        estimation = {
+          compute_cycles = 1018 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x32x1x1xbf16> loc(#loc52)
+        xten_nn.output %465 : tensor<1x32x1x1xbf16> loc(#loc52)
+      } -> tensor<1x32x1x1xbf16> loc(#loc324)
+      xten_nn.output %464 : tensor<1x32x1x1xbf16> loc(#loc324)
+    } -> tensor<1x32x1x1xbf16> loc(#loc324)
+    %201 = xten_nn.subgraph (%arg5 = %200: tensor<1x32x1x1xbf16>, %arg6 = %125: tensor<120x32x1x1xbf16>, %arg7 = %124: tensor<120xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_65",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 32, 0, 7]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 63]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[32, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[8, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[120, 32, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[8, 32, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[120, 32, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_65",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 7]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 31]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 266 : ui64, ofm = 650 : ui64, wts = 1162 : ui64},
+        computation_cycles = 1233 : ui64,
+        cycle_count = 1233 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[3, 1, 2, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x32x1x1xbf16>, %arg9 = %arg6: tensor<120x32x1x1xbf16>, %arg10 = %arg7: tensor<120xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_65",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[120, 32, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_65",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 12 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 64 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 8 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 1 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 32 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 8 : ui8
+        },
+        estimation = {
+          compute_cycles = 753 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x120x1x1xbf16> loc(#loc53)
+        xten_nn.output %465 : tensor<1x120x1x1xbf16> loc(#loc53)
+      } -> tensor<1x120x1x1xbf16> loc(#loc53)
+      xten_nn.output %464 : tensor<1x120x1x1xbf16> loc(#loc53)
+    } -> tensor<1x120x1x1xbf16> loc(#loc53)
+    %202 = xten_nn.subgraph (%arg5 = %201: tensor<1x120x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_67",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 11, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 31]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_67",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 11, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 47, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 778 : ui64, ofm = 394 : ui64},
+        computation_cycles = 401 : ui64,
+        cycle_count = 778 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x120x1x1xbf16>)  attributes {
+        LayerName = "Add_67",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_67",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 32 : ui32,
+          config.ifmsv_height = 12 : ui32,
+          config.ifmsv_width = 1 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 35 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x120x1x1xbf16> loc(#loc54)
+        xten_nn.output %465 : tensor<1x120x1x1xbf16> loc(#loc54)
+      } -> tensor<1x120x1x1xbf16> loc(#loc54)
+      xten_nn.output %464 : tensor<1x120x1x1xbf16> loc(#loc54)
+    } -> tensor<1x120x1x1xbf16> loc(#loc54)
+    %203 = xten_nn.subgraph (%arg5 = %202: tensor<1x120x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_70",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 7, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 47, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_70",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 7, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 31, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 522 : ui64, ofm = 266 : ui64},
+        computation_cycles = 395 : ui64,
+        cycle_count = 522 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x120x1x1xbf16>)  attributes {
+        LayerName = "Clip_70",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_70",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 32 : ui32,
+          config.ifmsv_height = 8 : ui32,
+          config.ifmsv_width = 1 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 35 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x120x1x1xbf16> loc(#loc55)
+        xten_nn.output %465 : tensor<1x120x1x1xbf16> loc(#loc55)
+      } -> tensor<1x120x1x1xbf16> loc(#loc55)
+      xten_nn.output %464 : tensor<1x120x1x1xbf16> loc(#loc55)
+    } -> tensor<1x120x1x1xbf16> loc(#loc55)
+    %204 = xten_nn.subgraph (%arg5 = %203: tensor<1x120x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_72",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 15, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 31, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_72",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 15, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 63, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 1034 : ui64, ofm = 522 : ui64},
+        computation_cycles = 409 : ui64,
+        cycle_count = 1034 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x120x1x1xbf16>)  attributes {
+        LayerName = "Div_72",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_72",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 32 : ui32,
+          config.ifmsv_height = 16 : ui32,
+          config.ifmsv_width = 1 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 43 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x120x1x1xbf16> loc(#loc56)
+        xten_nn.output %465 : tensor<1x120x1x1xbf16> loc(#loc56)
+      } -> tensor<1x120x1x1xbf16> loc(#loc56)
+      xten_nn.output %464 : tensor<1x120x1x1xbf16> loc(#loc56)
+    } -> tensor<1x120x1x1xbf16> loc(#loc56)
+    %205 = xten_nn.subgraph (%arg5 = %204: tensor<1x120x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#16",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#17",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+        }
+      ],
+      Specializes = "TileAdf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.dtype = "bfloat16",
+        config.i_dim_c = 120 : ui32,
+        config.i_dim_h = 1 : ui32,
+        config.i_dim_n = 1 : ui32,
+        config.i_dim_w = 1 : ui32,
+        config.rep_dim_c = 1 : ui32,
+        config.rep_dim_h = 23 : ui32,
+        config.rep_dim_w = 40 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x120x23x40xbf16> loc(#loc57)
+      xten_nn.output %464 : tensor<1x120x23x40xbf16> loc(#loc57)
+    } -> tensor<1x120x23x40xbf16> loc(#loc57)
+    %206 = xten_nn.subgraph (%arg5 = %205: tensor<1x120x23x40xbf16>, %arg6 = %197: tensor<1x120x23x40xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_73",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 6, 10]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 6, 10]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_73",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 6, 10]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 15440 : ui64, ifm2 = 15440 : ui64, ofm = 7760 : ui64},
+        computation_cycles = 1656 : ui64,
+        cycle_count = 15440 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x120x23x40xbf16>, %arg8 = %arg6: tensor<1x120x23x40xbf16>)  attributes {
+        LayerName = "Mul_73",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_73",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 6 : ui32,
+          config.ifmsv_width = 10 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x120x23x40xbf16> loc(#loc57)
+        xten_nn.output %465 : tensor<1x120x23x40xbf16> loc(#loc57)
+      } -> tensor<1x120x23x40xbf16> loc(#loc57)
+      xten_nn.output %464 : tensor<1x120x23x40xbf16> loc(#loc57)
+    } -> tensor<1x120x23x40xbf16> loc(#loc57)
+    %207 = xten_nn.subgraph (%arg5 = %206: tensor<1x120x23x40xbf16>, %arg6 = %123: tensor<40x120x1x1xbf16>, %arg7 = %122: tensor<40xbf16>, %arg8 = %195: tensor<1x40x23x40xbf16>)  attributes {
+      IfmOperands = [0 : index, 3 : index],
+      LayerName = "Conv_74",
+      OfmShare = 3 : index,
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 64, 1, 40]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[16, 64, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[24, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[40, 120, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[24, 8, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[40, 120, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 1, 40]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_75",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 1, 40]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 15480 : ui64, ifm2 = 7740 : ui64, ofm = 3900 : ui64, wts = 1172 : ui64},
+        computation_cycles = 16811 : ui64,
+        cycle_count = 16811 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg9 = %arg5: tensor<1x120x23x40xbf16>, %arg10 = %arg6: tensor<40x120x1x1xbf16>, %arg11 = %arg7: tensor<40xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_74",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[40, 120, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_74",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 12 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 64 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 40 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 2 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 16 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 40 : ui8
+        },
+        estimation = {
+          compute_cycles = 2416 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %466 = tensor.empty() : tensor<1x40x23x40xbf16> loc(#loc58)
+        xten_nn.output %466 : tensor<1x40x23x40xbf16> loc(#loc58)
+      } -> tensor<1x40x23x40xbf16> loc(#loc58)
+      %465 = xten_nn.subgraph (%arg9 = %464: tensor<1x40x23x40xbf16>, %arg10 = %arg8: tensor<1x40x23x40xbf16>)  attributes {
+        LayerName = "Add_75",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_75",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.act = 0 : ui8,
+          config.act_type = "LINEAR",
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 40 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 51 : ui64,
+          startup_cycles = 22 : ui64
+        }} {
+        %466 = tensor.empty() : tensor<1x40x23x40xbf16> loc(#loc59)
+        xten_nn.output %466 : tensor<1x40x23x40xbf16> loc(#loc59)
+      } -> tensor<1x40x23x40xbf16> loc(#loc59)
+      xten_nn.output %465 : tensor<1x40x23x40xbf16> loc(#loc59)
+    } -> tensor<1x40x23x40xbf16> loc(#loc325)
+    %208 = xten_nn.subgraph (%arg5 = %207: tensor<1x40x23x40xbf16>, %arg6 = %121: tensor<120x40x1x1xbf16>, %arg7 = %120: tensor<120xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_76",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 24, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 40, 2, 32]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<[0, 24, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[32, 40, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[8, 24, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[120, 40, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[8, 24, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[120, 40, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Relu_77",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 2, 32]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 1, 24]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 12348 : ui64, ofm = 13884 : ui64, wts = 1162 : ui64},
+        computation_cycles = 12977 : ui64,
+        cycle_count = 13884 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x40x23x40xbf16>, %arg9 = %arg6: tensor<120x40x1x1xbf16>, %arg10 = %arg7: tensor<120xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_76",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[120, 40, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Relu_77",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true,
+          NonNegativeOut = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 1 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 64 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 2 : ui8,
+          config.ifm_sv_width.size = 32 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 0.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 0.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 1 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 32 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 1965 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x120x23x40xbf16> loc(#loc61)
+        xten_nn.output %465 : tensor<1x120x23x40xbf16> loc(#loc61)
+      } -> tensor<1x120x23x40xbf16> loc(#loc326)
+      xten_nn.output %464 : tensor<1x120x23x40xbf16> loc(#loc326)
+    } -> tensor<1x120x23x40xbf16> loc(#loc326)
+    %209 = xten_nn.subgraph (%arg5 = %208: tensor<1x120x23x40xbf16>, %arg6 = %119: tensor<120x1x5x5xbf16>, %arg7 = %118: tensor<120xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_78",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 10, 12]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 1, 24]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "CMHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 3]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[8, 1, 5, 5]> : vector<4xindex>,
+          l2_extend_end = dense<[8, 0, 0, 3]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[120, 1, 5, 5]> : vector<4xindex>,
+          l3_extend_end = dense<[8, 0, 0, 3]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[120, 1, 5, 5]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Relu_79",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 6, 8]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 38600 : ui64, ofm = 7880 : ui64, wts = 744 : ui64},
+        computation_cycles = 22053 : ui64,
+        cycle_count = 38600 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 4, 3, 0]> : vector<4xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x120x23x40xbf16>, %arg9 = %arg6: tensor<120x1x5x5xbf16>, %arg10 = %arg7: tensor<120xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[2, 2], [2, 2]],
+        LayerName = "Conv_78",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "CMHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[120, 1, 5, 5]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Relu_79",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "DepthwiseConv2dBf16",
+        Traits = {
+          NonNegativeOut = true
+        },
+        With = {
+          config.act = 1 : ui8,
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.ifm_sv_depth.size = 8 : ui8,
+          config.ifm_sv_height.size = 10 : ui8,
+          config.ifm_sv_width.size = 12 : ui8,
+          config.kernel_height = 5 : ui8,
+          config.kernel_width = 5 : ui8,
+          config.stride = 1 : ui8,
+          data_io.ifm.dimensions.batch.padding = 0 : ui8,
+          data_io.ifm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.batch.padding = 0 : ui8,
+          data_io.ofm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.width.padding = 0 : ui8
+        },
+        estimation = {
+          compute_cycles = 955 : ui64,
+          startup_cycles = 30 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x120x23x40xbf16> loc(#loc63)
+        xten_nn.output %465 : tensor<1x120x23x40xbf16> loc(#loc63)
+      } -> tensor<1x120x23x40xbf16> loc(#loc327)
+      xten_nn.output %464 : tensor<1x120x23x40xbf16> loc(#loc327)
+    } -> tensor<1x120x23x40xbf16> loc(#loc327)
+    %210 = xten_nn.subgraph (%arg5 = %209: tensor<1x120x23x40xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#18",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#19",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 1, 920]> : vector<4xindex>
+        }
+      ],
+      Specializes = "Transpose4dAdf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.dim_0 = 23 : ui32,
+        config.dim_1 = 15 : ui32,
+        config.dim_2 = 40 : ui32,
+        config.dim_3 = 8 : ui32,
+        config.dtype = "bfloat16",
+        config.perm = 6 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x120x1x920xbf16> loc(#loc64)
+      xten_nn.output %464 : tensor<1x120x1x920xbf16> loc(#loc64)
+    } -> tensor<1x120x1x920xbf16> loc(#loc64)
+    %211 = xten_nn.subgraph (%arg5 = %210: tensor<1x120x1x920xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#20",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 1, 64]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 1, 920]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 1, 920]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#21",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 61590 : ui64, ofm = 3990 : ui64},
+        computation_cycles = 66253 : ui64,
+        cycle_count = 66253 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x120x1x920xbf16>)  attributes {
+        LayerName = "Generated-#20",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 1, 920]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Generated-#21",
+        PadValue = 0.000000e+00 : bf16,
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ReduceMeanC8Bf16",
+        Traits = {
+          Reduce = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.full_channel = 120 : ui32,
+          config.full_height = 1 : ui32,
+          config.full_width = 920 : ui32,
+          config.reduce_dim = "W",
+          config.sv_channel = 32 : ui32,
+          config.sv_height = 1 : ui32,
+          config.sv_width = 64 : ui32
+        },
+        estimation = {
+          compute_cycles = 2337 : ui64,
+          startup_cycles = 190 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x120x1x1xbf16> loc(#loc64)
+        xten_nn.output %465 : tensor<1x120x1x1xbf16> loc(#loc64)
+      } -> tensor<1x120x1x1xbf16> loc(#loc64)
+      xten_nn.output %464 : tensor<1x120x1x1xbf16> loc(#loc64)
+    } -> tensor<1x120x1x1xbf16> loc(#loc64)
+    %212 = xten_nn.subgraph (%arg5 = %211: tensor<1x120x1x1xbf16>, %arg6 = %117: tensor<32x120x1x1xbf16>, %arg7 = %116: tensor<32xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_81",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 15]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[16, 120, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[32, 0, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[32, 120, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[32, 0, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[32, 120, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Relu_82",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 15]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 63]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 970 : ui64, ofm = 778 : ui64, wts = 1034 : ui64},
+        computation_cycles = 1498 : ui64,
+        cycle_count = 1498 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[3, 1, 2, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x120x1x1xbf16>, %arg9 = %arg6: tensor<32x120x1x1xbf16>, %arg10 = %arg7: tensor<32xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_81",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[32, 120, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Relu_82",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true,
+          NonNegativeOut = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 1 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 12 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 120 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 16 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 0.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 0.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 1 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 16 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 16 : ui8
+        },
+        estimation = {
+          compute_cycles = 1018 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x32x1x1xbf16> loc(#loc66)
+        xten_nn.output %465 : tensor<1x32x1x1xbf16> loc(#loc66)
+      } -> tensor<1x32x1x1xbf16> loc(#loc328)
+      xten_nn.output %464 : tensor<1x32x1x1xbf16> loc(#loc328)
+    } -> tensor<1x32x1x1xbf16> loc(#loc328)
+    %213 = xten_nn.subgraph (%arg5 = %212: tensor<1x32x1x1xbf16>, %arg6 = %115: tensor<120x32x1x1xbf16>, %arg7 = %114: tensor<120xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_83",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 32, 0, 7]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 63]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[32, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[8, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[120, 32, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[8, 32, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[120, 32, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_83",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 7]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 31]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 266 : ui64, ofm = 650 : ui64, wts = 1162 : ui64},
+        computation_cycles = 1233 : ui64,
+        cycle_count = 1233 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[3, 1, 2, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x32x1x1xbf16>, %arg9 = %arg6: tensor<120x32x1x1xbf16>, %arg10 = %arg7: tensor<120xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_83",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[120, 32, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_83",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 12 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 64 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 8 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 1 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 32 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 8 : ui8
+        },
+        estimation = {
+          compute_cycles = 753 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x120x1x1xbf16> loc(#loc67)
+        xten_nn.output %465 : tensor<1x120x1x1xbf16> loc(#loc67)
+      } -> tensor<1x120x1x1xbf16> loc(#loc67)
+      xten_nn.output %464 : tensor<1x120x1x1xbf16> loc(#loc67)
+    } -> tensor<1x120x1x1xbf16> loc(#loc67)
+    %214 = xten_nn.subgraph (%arg5 = %213: tensor<1x120x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_85",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 11, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 31]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_85",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 11, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 47, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 778 : ui64, ofm = 394 : ui64},
+        computation_cycles = 401 : ui64,
+        cycle_count = 778 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x120x1x1xbf16>)  attributes {
+        LayerName = "Add_85",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_85",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 32 : ui32,
+          config.ifmsv_height = 12 : ui32,
+          config.ifmsv_width = 1 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 35 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x120x1x1xbf16> loc(#loc68)
+        xten_nn.output %465 : tensor<1x120x1x1xbf16> loc(#loc68)
+      } -> tensor<1x120x1x1xbf16> loc(#loc68)
+      xten_nn.output %464 : tensor<1x120x1x1xbf16> loc(#loc68)
+    } -> tensor<1x120x1x1xbf16> loc(#loc68)
+    %215 = xten_nn.subgraph (%arg5 = %214: tensor<1x120x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_88",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 7, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 47, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_88",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 7, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 31, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 522 : ui64, ofm = 266 : ui64},
+        computation_cycles = 395 : ui64,
+        cycle_count = 522 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x120x1x1xbf16>)  attributes {
+        LayerName = "Clip_88",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_88",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 32 : ui32,
+          config.ifmsv_height = 8 : ui32,
+          config.ifmsv_width = 1 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 35 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x120x1x1xbf16> loc(#loc69)
+        xten_nn.output %465 : tensor<1x120x1x1xbf16> loc(#loc69)
+      } -> tensor<1x120x1x1xbf16> loc(#loc69)
+      xten_nn.output %464 : tensor<1x120x1x1xbf16> loc(#loc69)
+    } -> tensor<1x120x1x1xbf16> loc(#loc69)
+    %216 = xten_nn.subgraph (%arg5 = %215: tensor<1x120x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_90",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 15, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 31, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_90",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 15, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 63, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 1034 : ui64, ofm = 522 : ui64},
+        computation_cycles = 409 : ui64,
+        cycle_count = 1034 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x120x1x1xbf16>)  attributes {
+        LayerName = "Div_90",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_90",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 32 : ui32,
+          config.ifmsv_height = 16 : ui32,
+          config.ifmsv_width = 1 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 43 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x120x1x1xbf16> loc(#loc70)
+        xten_nn.output %465 : tensor<1x120x1x1xbf16> loc(#loc70)
+      } -> tensor<1x120x1x1xbf16> loc(#loc70)
+      xten_nn.output %464 : tensor<1x120x1x1xbf16> loc(#loc70)
+    } -> tensor<1x120x1x1xbf16> loc(#loc70)
+    %217 = xten_nn.subgraph (%arg5 = %216: tensor<1x120x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#22",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#23",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+        }
+      ],
+      Specializes = "TileAdf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.dtype = "bfloat16",
+        config.i_dim_c = 120 : ui32,
+        config.i_dim_h = 1 : ui32,
+        config.i_dim_n = 1 : ui32,
+        config.i_dim_w = 1 : ui32,
+        config.rep_dim_c = 1 : ui32,
+        config.rep_dim_h = 23 : ui32,
+        config.rep_dim_w = 40 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x120x23x40xbf16> loc(#loc71)
+      xten_nn.output %464 : tensor<1x120x23x40xbf16> loc(#loc71)
+    } -> tensor<1x120x23x40xbf16> loc(#loc71)
+    %218 = xten_nn.subgraph (%arg5 = %217: tensor<1x120x23x40xbf16>, %arg6 = %209: tensor<1x120x23x40xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_91",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 6, 10]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 6, 10]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_91",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 6, 10]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 15440 : ui64, ifm2 = 15440 : ui64, ofm = 7760 : ui64},
+        computation_cycles = 1656 : ui64,
+        cycle_count = 15440 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x120x23x40xbf16>, %arg8 = %arg6: tensor<1x120x23x40xbf16>)  attributes {
+        LayerName = "Mul_91",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_91",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 6 : ui32,
+          config.ifmsv_width = 10 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x120x23x40xbf16> loc(#loc71)
+        xten_nn.output %465 : tensor<1x120x23x40xbf16> loc(#loc71)
+      } -> tensor<1x120x23x40xbf16> loc(#loc71)
+      xten_nn.output %464 : tensor<1x120x23x40xbf16> loc(#loc71)
+    } -> tensor<1x120x23x40xbf16> loc(#loc71)
+    %219 = xten_nn.subgraph (%arg5 = %218: tensor<1x120x23x40xbf16>, %arg6 = %113: tensor<40x120x1x1xbf16>, %arg7 = %112: tensor<40xbf16>, %arg8 = %207: tensor<1x40x23x40xbf16>)  attributes {
+      IfmOperands = [0 : index, 3 : index],
+      LayerName = "Conv_92",
+      OfmShare = 3 : index,
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 64, 1, 40]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[16, 64, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[24, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[40, 120, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[24, 8, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[40, 120, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 1, 40]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_93",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 1, 40]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 15480 : ui64, ifm2 = 7740 : ui64, ofm = 3900 : ui64, wts = 1172 : ui64},
+        computation_cycles = 16811 : ui64,
+        cycle_count = 16811 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg9 = %arg5: tensor<1x120x23x40xbf16>, %arg10 = %arg6: tensor<40x120x1x1xbf16>, %arg11 = %arg7: tensor<40xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_92",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 23, 40]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[40, 120, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_92",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 12 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 64 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 40 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 2 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 16 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 40 : ui8
+        },
+        estimation = {
+          compute_cycles = 2416 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %466 = tensor.empty() : tensor<1x40x23x40xbf16> loc(#loc72)
+        xten_nn.output %466 : tensor<1x40x23x40xbf16> loc(#loc72)
+      } -> tensor<1x40x23x40xbf16> loc(#loc72)
+      %465 = xten_nn.subgraph (%arg9 = %464: tensor<1x40x23x40xbf16>, %arg10 = %arg8: tensor<1x40x23x40xbf16>)  attributes {
+        LayerName = "Add_93",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_93",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.act = 0 : ui8,
+          config.act_type = "LINEAR",
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 40 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 51 : ui64,
+          startup_cycles = 22 : ui64
+        }} {
+        %466 = tensor.empty() : tensor<1x40x23x40xbf16> loc(#loc73)
+        xten_nn.output %466 : tensor<1x40x23x40xbf16> loc(#loc73)
+      } -> tensor<1x40x23x40xbf16> loc(#loc73)
+      xten_nn.output %465 : tensor<1x40x23x40xbf16> loc(#loc73)
+    } -> tensor<1x40x23x40xbf16> loc(#loc329)
+    %220 = xten_nn.subgraph (%arg5 = %219: tensor<1x40x23x40xbf16>, %arg6 = %111: tensor<240x40x1x1xbf16>, %arg7 = %110: tensor<240xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_94",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 24, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 40, 2, 32]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<[0, 24, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[32, 40, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[16, 24, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[240, 40, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[16, 24, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[240, 40, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_94",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 2, 32]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 1, 24]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 12348 : ui64, ofm = 27768 : ui64, wts = 2324 : ui64},
+        computation_cycles = 25589 : ui64,
+        cycle_count = 27768 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x40x23x40xbf16>, %arg9 = %arg6: tensor<240x40x1x1xbf16>, %arg10 = %arg7: tensor<240xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_94",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[240, 40, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_94",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 64 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 2 : ui8,
+          config.ifm_sv_width.size = 32 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 1 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 32 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 1965 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x240x23x40xbf16> loc(#loc74)
+        xten_nn.output %465 : tensor<1x240x23x40xbf16> loc(#loc74)
+      } -> tensor<1x240x23x40xbf16> loc(#loc74)
+      xten_nn.output %464 : tensor<1x240x23x40xbf16> loc(#loc74)
+    } -> tensor<1x240x23x40xbf16> loc(#loc74)
+    %221 = xten_nn.subgraph (%arg5 = %220: tensor<1x240x23x40xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_96",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 6, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 1, 24]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_96",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 6, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 30800 : ui64, ofm = 15440 : ui64},
+        computation_cycles = 2373 : ui64,
+        cycle_count = 30800 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x240x23x40xbf16>)  attributes {
+        LayerName = "Add_96",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_96",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 6 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 131 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x240x23x40xbf16> loc(#loc75)
+        xten_nn.output %465 : tensor<1x240x23x40xbf16> loc(#loc75)
+      } -> tensor<1x240x23x40xbf16> loc(#loc75)
+      xten_nn.output %464 : tensor<1x240x23x40xbf16> loc(#loc75)
+    } -> tensor<1x240x23x40xbf16> loc(#loc75)
+    %222 = xten_nn.subgraph (%arg5 = %221: tensor<1x240x23x40xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_99",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 6, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_99",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 6, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 30800 : ui64, ofm = 15440 : ui64},
+        computation_cycles = 2431 : ui64,
+        cycle_count = 30800 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x240x23x40xbf16>)  attributes {
+        LayerName = "Clip_99",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_99",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 6 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 139 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x240x23x40xbf16> loc(#loc76)
+        xten_nn.output %465 : tensor<1x240x23x40xbf16> loc(#loc76)
+      } -> tensor<1x240x23x40xbf16> loc(#loc76)
+      xten_nn.output %464 : tensor<1x240x23x40xbf16> loc(#loc76)
+    } -> tensor<1x240x23x40xbf16> loc(#loc76)
+    %223 = xten_nn.subgraph (%arg5 = %222: tensor<1x240x23x40xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_101",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 6, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_101",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 6, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 30800 : ui64, ofm = 15440 : ui64},
+        computation_cycles = 2373 : ui64,
+        cycle_count = 30800 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x240x23x40xbf16>)  attributes {
+        LayerName = "Div_101",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_101",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 6 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 131 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x240x23x40xbf16> loc(#loc77)
+        xten_nn.output %465 : tensor<1x240x23x40xbf16> loc(#loc77)
+      } -> tensor<1x240x23x40xbf16> loc(#loc77)
+      xten_nn.output %464 : tensor<1x240x23x40xbf16> loc(#loc77)
+    } -> tensor<1x240x23x40xbf16> loc(#loc77)
+    %224 = xten_nn.subgraph (%arg5 = %220: tensor<1x240x23x40xbf16>, %arg6 = %223: tensor<1x240x23x40xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_102",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_force_single_buffering = true,
+          l2_tile_count = dense<[1, 240, 12, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_force_single_buffering = true,
+          l2_tile_count = dense<[1, 240, 12, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_102",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_force_single_buffering = true,
+          l2_tile_count = dense<[1, 240, 12, 40]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 0, 1, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 30880 : ui64, ifm2 = 30880 : ui64, ofm = 15520 : ui64},
+        computation_cycles = 3104 : ui64,
+        cycle_count = 61760 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x240x23x40xbf16>, %arg8 = %arg6: tensor<1x240x23x40xbf16>)  attributes {
+        LayerName = "Mul_102",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_102",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x240x23x40xbf16> loc(#loc78)
+        xten_nn.output %465 : tensor<1x240x23x40xbf16> loc(#loc78)
+      } -> tensor<1x240x23x40xbf16> loc(#loc78)
+      xten_nn.output %464 : tensor<1x240x23x40xbf16> loc(#loc78)
+    } -> tensor<1x240x23x40xbf16> loc(#loc78)
+    %225 = xten_nn.subgraph (%arg5 = %224: tensor<1x240x23x40xbf16>)  attributes {
+      LayerName = "Generated-#64",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<[0, 0, 1, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#65",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>
+        }
+      ],
+      Specializes = "BufferUnpadAdf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.dim_0 = 24 : ui32,
+        config.dim_0_unpadded = 23 : ui32,
+        config.dim_1 = 30 : ui32,
+        config.dim_1_unpadded = 30 : ui32,
+        config.dim_2 = 40 : ui32,
+        config.dim_2_unpadded = 40 : ui32,
+        config.dim_3 = 8 : ui32,
+        config.dim_3_unpadded = 8 : ui32,
+        config.dtype = "bfloat16"
+      }} {
+      xten_nn.output %arg5 : tensor<1x240x23x40xbf16> loc(#loc10)
+    } -> tensor<1x240x23x40xbf16> loc(#loc10)
+    %226 = xten_nn.subgraph (%arg5 = %225: tensor<1x240x23x40xbf16>, %arg6 = %109: tensor<240x1x3x3xbf16>, %arg7 = %108: tensor<240xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_103",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 2]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 10, 10]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "CMHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 1]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[8, 1, 3, 3]> : vector<4xindex>,
+          l2_extend_end = dense<[16, 0, 0, 1]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[240, 1, 3, 3]> : vector<4xindex>,
+          l3_extend_end = dense<[16, 0, 0, 1]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[240, 1, 3, 3]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_103",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 4, 4]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 4, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 77200 : ui64, ofm = 5520 : ui64, wts = 592 : ui64},
+        computation_cycles = 20853 : ui64,
+        cycle_count = 77200 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 4, 3, 0]> : vector<4xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x240x23x40xbf16>, %arg9 = %arg6: tensor<240x1x3x3xbf16>, %arg10 = %arg7: tensor<240xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[1, 1], [1, 0]],
+        LayerName = "Conv_103",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 240, 23, 40]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "CMHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[240, 1, 3, 3]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_103",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "DepthwiseConv2dBf16",
+        With = {
+          config.act = 0 : ui8,
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.ifm_sv_depth.size = 8 : ui8,
+          config.ifm_sv_height.size = 10 : ui8,
+          config.ifm_sv_width.size = 10 : ui8,
+          config.kernel_height = 3 : ui8,
+          config.kernel_width = 3 : ui8,
+          config.stride = 2 : ui8,
+          data_io.ifm.dimensions.batch.padding = 0 : ui8,
+          data_io.ifm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.batch.padding = 0 : ui8,
+          data_io.ofm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.width.padding = 0 : ui8
+        },
+        estimation = {
+          compute_cycles = 379 : ui64,
+          startup_cycles = 30 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x240x12x20xbf16> loc(#loc79)
+        xten_nn.output %465 : tensor<1x240x12x20xbf16> loc(#loc79)
+      } -> tensor<1x240x12x20xbf16> loc(#loc79)
+      xten_nn.output %464 : tensor<1x240x12x20xbf16> loc(#loc79)
+    } -> tensor<1x240x12x20xbf16> loc(#loc79)
+    %227 = xten_nn.subgraph (%arg5 = %226: tensor<1x240x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_105",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 4, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_105",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 7700 : ui64, ofm = 3860 : ui64},
+        computation_cycles = 765 : ui64,
+        cycle_count = 7700 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x240x12x20xbf16>)  attributes {
+        LayerName = "Add_105",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_105",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 32 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 131 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x240x12x20xbf16> loc(#loc80)
+        xten_nn.output %465 : tensor<1x240x12x20xbf16> loc(#loc80)
+      } -> tensor<1x240x12x20xbf16> loc(#loc80)
+      xten_nn.output %464 : tensor<1x240x12x20xbf16> loc(#loc80)
+    } -> tensor<1x240x12x20xbf16> loc(#loc80)
+    %228 = xten_nn.subgraph (%arg5 = %227: tensor<1x240x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_108",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_108",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 7700 : ui64, ofm = 3860 : ui64},
+        computation_cycles = 775 : ui64,
+        cycle_count = 7700 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x240x12x20xbf16>)  attributes {
+        LayerName = "Clip_108",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_108",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 32 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 139 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x240x12x20xbf16> loc(#loc81)
+        xten_nn.output %465 : tensor<1x240x12x20xbf16> loc(#loc81)
+      } -> tensor<1x240x12x20xbf16> loc(#loc81)
+      xten_nn.output %464 : tensor<1x240x12x20xbf16> loc(#loc81)
+    } -> tensor<1x240x12x20xbf16> loc(#loc81)
+    %229 = xten_nn.subgraph (%arg5 = %228: tensor<1x240x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_110",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_110",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 7700 : ui64, ofm = 3860 : ui64},
+        computation_cycles = 765 : ui64,
+        cycle_count = 7700 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x240x12x20xbf16>)  attributes {
+        LayerName = "Div_110",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_110",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 32 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 131 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x240x12x20xbf16> loc(#loc82)
+        xten_nn.output %465 : tensor<1x240x12x20xbf16> loc(#loc82)
+      } -> tensor<1x240x12x20xbf16> loc(#loc82)
+      xten_nn.output %464 : tensor<1x240x12x20xbf16> loc(#loc82)
+    } -> tensor<1x240x12x20xbf16> loc(#loc82)
+    %230 = xten_nn.subgraph (%arg5 = %226: tensor<1x240x12x20xbf16>, %arg6 = %229: tensor<1x240x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_111",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 4, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_111",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 7720 : ui64, ifm2 = 7720 : ui64, ofm = 3880 : ui64},
+        computation_cycles = 932 : ui64,
+        cycle_count = 7720 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x240x12x20xbf16>, %arg8 = %arg6: tensor<1x240x12x20xbf16>)  attributes {
+        LayerName = "Mul_111",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_111",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x240x12x20xbf16> loc(#loc83)
+        xten_nn.output %465 : tensor<1x240x12x20xbf16> loc(#loc83)
+      } -> tensor<1x240x12x20xbf16> loc(#loc83)
+      xten_nn.output %464 : tensor<1x240x12x20xbf16> loc(#loc83)
+    } -> tensor<1x240x12x20xbf16> loc(#loc83)
+    %231 = xten_nn.subgraph (%arg5 = %230: tensor<1x240x12x20xbf16>, %arg6 = %107: tensor<80x240x1x1xbf16>, %arg7 = %106: tensor<80xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_112",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[24, 80, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[16, 0, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[80, 240, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[16, 0, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[80, 240, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_112",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 24, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 11610 : ui64, ofm = 3102 : ui64, wts = 3198 : ui64},
+        computation_cycles = 12272 : ui64,
+        cycle_count = 12272 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x240x12x20xbf16>, %arg9 = %arg6: tensor<80x240x1x1xbf16>, %arg10 = %arg7: tensor<80xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_112",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 240, 12, 20]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[80, 240, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_112",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 80 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 32 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 3 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 24 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 3558 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x80x12x20xbf16> loc(#loc84)
+        xten_nn.output %465 : tensor<1x80x12x20xbf16> loc(#loc84)
+      } -> tensor<1x80x12x20xbf16> loc(#loc84)
+      xten_nn.output %464 : tensor<1x80x12x20xbf16> loc(#loc84)
+    } -> tensor<1x80x12x20xbf16> loc(#loc84)
+    %232 = xten_nn.subgraph (%arg5 = %231: tensor<1x80x12x20xbf16>, %arg6 = %105: tensor<200x80x1x1xbf16>, %arg7 = %104: tensor<200xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_113",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[32, 80, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[56, 0, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[200, 80, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[56, 0, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[200, 80, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_113",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 56, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 3870 : ui64, ofm = 7740 : ui64, wts = 2836 : ui64},
+        computation_cycles = 9533 : ui64,
+        cycle_count = 9533 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x80x12x20xbf16>, %arg9 = %arg6: tensor<200x80x1x1xbf16>, %arg10 = %arg7: tensor<200xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_113",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[200, 80, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_113",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 80 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 32 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 1 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 32 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 1391 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x200x12x20xbf16> loc(#loc85)
+        xten_nn.output %465 : tensor<1x200x12x20xbf16> loc(#loc85)
+      } -> tensor<1x200x12x20xbf16> loc(#loc85)
+      xten_nn.output %464 : tensor<1x200x12x20xbf16> loc(#loc85)
+    } -> tensor<1x200x12x20xbf16> loc(#loc85)
+    %233 = xten_nn.subgraph (%arg5 = %232: tensor<1x200x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_115",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 56, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_115",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 56, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 7700 : ui64, ofm = 3860 : ui64},
+        computation_cycles = 765 : ui64,
+        cycle_count = 7700 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x200x12x20xbf16>)  attributes {
+        LayerName = "Add_115",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_115",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 32 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 131 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x200x12x20xbf16> loc(#loc86)
+        xten_nn.output %465 : tensor<1x200x12x20xbf16> loc(#loc86)
+      } -> tensor<1x200x12x20xbf16> loc(#loc86)
+      xten_nn.output %464 : tensor<1x200x12x20xbf16> loc(#loc86)
+    } -> tensor<1x200x12x20xbf16> loc(#loc86)
+    %234 = xten_nn.subgraph (%arg5 = %233: tensor<1x200x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_118",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 56, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_118",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 56, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 7700 : ui64, ofm = 3860 : ui64},
+        computation_cycles = 775 : ui64,
+        cycle_count = 7700 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x200x12x20xbf16>)  attributes {
+        LayerName = "Clip_118",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_118",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 32 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 139 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x200x12x20xbf16> loc(#loc87)
+        xten_nn.output %465 : tensor<1x200x12x20xbf16> loc(#loc87)
+      } -> tensor<1x200x12x20xbf16> loc(#loc87)
+      xten_nn.output %464 : tensor<1x200x12x20xbf16> loc(#loc87)
+    } -> tensor<1x200x12x20xbf16> loc(#loc87)
+    %235 = xten_nn.subgraph (%arg5 = %234: tensor<1x200x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_120",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 56, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_120",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 56, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 7700 : ui64, ofm = 3860 : ui64},
+        computation_cycles = 765 : ui64,
+        cycle_count = 7700 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x200x12x20xbf16>)  attributes {
+        LayerName = "Div_120",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_120",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 32 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 131 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x200x12x20xbf16> loc(#loc88)
+        xten_nn.output %465 : tensor<1x200x12x20xbf16> loc(#loc88)
+      } -> tensor<1x200x12x20xbf16> loc(#loc88)
+      xten_nn.output %464 : tensor<1x200x12x20xbf16> loc(#loc88)
+    } -> tensor<1x200x12x20xbf16> loc(#loc88)
+    %236 = xten_nn.subgraph (%arg5 = %232: tensor<1x200x12x20xbf16>, %arg6 = %235: tensor<1x200x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_121",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 56, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 56, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_121",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 56, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 7720 : ui64, ifm2 = 7720 : ui64, ofm = 3880 : ui64},
+        computation_cycles = 932 : ui64,
+        cycle_count = 7720 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x200x12x20xbf16>, %arg8 = %arg6: tensor<1x200x12x20xbf16>)  attributes {
+        LayerName = "Mul_121",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_121",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x200x12x20xbf16> loc(#loc89)
+        xten_nn.output %465 : tensor<1x200x12x20xbf16> loc(#loc89)
+      } -> tensor<1x200x12x20xbf16> loc(#loc89)
+      xten_nn.output %464 : tensor<1x200x12x20xbf16> loc(#loc89)
+    } -> tensor<1x200x12x20xbf16> loc(#loc89)
+    %237 = xten_nn.subgraph (%arg5 = %236: tensor<1x200x12x20xbf16>, %arg6 = %103: tensor<200x1x3x3xbf16>, %arg7 = %102: tensor<200xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_122",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 8]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 6, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 56, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "CMHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 1]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[8, 1, 3, 3]> : vector<4xindex>,
+          l2_extend_end = dense<[24, 0, 0, 1]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[200, 1, 3, 3]> : vector<4xindex>,
+          l3_extend_end = dense<[24, 0, 0, 1]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[200, 1, 3, 3]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_122",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 4]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 4, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 4, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 18886 : ui64, ofm = 5446 : ui64, wts = 518 : ui64},
+        computation_cycles = 8865 : ui64,
+        cycle_count = 18886 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 4, 3, 0]> : vector<4xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x200x12x20xbf16>, %arg9 = %arg6: tensor<200x1x3x3xbf16>, %arg10 = %arg7: tensor<200xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[1, 1], [1, 1]],
+        LayerName = "Conv_122",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "CMHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[200, 1, 3, 3]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_122",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "DepthwiseConv2dBf16",
+        With = {
+          config.act = 0 : ui8,
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.ifm_sv_depth.size = 8 : ui8,
+          config.ifm_sv_height.size = 6 : ui8,
+          config.ifm_sv_width.size = 26 : ui8,
+          config.kernel_height = 3 : ui8,
+          config.kernel_width = 3 : ui8,
+          config.stride = 1 : ui8,
+          data_io.ifm.dimensions.batch.padding = 0 : ui8,
+          data_io.ifm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.batch.padding = 0 : ui8,
+          data_io.ofm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.width.padding = 0 : ui8
+        },
+        estimation = {
+          compute_cycles = 1099 : ui64,
+          startup_cycles = 30 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x200x12x20xbf16> loc(#loc90)
+        xten_nn.output %465 : tensor<1x200x12x20xbf16> loc(#loc90)
+      } -> tensor<1x200x12x20xbf16> loc(#loc90)
+      xten_nn.output %464 : tensor<1x200x12x20xbf16> loc(#loc90)
+    } -> tensor<1x200x12x20xbf16> loc(#loc90)
+    %238 = xten_nn.subgraph (%arg5 = %237: tensor<1x200x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_124",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 4, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_124",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 56, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 7700 : ui64, ofm = 3860 : ui64},
+        computation_cycles = 765 : ui64,
+        cycle_count = 7700 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x200x12x20xbf16>)  attributes {
+        LayerName = "Add_124",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_124",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 32 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 131 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x200x12x20xbf16> loc(#loc91)
+        xten_nn.output %465 : tensor<1x200x12x20xbf16> loc(#loc91)
+      } -> tensor<1x200x12x20xbf16> loc(#loc91)
+      xten_nn.output %464 : tensor<1x200x12x20xbf16> loc(#loc91)
+    } -> tensor<1x200x12x20xbf16> loc(#loc91)
+    %239 = xten_nn.subgraph (%arg5 = %238: tensor<1x200x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_127",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 56, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_127",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 56, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 7700 : ui64, ofm = 3860 : ui64},
+        computation_cycles = 775 : ui64,
+        cycle_count = 7700 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x200x12x20xbf16>)  attributes {
+        LayerName = "Clip_127",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_127",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 32 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 139 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x200x12x20xbf16> loc(#loc92)
+        xten_nn.output %465 : tensor<1x200x12x20xbf16> loc(#loc92)
+      } -> tensor<1x200x12x20xbf16> loc(#loc92)
+      xten_nn.output %464 : tensor<1x200x12x20xbf16> loc(#loc92)
+    } -> tensor<1x200x12x20xbf16> loc(#loc92)
+    %240 = xten_nn.subgraph (%arg5 = %239: tensor<1x200x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_129",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 56, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_129",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 56, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 7700 : ui64, ofm = 3860 : ui64},
+        computation_cycles = 765 : ui64,
+        cycle_count = 7700 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x200x12x20xbf16>)  attributes {
+        LayerName = "Div_129",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_129",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 32 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 131 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x200x12x20xbf16> loc(#loc93)
+        xten_nn.output %465 : tensor<1x200x12x20xbf16> loc(#loc93)
+      } -> tensor<1x200x12x20xbf16> loc(#loc93)
+      xten_nn.output %464 : tensor<1x200x12x20xbf16> loc(#loc93)
+    } -> tensor<1x200x12x20xbf16> loc(#loc93)
+    %241 = xten_nn.subgraph (%arg5 = %237: tensor<1x200x12x20xbf16>, %arg6 = %240: tensor<1x200x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_130",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 4, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 56, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_130",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 56, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 7720 : ui64, ifm2 = 7720 : ui64, ofm = 3880 : ui64},
+        computation_cycles = 932 : ui64,
+        cycle_count = 7720 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x200x12x20xbf16>, %arg8 = %arg6: tensor<1x200x12x20xbf16>)  attributes {
+        LayerName = "Mul_130",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_130",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x200x12x20xbf16> loc(#loc94)
+        xten_nn.output %465 : tensor<1x200x12x20xbf16> loc(#loc94)
+      } -> tensor<1x200x12x20xbf16> loc(#loc94)
+      xten_nn.output %464 : tensor<1x200x12x20xbf16> loc(#loc94)
+    } -> tensor<1x200x12x20xbf16> loc(#loc94)
+    %242 = xten_nn.subgraph (%arg5 = %241: tensor<1x200x12x20xbf16>, %arg6 = %101: tensor<80x200x1x1xbf16>, %arg7 = %100: tensor<80xbf16>, %arg8 = %231: tensor<1x80x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 3 : index],
+      LayerName = "Conv_131",
+      OfmShare = 3 : index,
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 104, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 56, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[24, 104, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[16, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[80, 200, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[16, 8, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[80, 200, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 24, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_132",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 24, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 10044 : ui64, ifm2 = 4638 : ui64, ofm = 2334 : ui64, wts = 2708 : ui64},
+        computation_cycles = 9960 : ui64,
+        cycle_count = 10044 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg9 = %arg5: tensor<1x200x12x20xbf16>, %arg10 = %arg6: tensor<80x200x1x1xbf16>, %arg11 = %arg7: tensor<80xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_131",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 200, 12, 20]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[80, 200, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_131",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 104 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 32 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 2 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 24 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 2858 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %466 = tensor.empty() : tensor<1x80x12x20xbf16> loc(#loc95)
+        xten_nn.output %466 : tensor<1x80x12x20xbf16> loc(#loc95)
+      } -> tensor<1x80x12x20xbf16> loc(#loc95)
+      %465 = xten_nn.subgraph (%arg9 = %464: tensor<1x80x12x20xbf16>, %arg10 = %arg8: tensor<1x80x12x20xbf16>)  attributes {
+        LayerName = "Add_132",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_132",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.act = 0 : ui8,
+          config.act_type = "LINEAR",
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 24 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 32 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 59 : ui64,
+          startup_cycles = 22 : ui64
+        }} {
+        %466 = tensor.empty() : tensor<1x80x12x20xbf16> loc(#loc96)
+        xten_nn.output %466 : tensor<1x80x12x20xbf16> loc(#loc96)
+      } -> tensor<1x80x12x20xbf16> loc(#loc96)
+      xten_nn.output %465 : tensor<1x80x12x20xbf16> loc(#loc96)
+    } -> tensor<1x80x12x20xbf16> loc(#loc330)
+    %243 = xten_nn.subgraph (%arg5 = %242: tensor<1x80x12x20xbf16>, %arg6 = %99: tensor<184x80x1x1xbf16>, %arg7 = %98: tensor<184xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_133",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 80, 3, 8]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[48, 80, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[8, 0, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[184, 80, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[8, 0, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[184, 80, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_133",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 48, 3, 8]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 2910 : ui64, ofm = 7326 : ui64, wts = 2122 : ui64},
+        computation_cycles = 7180 : ui64,
+        cycle_count = 7326 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x80x12x20xbf16>, %arg9 = %arg6: tensor<184x80x1x1xbf16>, %arg10 = %arg7: tensor<184xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_133",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[184, 80, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_133",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 12 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 80 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 3 : ui8,
+          config.ifm_sv_width.size = 8 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 1 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 48 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 8 : ui8
+        },
+        estimation = {
+          compute_cycles = 2142 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x184x12x20xbf16> loc(#loc97)
+        xten_nn.output %465 : tensor<1x184x12x20xbf16> loc(#loc97)
+      } -> tensor<1x184x12x20xbf16> loc(#loc97)
+      xten_nn.output %464 : tensor<1x184x12x20xbf16> loc(#loc97)
+    } -> tensor<1x184x12x20xbf16> loc(#loc97)
+    %244 = xten_nn.subgraph (%arg5 = %243: tensor<1x184x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_135",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_135",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 5790 : ui64, ofm = 2910 : ui64},
+        computation_cycles = 853 : ui64,
+        cycle_count = 5790 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x184x12x20xbf16>)  attributes {
+        LayerName = "Add_135",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_135",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 71 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x184x12x20xbf16> loc(#loc98)
+        xten_nn.output %465 : tensor<1x184x12x20xbf16> loc(#loc98)
+      } -> tensor<1x184x12x20xbf16> loc(#loc98)
+      xten_nn.output %464 : tensor<1x184x12x20xbf16> loc(#loc98)
+    } -> tensor<1x184x12x20xbf16> loc(#loc98)
+    %245 = xten_nn.subgraph (%arg5 = %244: tensor<1x184x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_138",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_138",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 5790 : ui64, ofm = 2910 : ui64},
+        computation_cycles = 871 : ui64,
+        cycle_count = 5790 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x184x12x20xbf16>)  attributes {
+        LayerName = "Clip_138",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_138",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 79 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x184x12x20xbf16> loc(#loc99)
+        xten_nn.output %465 : tensor<1x184x12x20xbf16> loc(#loc99)
+      } -> tensor<1x184x12x20xbf16> loc(#loc99)
+      xten_nn.output %464 : tensor<1x184x12x20xbf16> loc(#loc99)
+    } -> tensor<1x184x12x20xbf16> loc(#loc99)
+    %246 = xten_nn.subgraph (%arg5 = %245: tensor<1x184x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_140",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_140",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 5790 : ui64, ofm = 2910 : ui64},
+        computation_cycles = 853 : ui64,
+        cycle_count = 5790 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x184x12x20xbf16>)  attributes {
+        LayerName = "Div_140",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_140",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 71 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x184x12x20xbf16> loc(#loc100)
+        xten_nn.output %465 : tensor<1x184x12x20xbf16> loc(#loc100)
+      } -> tensor<1x184x12x20xbf16> loc(#loc100)
+      xten_nn.output %464 : tensor<1x184x12x20xbf16> loc(#loc100)
+    } -> tensor<1x184x12x20xbf16> loc(#loc100)
+    %247 = xten_nn.subgraph (%arg5 = %243: tensor<1x184x12x20xbf16>, %arg6 = %246: tensor<1x184x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_141",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_141",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 5790 : ui64, ifm2 = 5790 : ui64, ofm = 2910 : ui64},
+        computation_cycles = 751 : ui64,
+        cycle_count = 5790 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x184x12x20xbf16>, %arg8 = %arg6: tensor<1x184x12x20xbf16>)  attributes {
+        LayerName = "Mul_141",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_141",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x184x12x20xbf16> loc(#loc101)
+        xten_nn.output %465 : tensor<1x184x12x20xbf16> loc(#loc101)
+      } -> tensor<1x184x12x20xbf16> loc(#loc101)
+      xten_nn.output %464 : tensor<1x184x12x20xbf16> loc(#loc101)
+    } -> tensor<1x184x12x20xbf16> loc(#loc101)
+    %248 = xten_nn.subgraph (%arg5 = %247: tensor<1x184x12x20xbf16>, %arg6 = %97: tensor<184x1x3x3xbf16>, %arg7 = %96: tensor<184xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_142",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 8]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 6, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "CMHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 1]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[8, 1, 3, 3]> : vector<4xindex>,
+          l2_extend_end = dense<[8, 0, 0, 1]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[184, 1, 3, 3]> : vector<4xindex>,
+          l3_extend_end = dense<[8, 0, 0, 1]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[184, 1, 3, 3]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_142",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 4]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 4, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 4, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 16188 : ui64, ofm = 4668 : ui64, wts = 444 : ui64},
+        computation_cycles = 7629 : ui64,
+        cycle_count = 16188 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 4, 3, 0]> : vector<4xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x184x12x20xbf16>, %arg9 = %arg6: tensor<184x1x3x3xbf16>, %arg10 = %arg7: tensor<184xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[1, 1], [1, 1]],
+        LayerName = "Conv_142",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "CMHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[184, 1, 3, 3]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_142",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "DepthwiseConv2dBf16",
+        With = {
+          config.act = 0 : ui8,
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.ifm_sv_depth.size = 8 : ui8,
+          config.ifm_sv_height.size = 6 : ui8,
+          config.ifm_sv_width.size = 26 : ui8,
+          config.kernel_height = 3 : ui8,
+          config.kernel_width = 3 : ui8,
+          config.stride = 1 : ui8,
+          data_io.ifm.dimensions.batch.padding = 0 : ui8,
+          data_io.ifm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.batch.padding = 0 : ui8,
+          data_io.ofm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.width.padding = 0 : ui8
+        },
+        estimation = {
+          compute_cycles = 1099 : ui64,
+          startup_cycles = 30 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x184x12x20xbf16> loc(#loc102)
+        xten_nn.output %465 : tensor<1x184x12x20xbf16> loc(#loc102)
+      } -> tensor<1x184x12x20xbf16> loc(#loc102)
+      xten_nn.output %464 : tensor<1x184x12x20xbf16> loc(#loc102)
+    } -> tensor<1x184x12x20xbf16> loc(#loc102)
+    %249 = xten_nn.subgraph (%arg5 = %248: tensor<1x184x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_144",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 4, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_144",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 5790 : ui64, ofm = 2910 : ui64},
+        computation_cycles = 853 : ui64,
+        cycle_count = 5790 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x184x12x20xbf16>)  attributes {
+        LayerName = "Add_144",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_144",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 71 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x184x12x20xbf16> loc(#loc103)
+        xten_nn.output %465 : tensor<1x184x12x20xbf16> loc(#loc103)
+      } -> tensor<1x184x12x20xbf16> loc(#loc103)
+      xten_nn.output %464 : tensor<1x184x12x20xbf16> loc(#loc103)
+    } -> tensor<1x184x12x20xbf16> loc(#loc103)
+    %250 = xten_nn.subgraph (%arg5 = %249: tensor<1x184x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_147",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_147",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 5790 : ui64, ofm = 2910 : ui64},
+        computation_cycles = 871 : ui64,
+        cycle_count = 5790 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x184x12x20xbf16>)  attributes {
+        LayerName = "Clip_147",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_147",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 79 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x184x12x20xbf16> loc(#loc104)
+        xten_nn.output %465 : tensor<1x184x12x20xbf16> loc(#loc104)
+      } -> tensor<1x184x12x20xbf16> loc(#loc104)
+      xten_nn.output %464 : tensor<1x184x12x20xbf16> loc(#loc104)
+    } -> tensor<1x184x12x20xbf16> loc(#loc104)
+    %251 = xten_nn.subgraph (%arg5 = %250: tensor<1x184x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_149",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_149",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 5790 : ui64, ofm = 2910 : ui64},
+        computation_cycles = 853 : ui64,
+        cycle_count = 5790 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x184x12x20xbf16>)  attributes {
+        LayerName = "Div_149",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_149",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 71 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x184x12x20xbf16> loc(#loc105)
+        xten_nn.output %465 : tensor<1x184x12x20xbf16> loc(#loc105)
+      } -> tensor<1x184x12x20xbf16> loc(#loc105)
+      xten_nn.output %464 : tensor<1x184x12x20xbf16> loc(#loc105)
+    } -> tensor<1x184x12x20xbf16> loc(#loc105)
+    %252 = xten_nn.subgraph (%arg5 = %248: tensor<1x184x12x20xbf16>, %arg6 = %251: tensor<1x184x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_150",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 4, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_150",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 5790 : ui64, ifm2 = 5790 : ui64, ofm = 2910 : ui64},
+        computation_cycles = 751 : ui64,
+        cycle_count = 5790 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x184x12x20xbf16>, %arg8 = %arg6: tensor<1x184x12x20xbf16>)  attributes {
+        LayerName = "Mul_150",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_150",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x184x12x20xbf16> loc(#loc106)
+        xten_nn.output %465 : tensor<1x184x12x20xbf16> loc(#loc106)
+      } -> tensor<1x184x12x20xbf16> loc(#loc106)
+      xten_nn.output %464 : tensor<1x184x12x20xbf16> loc(#loc106)
+    } -> tensor<1x184x12x20xbf16> loc(#loc106)
+    %253 = xten_nn.subgraph (%arg5 = %252: tensor<1x184x12x20xbf16>, %arg6 = %95: tensor<80x184x1x1xbf16>, %arg7 = %94: tensor<80xbf16>, %arg8 = %242: tensor<1x80x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 3 : index],
+      LayerName = "Conv_151",
+      OfmShare = 3 : index,
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 96, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[24, 96, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[16, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[80, 184, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[16, 8, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[80, 184, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 24, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_152",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 24, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 9276 : ui64, ifm2 = 4638 : ui64, ofm = 2334 : ui64, wts = 2516 : ui64},
+        computation_cycles = 9474 : ui64,
+        cycle_count = 9474 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg9 = %arg5: tensor<1x184x12x20xbf16>, %arg10 = %arg6: tensor<80x184x1x1xbf16>, %arg11 = %arg7: tensor<80xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_151",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[80, 184, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_151",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 96 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 32 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 2 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 24 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 2696 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %466 = tensor.empty() : tensor<1x80x12x20xbf16> loc(#loc107)
+        xten_nn.output %466 : tensor<1x80x12x20xbf16> loc(#loc107)
+      } -> tensor<1x80x12x20xbf16> loc(#loc107)
+      %465 = xten_nn.subgraph (%arg9 = %464: tensor<1x80x12x20xbf16>, %arg10 = %arg8: tensor<1x80x12x20xbf16>)  attributes {
+        LayerName = "Add_152",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_152",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.act = 0 : ui8,
+          config.act_type = "LINEAR",
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 24 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 32 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 59 : ui64,
+          startup_cycles = 22 : ui64
+        }} {
+        %466 = tensor.empty() : tensor<1x80x12x20xbf16> loc(#loc108)
+        xten_nn.output %466 : tensor<1x80x12x20xbf16> loc(#loc108)
+      } -> tensor<1x80x12x20xbf16> loc(#loc108)
+      xten_nn.output %465 : tensor<1x80x12x20xbf16> loc(#loc108)
+    } -> tensor<1x80x12x20xbf16> loc(#loc331)
+    %254 = xten_nn.subgraph (%arg5 = %253: tensor<1x80x12x20xbf16>, %arg6 = %93: tensor<184x80x1x1xbf16>, %arg7 = %92: tensor<184xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_153",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 80, 3, 8]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[48, 80, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[8, 0, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[184, 80, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[8, 0, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[184, 80, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_153",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 48, 3, 8]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 2910 : ui64, ofm = 7326 : ui64, wts = 2122 : ui64},
+        computation_cycles = 7180 : ui64,
+        cycle_count = 7326 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x80x12x20xbf16>, %arg9 = %arg6: tensor<184x80x1x1xbf16>, %arg10 = %arg7: tensor<184xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_153",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[184, 80, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_153",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 12 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 80 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 3 : ui8,
+          config.ifm_sv_width.size = 8 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 1 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 48 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 8 : ui8
+        },
+        estimation = {
+          compute_cycles = 2142 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x184x12x20xbf16> loc(#loc109)
+        xten_nn.output %465 : tensor<1x184x12x20xbf16> loc(#loc109)
+      } -> tensor<1x184x12x20xbf16> loc(#loc109)
+      xten_nn.output %464 : tensor<1x184x12x20xbf16> loc(#loc109)
+    } -> tensor<1x184x12x20xbf16> loc(#loc109)
+    %255 = xten_nn.subgraph (%arg5 = %254: tensor<1x184x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_155",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_155",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 5790 : ui64, ofm = 2910 : ui64},
+        computation_cycles = 853 : ui64,
+        cycle_count = 5790 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x184x12x20xbf16>)  attributes {
+        LayerName = "Add_155",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_155",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 71 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x184x12x20xbf16> loc(#loc110)
+        xten_nn.output %465 : tensor<1x184x12x20xbf16> loc(#loc110)
+      } -> tensor<1x184x12x20xbf16> loc(#loc110)
+      xten_nn.output %464 : tensor<1x184x12x20xbf16> loc(#loc110)
+    } -> tensor<1x184x12x20xbf16> loc(#loc110)
+    %256 = xten_nn.subgraph (%arg5 = %255: tensor<1x184x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_158",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_158",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 5790 : ui64, ofm = 2910 : ui64},
+        computation_cycles = 871 : ui64,
+        cycle_count = 5790 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x184x12x20xbf16>)  attributes {
+        LayerName = "Clip_158",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_158",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 79 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x184x12x20xbf16> loc(#loc111)
+        xten_nn.output %465 : tensor<1x184x12x20xbf16> loc(#loc111)
+      } -> tensor<1x184x12x20xbf16> loc(#loc111)
+      xten_nn.output %464 : tensor<1x184x12x20xbf16> loc(#loc111)
+    } -> tensor<1x184x12x20xbf16> loc(#loc111)
+    %257 = xten_nn.subgraph (%arg5 = %256: tensor<1x184x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_160",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_160",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 5790 : ui64, ofm = 2910 : ui64},
+        computation_cycles = 853 : ui64,
+        cycle_count = 5790 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x184x12x20xbf16>)  attributes {
+        LayerName = "Div_160",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_160",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 71 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x184x12x20xbf16> loc(#loc112)
+        xten_nn.output %465 : tensor<1x184x12x20xbf16> loc(#loc112)
+      } -> tensor<1x184x12x20xbf16> loc(#loc112)
+      xten_nn.output %464 : tensor<1x184x12x20xbf16> loc(#loc112)
+    } -> tensor<1x184x12x20xbf16> loc(#loc112)
+    %258 = xten_nn.subgraph (%arg5 = %254: tensor<1x184x12x20xbf16>, %arg6 = %257: tensor<1x184x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_161",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_161",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 5790 : ui64, ifm2 = 5790 : ui64, ofm = 2910 : ui64},
+        computation_cycles = 751 : ui64,
+        cycle_count = 5790 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x184x12x20xbf16>, %arg8 = %arg6: tensor<1x184x12x20xbf16>)  attributes {
+        LayerName = "Mul_161",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_161",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x184x12x20xbf16> loc(#loc113)
+        xten_nn.output %465 : tensor<1x184x12x20xbf16> loc(#loc113)
+      } -> tensor<1x184x12x20xbf16> loc(#loc113)
+      xten_nn.output %464 : tensor<1x184x12x20xbf16> loc(#loc113)
+    } -> tensor<1x184x12x20xbf16> loc(#loc113)
+    %259 = xten_nn.subgraph (%arg5 = %258: tensor<1x184x12x20xbf16>, %arg6 = %91: tensor<184x1x3x3xbf16>, %arg7 = %90: tensor<184xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_162",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 8]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 6, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "CMHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 1]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[8, 1, 3, 3]> : vector<4xindex>,
+          l2_extend_end = dense<[8, 0, 0, 1]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[184, 1, 3, 3]> : vector<4xindex>,
+          l3_extend_end = dense<[8, 0, 0, 1]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[184, 1, 3, 3]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_162",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 4]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 4, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 4, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 16188 : ui64, ofm = 4668 : ui64, wts = 444 : ui64},
+        computation_cycles = 7629 : ui64,
+        cycle_count = 16188 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 4, 3, 0]> : vector<4xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x184x12x20xbf16>, %arg9 = %arg6: tensor<184x1x3x3xbf16>, %arg10 = %arg7: tensor<184xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[1, 1], [1, 1]],
+        LayerName = "Conv_162",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "CMHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[184, 1, 3, 3]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_162",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "DepthwiseConv2dBf16",
+        With = {
+          config.act = 0 : ui8,
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.ifm_sv_depth.size = 8 : ui8,
+          config.ifm_sv_height.size = 6 : ui8,
+          config.ifm_sv_width.size = 26 : ui8,
+          config.kernel_height = 3 : ui8,
+          config.kernel_width = 3 : ui8,
+          config.stride = 1 : ui8,
+          data_io.ifm.dimensions.batch.padding = 0 : ui8,
+          data_io.ifm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.batch.padding = 0 : ui8,
+          data_io.ofm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.width.padding = 0 : ui8
+        },
+        estimation = {
+          compute_cycles = 1099 : ui64,
+          startup_cycles = 30 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x184x12x20xbf16> loc(#loc114)
+        xten_nn.output %465 : tensor<1x184x12x20xbf16> loc(#loc114)
+      } -> tensor<1x184x12x20xbf16> loc(#loc114)
+      xten_nn.output %464 : tensor<1x184x12x20xbf16> loc(#loc114)
+    } -> tensor<1x184x12x20xbf16> loc(#loc114)
+    %260 = xten_nn.subgraph (%arg5 = %259: tensor<1x184x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_164",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 4, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_164",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 5790 : ui64, ofm = 2910 : ui64},
+        computation_cycles = 853 : ui64,
+        cycle_count = 5790 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x184x12x20xbf16>)  attributes {
+        LayerName = "Add_164",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_164",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 71 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x184x12x20xbf16> loc(#loc115)
+        xten_nn.output %465 : tensor<1x184x12x20xbf16> loc(#loc115)
+      } -> tensor<1x184x12x20xbf16> loc(#loc115)
+      xten_nn.output %464 : tensor<1x184x12x20xbf16> loc(#loc115)
+    } -> tensor<1x184x12x20xbf16> loc(#loc115)
+    %261 = xten_nn.subgraph (%arg5 = %260: tensor<1x184x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_167",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_167",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 5790 : ui64, ofm = 2910 : ui64},
+        computation_cycles = 871 : ui64,
+        cycle_count = 5790 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x184x12x20xbf16>)  attributes {
+        LayerName = "Clip_167",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_167",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 79 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x184x12x20xbf16> loc(#loc116)
+        xten_nn.output %465 : tensor<1x184x12x20xbf16> loc(#loc116)
+      } -> tensor<1x184x12x20xbf16> loc(#loc116)
+      xten_nn.output %464 : tensor<1x184x12x20xbf16> loc(#loc116)
+    } -> tensor<1x184x12x20xbf16> loc(#loc116)
+    %262 = xten_nn.subgraph (%arg5 = %261: tensor<1x184x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_169",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_169",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 5790 : ui64, ofm = 2910 : ui64},
+        computation_cycles = 853 : ui64,
+        cycle_count = 5790 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x184x12x20xbf16>)  attributes {
+        LayerName = "Div_169",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_169",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 71 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x184x12x20xbf16> loc(#loc117)
+        xten_nn.output %465 : tensor<1x184x12x20xbf16> loc(#loc117)
+      } -> tensor<1x184x12x20xbf16> loc(#loc117)
+      xten_nn.output %464 : tensor<1x184x12x20xbf16> loc(#loc117)
+    } -> tensor<1x184x12x20xbf16> loc(#loc117)
+    %263 = xten_nn.subgraph (%arg5 = %259: tensor<1x184x12x20xbf16>, %arg6 = %262: tensor<1x184x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_170",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 4, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_170",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 5790 : ui64, ifm2 = 5790 : ui64, ofm = 2910 : ui64},
+        computation_cycles = 751 : ui64,
+        cycle_count = 5790 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x184x12x20xbf16>, %arg8 = %arg6: tensor<1x184x12x20xbf16>)  attributes {
+        LayerName = "Mul_170",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_170",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x184x12x20xbf16> loc(#loc118)
+        xten_nn.output %465 : tensor<1x184x12x20xbf16> loc(#loc118)
+      } -> tensor<1x184x12x20xbf16> loc(#loc118)
+      xten_nn.output %464 : tensor<1x184x12x20xbf16> loc(#loc118)
+    } -> tensor<1x184x12x20xbf16> loc(#loc118)
+    %264 = xten_nn.subgraph (%arg5 = %263: tensor<1x184x12x20xbf16>, %arg6 = %89: tensor<80x184x1x1xbf16>, %arg7 = %88: tensor<80xbf16>, %arg8 = %253: tensor<1x80x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 3 : index],
+      LayerName = "Conv_171",
+      OfmShare = 3 : index,
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 96, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[24, 96, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[16, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[80, 184, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[16, 8, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[80, 184, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 24, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_172",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 24, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 9276 : ui64, ifm2 = 4638 : ui64, ofm = 2334 : ui64, wts = 2516 : ui64},
+        computation_cycles = 9474 : ui64,
+        cycle_count = 9474 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg9 = %arg5: tensor<1x184x12x20xbf16>, %arg10 = %arg6: tensor<80x184x1x1xbf16>, %arg11 = %arg7: tensor<80xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_171",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 184, 12, 20]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[80, 184, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_171",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 96 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 32 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 2 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 24 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 2696 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %466 = tensor.empty() : tensor<1x80x12x20xbf16> loc(#loc119)
+        xten_nn.output %466 : tensor<1x80x12x20xbf16> loc(#loc119)
+      } -> tensor<1x80x12x20xbf16> loc(#loc119)
+      %465 = xten_nn.subgraph (%arg9 = %464: tensor<1x80x12x20xbf16>, %arg10 = %arg8: tensor<1x80x12x20xbf16>)  attributes {
+        LayerName = "Add_172",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_172",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.act = 0 : ui8,
+          config.act_type = "LINEAR",
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 24 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 32 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 59 : ui64,
+          startup_cycles = 22 : ui64
+        }} {
+        %466 = tensor.empty() : tensor<1x80x12x20xbf16> loc(#loc120)
+        xten_nn.output %466 : tensor<1x80x12x20xbf16> loc(#loc120)
+      } -> tensor<1x80x12x20xbf16> loc(#loc120)
+      xten_nn.output %465 : tensor<1x80x12x20xbf16> loc(#loc120)
+    } -> tensor<1x80x12x20xbf16> loc(#loc332)
+    %265 = xten_nn.subgraph (%arg5 = %264: tensor<1x80x12x20xbf16>, %arg6 = %87: tensor<480x80x1x1xbf16>, %arg7 = %86: tensor<480xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_173",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[40, 80, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[480, 80, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[480, 80, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_173",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 40, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 3870 : ui64, ofm = 13914 : ui64, wts = 5310 : ui64},
+        computation_cycles = 15962 : ui64,
+        cycle_count = 15962 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x80x12x20xbf16>, %arg9 = %arg6: tensor<480x80x1x1xbf16>, %arg10 = %arg7: tensor<480xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_173",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 80, 12, 20]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[480, 80, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_173",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 80 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 32 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 1 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 40 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 1596 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x480x12x20xbf16> loc(#loc121)
+        xten_nn.output %465 : tensor<1x480x12x20xbf16> loc(#loc121)
+      } -> tensor<1x480x12x20xbf16> loc(#loc121)
+      xten_nn.output %464 : tensor<1x480x12x20xbf16> loc(#loc121)
+    } -> tensor<1x480x12x20xbf16> loc(#loc121)
+    %266 = xten_nn.subgraph (%arg5 = %265: tensor<1x480x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_175",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_175",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 15400 : ui64, ofm = 7720 : ui64},
+        computation_cycles = 1301 : ui64,
+        cycle_count = 15400 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x480x12x20xbf16>)  attributes {
+        LayerName = "Add_175",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_175",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 32 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 131 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x480x12x20xbf16> loc(#loc122)
+        xten_nn.output %465 : tensor<1x480x12x20xbf16> loc(#loc122)
+      } -> tensor<1x480x12x20xbf16> loc(#loc122)
+      xten_nn.output %464 : tensor<1x480x12x20xbf16> loc(#loc122)
+    } -> tensor<1x480x12x20xbf16> loc(#loc122)
+    %267 = xten_nn.subgraph (%arg5 = %266: tensor<1x480x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_178",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_178",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 15400 : ui64, ofm = 7720 : ui64},
+        computation_cycles = 1327 : ui64,
+        cycle_count = 15400 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x480x12x20xbf16>)  attributes {
+        LayerName = "Clip_178",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_178",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 32 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 139 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x480x12x20xbf16> loc(#loc123)
+        xten_nn.output %465 : tensor<1x480x12x20xbf16> loc(#loc123)
+      } -> tensor<1x480x12x20xbf16> loc(#loc123)
+      xten_nn.output %464 : tensor<1x480x12x20xbf16> loc(#loc123)
+    } -> tensor<1x480x12x20xbf16> loc(#loc123)
+    %268 = xten_nn.subgraph (%arg5 = %267: tensor<1x480x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_180",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_180",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 15400 : ui64, ofm = 7720 : ui64},
+        computation_cycles = 1301 : ui64,
+        cycle_count = 15400 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x480x12x20xbf16>)  attributes {
+        LayerName = "Div_180",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_180",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 32 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 131 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x480x12x20xbf16> loc(#loc124)
+        xten_nn.output %465 : tensor<1x480x12x20xbf16> loc(#loc124)
+      } -> tensor<1x480x12x20xbf16> loc(#loc124)
+      xten_nn.output %464 : tensor<1x480x12x20xbf16> loc(#loc124)
+    } -> tensor<1x480x12x20xbf16> loc(#loc124)
+    %269 = xten_nn.subgraph (%arg5 = %265: tensor<1x480x12x20xbf16>, %arg6 = %268: tensor<1x480x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_181",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_181",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 15440 : ui64, ifm2 = 15440 : ui64, ofm = 7760 : ui64},
+        computation_cycles = 1656 : ui64,
+        cycle_count = 15440 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x480x12x20xbf16>, %arg8 = %arg6: tensor<1x480x12x20xbf16>)  attributes {
+        LayerName = "Mul_181",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_181",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x480x12x20xbf16> loc(#loc125)
+        xten_nn.output %465 : tensor<1x480x12x20xbf16> loc(#loc125)
+      } -> tensor<1x480x12x20xbf16> loc(#loc125)
+      xten_nn.output %464 : tensor<1x480x12x20xbf16> loc(#loc125)
+    } -> tensor<1x480x12x20xbf16> loc(#loc125)
+    %270 = xten_nn.subgraph (%arg5 = %269: tensor<1x480x12x20xbf16>, %arg6 = %85: tensor<480x1x3x3xbf16>, %arg7 = %84: tensor<480xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_182",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 8]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 6, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "CMHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 1]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[8, 1, 3, 3]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 1]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[480, 1, 3, 3]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 0, 0, 1]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[480, 1, 3, 3]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_182",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 4]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 4, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 4, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 40470 : ui64, ofm = 11670 : ui64, wts = 1110 : ui64},
+        computation_cycles = 18753 : ui64,
+        cycle_count = 40470 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 4, 3, 0]> : vector<4xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x480x12x20xbf16>, %arg9 = %arg6: tensor<480x1x3x3xbf16>, %arg10 = %arg7: tensor<480xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[1, 1], [1, 1]],
+        LayerName = "Conv_182",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "CMHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[480, 1, 3, 3]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_182",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "DepthwiseConv2dBf16",
+        With = {
+          config.act = 0 : ui8,
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.ifm_sv_depth.size = 8 : ui8,
+          config.ifm_sv_height.size = 6 : ui8,
+          config.ifm_sv_width.size = 26 : ui8,
+          config.kernel_height = 3 : ui8,
+          config.kernel_width = 3 : ui8,
+          config.stride = 1 : ui8,
+          data_io.ifm.dimensions.batch.padding = 0 : ui8,
+          data_io.ifm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.batch.padding = 0 : ui8,
+          data_io.ofm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.width.padding = 0 : ui8
+        },
+        estimation = {
+          compute_cycles = 1099 : ui64,
+          startup_cycles = 30 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x480x12x20xbf16> loc(#loc126)
+        xten_nn.output %465 : tensor<1x480x12x20xbf16> loc(#loc126)
+      } -> tensor<1x480x12x20xbf16> loc(#loc126)
+      xten_nn.output %464 : tensor<1x480x12x20xbf16> loc(#loc126)
+    } -> tensor<1x480x12x20xbf16> loc(#loc126)
+    %271 = xten_nn.subgraph (%arg5 = %270: tensor<1x480x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_184",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 4, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_184",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 15400 : ui64, ofm = 7720 : ui64},
+        computation_cycles = 1301 : ui64,
+        cycle_count = 15400 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x480x12x20xbf16>)  attributes {
+        LayerName = "Add_184",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_184",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 32 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 131 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x480x12x20xbf16> loc(#loc127)
+        xten_nn.output %465 : tensor<1x480x12x20xbf16> loc(#loc127)
+      } -> tensor<1x480x12x20xbf16> loc(#loc127)
+      xten_nn.output %464 : tensor<1x480x12x20xbf16> loc(#loc127)
+    } -> tensor<1x480x12x20xbf16> loc(#loc127)
+    %272 = xten_nn.subgraph (%arg5 = %271: tensor<1x480x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_187",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_187",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 15400 : ui64, ofm = 7720 : ui64},
+        computation_cycles = 1327 : ui64,
+        cycle_count = 15400 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x480x12x20xbf16>)  attributes {
+        LayerName = "Clip_187",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_187",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 32 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 139 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x480x12x20xbf16> loc(#loc128)
+        xten_nn.output %465 : tensor<1x480x12x20xbf16> loc(#loc128)
+      } -> tensor<1x480x12x20xbf16> loc(#loc128)
+      xten_nn.output %464 : tensor<1x480x12x20xbf16> loc(#loc128)
+    } -> tensor<1x480x12x20xbf16> loc(#loc128)
+    %273 = xten_nn.subgraph (%arg5 = %272: tensor<1x480x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_189",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_189",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 15400 : ui64, ofm = 7720 : ui64},
+        computation_cycles = 1301 : ui64,
+        cycle_count = 15400 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x480x12x20xbf16>)  attributes {
+        LayerName = "Div_189",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_189",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 32 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 131 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x480x12x20xbf16> loc(#loc129)
+        xten_nn.output %465 : tensor<1x480x12x20xbf16> loc(#loc129)
+      } -> tensor<1x480x12x20xbf16> loc(#loc129)
+      xten_nn.output %464 : tensor<1x480x12x20xbf16> loc(#loc129)
+    } -> tensor<1x480x12x20xbf16> loc(#loc129)
+    %274 = xten_nn.subgraph (%arg5 = %270: tensor<1x480x12x20xbf16>, %arg6 = %273: tensor<1x480x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_190",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 4, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_190",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 15440 : ui64, ifm2 = 15440 : ui64, ofm = 7760 : ui64},
+        computation_cycles = 1656 : ui64,
+        cycle_count = 15440 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x480x12x20xbf16>, %arg8 = %arg6: tensor<1x480x12x20xbf16>)  attributes {
+        LayerName = "Mul_190",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_190",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x480x12x20xbf16> loc(#loc130)
+        xten_nn.output %465 : tensor<1x480x12x20xbf16> loc(#loc130)
+      } -> tensor<1x480x12x20xbf16> loc(#loc130)
+      xten_nn.output %464 : tensor<1x480x12x20xbf16> loc(#loc130)
+    } -> tensor<1x480x12x20xbf16> loc(#loc130)
+    %275 = xten_nn.subgraph (%arg5 = %274: tensor<1x480x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#24",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#25",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 1, 240]> : vector<4xindex>
+        }
+      ],
+      Specializes = "Transpose4dAdf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.dim_0 = 12 : ui32,
+        config.dim_1 = 60 : ui32,
+        config.dim_2 = 20 : ui32,
+        config.dim_3 = 8 : ui32,
+        config.dtype = "bfloat16",
+        config.perm = 6 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x480x1x240xbf16> loc(#loc333)
+      xten_nn.output %464 : tensor<1x480x1x240xbf16> loc(#loc333)
+    } -> tensor<1x480x1x240xbf16> loc(#loc333)
+    %276 = xten_nn.subgraph (%arg5 = %275: tensor<1x480x1x240xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#26",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 40, 1, 48]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 1, 240]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 1, 240]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#27",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 40, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 57750 : ui64, ofm = 4950 : ui64},
+        computation_cycles = 45313 : ui64,
+        cycle_count = 57750 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x480x1x240xbf16>)  attributes {
+        LayerName = "Generated-#26",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 1, 240]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Generated-#27",
+        PadValue = 0.000000e+00 : bf16,
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ReduceMeanC8Bf16",
+        Traits = {
+          Reduce = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.full_channel = 480 : ui32,
+          config.full_height = 1 : ui32,
+          config.full_width = 240 : ui32,
+          config.reduce_dim = "W",
+          config.sv_channel = 40 : ui32,
+          config.sv_height = 1 : ui32,
+          config.sv_width = 48 : ui32
+        },
+        estimation = {
+          compute_cycles = 2311 : ui64,
+          startup_cycles = 190 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x480x1x1xbf16> loc(#loc131)
+        xten_nn.output %465 : tensor<1x480x1x1xbf16> loc(#loc131)
+      } -> tensor<1x480x1x1xbf16> loc(#loc131)
+      xten_nn.output %464 : tensor<1x480x1x1xbf16> loc(#loc131)
+    } -> tensor<1x480x1x1xbf16> loc(#loc131)
+    %277 = xten_nn.subgraph (%arg5 = %276: tensor<1x480x1x1xbf16>, %arg6 = %83: tensor<120x480x1x1xbf16>, %arg7 = %82: tensor<120xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_192",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 7]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[32, 120, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[8, 0, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[120, 480, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[8, 0, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[120, 480, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Relu_193",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 7]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 31]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 1960 : ui64, ofm = 650 : ui64, wts = 8232 : ui64},
+        computation_cycles = 5443 : ui64,
+        cycle_count = 8232 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[3, 1, 2, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x480x1x1xbf16>, %arg9 = %arg6: tensor<120x480x1x1xbf16>, %arg10 = %arg7: tensor<120xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_192",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[120, 480, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Relu_193",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true,
+          NonNegativeOut = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 1 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 12 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 120 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 8 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 0.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 0.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 4 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 32 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 8 : ui8
+        },
+        estimation = {
+          compute_cycles = 4552 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x120x1x1xbf16> loc(#loc133)
+        xten_nn.output %465 : tensor<1x120x1x1xbf16> loc(#loc133)
+      } -> tensor<1x120x1x1xbf16> loc(#loc334)
+      xten_nn.output %464 : tensor<1x120x1x1xbf16> loc(#loc334)
+    } -> tensor<1x120x1x1xbf16> loc(#loc334)
+    %278 = xten_nn.subgraph (%arg5 = %277: tensor<1x120x1x1xbf16>, %arg6 = %81: tensor<480x120x1x1xbf16>, %arg7 = %80: tensor<480xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_194",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 7]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 0, 31]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[32, 120, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[32, 0, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[480, 120, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[32, 0, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[480, 120, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_194",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 7]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 31]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 490 : ui64, ofm = 2600 : ui64, wts = 8232 : ui64},
+        computation_cycles = 5443 : ui64,
+        cycle_count = 8232 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[3, 1, 2, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x120x1x1xbf16>, %arg9 = %arg6: tensor<480x120x1x1xbf16>, %arg10 = %arg7: tensor<480xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_194",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 120, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[480, 120, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_194",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 12 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 120 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 8 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 1 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 32 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 8 : ui8
+        },
+        estimation = {
+          compute_cycles = 1138 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x480x1x1xbf16> loc(#loc134)
+        xten_nn.output %465 : tensor<1x480x1x1xbf16> loc(#loc134)
+      } -> tensor<1x480x1x1xbf16> loc(#loc134)
+      xten_nn.output %464 : tensor<1x480x1x1xbf16> loc(#loc134)
+    } -> tensor<1x480x1x1xbf16> loc(#loc134)
+    %279 = xten_nn.subgraph (%arg5 = %278: tensor<1x480x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_196",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 2, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 128, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 31]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_196",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 2, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 128, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 11, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 778 : ui64, ofm = 394 : ui64},
+        computation_cycles = 401 : ui64,
+        cycle_count = 778 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x480x1x1xbf16>)  attributes {
+        LayerName = "Add_196",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_196",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 128 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 1 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 35 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x480x1x1xbf16> loc(#loc135)
+        xten_nn.output %465 : tensor<1x480x1x1xbf16> loc(#loc135)
+      } -> tensor<1x480x1x1xbf16> loc(#loc135)
+      xten_nn.output %464 : tensor<1x480x1x1xbf16> loc(#loc135)
+    } -> tensor<1x480x1x1xbf16> loc(#loc135)
+    %280 = xten_nn.subgraph (%arg5 = %279: tensor<1x480x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_199",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 1, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 128, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 11, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_199",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 1, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 128, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 7, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 522 : ui64, ofm = 266 : ui64},
+        computation_cycles = 395 : ui64,
+        cycle_count = 522 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x480x1x1xbf16>)  attributes {
+        LayerName = "Clip_199",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_199",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 128 : ui32,
+          config.ifmsv_height = 2 : ui32,
+          config.ifmsv_width = 1 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 35 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x480x1x1xbf16> loc(#loc136)
+        xten_nn.output %465 : tensor<1x480x1x1xbf16> loc(#loc136)
+      } -> tensor<1x480x1x1xbf16> loc(#loc136)
+      xten_nn.output %464 : tensor<1x480x1x1xbf16> loc(#loc136)
+    } -> tensor<1x480x1x1xbf16> loc(#loc136)
+    %281 = xten_nn.subgraph (%arg5 = %280: tensor<1x480x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_201",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 3, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 128, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 7, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_201",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 3, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 128, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 15, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 1034 : ui64, ofm = 522 : ui64},
+        computation_cycles = 409 : ui64,
+        cycle_count = 1034 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x480x1x1xbf16>)  attributes {
+        LayerName = "Div_201",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_201",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 128 : ui32,
+          config.ifmsv_height = 4 : ui32,
+          config.ifmsv_width = 1 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 43 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x480x1x1xbf16> loc(#loc137)
+        xten_nn.output %465 : tensor<1x480x1x1xbf16> loc(#loc137)
+      } -> tensor<1x480x1x1xbf16> loc(#loc137)
+      xten_nn.output %464 : tensor<1x480x1x1xbf16> loc(#loc137)
+    } -> tensor<1x480x1x1xbf16> loc(#loc137)
+    %282 = xten_nn.subgraph (%arg5 = %281: tensor<1x480x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#28",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#29",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+        }
+      ],
+      Specializes = "TileAdf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.dtype = "bfloat16",
+        config.i_dim_c = 480 : ui32,
+        config.i_dim_h = 1 : ui32,
+        config.i_dim_n = 1 : ui32,
+        config.i_dim_w = 1 : ui32,
+        config.rep_dim_c = 1 : ui32,
+        config.rep_dim_h = 12 : ui32,
+        config.rep_dim_w = 20 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x480x12x20xbf16> loc(#loc138)
+      xten_nn.output %464 : tensor<1x480x12x20xbf16> loc(#loc138)
+    } -> tensor<1x480x12x20xbf16> loc(#loc138)
+    %283 = xten_nn.subgraph (%arg5 = %282: tensor<1x480x12x20xbf16>, %arg6 = %274: tensor<1x480x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_202",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_202",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 15440 : ui64, ifm2 = 15440 : ui64, ofm = 7760 : ui64},
+        computation_cycles = 1656 : ui64,
+        cycle_count = 15440 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x480x12x20xbf16>, %arg8 = %arg6: tensor<1x480x12x20xbf16>)  attributes {
+        LayerName = "Mul_202",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_202",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x480x12x20xbf16> loc(#loc138)
+        xten_nn.output %465 : tensor<1x480x12x20xbf16> loc(#loc138)
+      } -> tensor<1x480x12x20xbf16> loc(#loc138)
+      xten_nn.output %464 : tensor<1x480x12x20xbf16> loc(#loc138)
+    } -> tensor<1x480x12x20xbf16> loc(#loc138)
+    %284 = xten_nn.subgraph (%arg5 = %283: tensor<1x480x12x20xbf16>, %arg6 = %79: tensor<112x480x1x1xbf16>, %arg7 = %78: tensor<112xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_203",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 96, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[32, 96, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[16, 0, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[112, 480, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[16, 0, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[112, 480, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_203",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 112, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 112, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 23190 : ui64, ofm = 6942 : ui64, wts = 8370 : ui64},
+        computation_cycles = 25063 : ui64,
+        cycle_count = 25063 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x480x12x20xbf16>, %arg9 = %arg6: tensor<112x480x1x1xbf16>, %arg10 = %arg7: tensor<112xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_203",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 480, 12, 20]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[112, 480, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_203",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 112, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 0 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 96 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 32 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 5 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 32 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 7555 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x112x12x20xbf16> loc(#loc139)
+        xten_nn.output %465 : tensor<1x112x12x20xbf16> loc(#loc139)
+      } -> tensor<1x112x12x20xbf16> loc(#loc139)
+      xten_nn.output %464 : tensor<1x112x12x20xbf16> loc(#loc139)
+    } -> tensor<1x112x12x20xbf16> loc(#loc139)
+    %285 = xten_nn.subgraph (%arg5 = %284: tensor<1x112x12x20xbf16>, %arg6 = %77: tensor<672x112x1x1xbf16>, %arg7 = %76: tensor<672xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_204",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 64, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 112, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 112, 12, 20]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[56, 64, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[672, 112, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 16, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[672, 112, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_204",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 56, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 6204 : ui64, ofm = 18522 : ui64, wts = 12156 : ui64},
+        computation_cycles = 34007 : ui64,
+        cycle_count = 34007 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x112x12x20xbf16>, %arg9 = %arg6: tensor<672x112x1x1xbf16>, %arg10 = %arg7: tensor<672xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_204",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 112, 12, 20]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[672, 112, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_204",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 64 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 32 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 2 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 56 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 3464 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x12x20xbf16> loc(#loc140)
+        xten_nn.output %465 : tensor<1x672x12x20xbf16> loc(#loc140)
+      } -> tensor<1x672x12x20xbf16> loc(#loc140)
+      xten_nn.output %464 : tensor<1x672x12x20xbf16> loc(#loc140)
+    } -> tensor<1x672x12x20xbf16> loc(#loc140)
+    %286 = xten_nn.subgraph (%arg5 = %285: tensor<1x672x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_206",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_206",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 21230 : ui64, ofm = 10670 : ui64},
+        computation_cycles = 2517 : ui64,
+        cycle_count = 21230 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x672x12x20xbf16>)  attributes {
+        LayerName = "Add_206",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_206",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 71 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x12x20xbf16> loc(#loc141)
+        xten_nn.output %465 : tensor<1x672x12x20xbf16> loc(#loc141)
+      } -> tensor<1x672x12x20xbf16> loc(#loc141)
+      xten_nn.output %464 : tensor<1x672x12x20xbf16> loc(#loc141)
+    } -> tensor<1x672x12x20xbf16> loc(#loc141)
+    %287 = xten_nn.subgraph (%arg5 = %286: tensor<1x672x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_209",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_209",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 21230 : ui64, ofm = 10670 : ui64},
+        computation_cycles = 2599 : ui64,
+        cycle_count = 21230 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x672x12x20xbf16>)  attributes {
+        LayerName = "Clip_209",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_209",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 79 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x12x20xbf16> loc(#loc142)
+        xten_nn.output %465 : tensor<1x672x12x20xbf16> loc(#loc142)
+      } -> tensor<1x672x12x20xbf16> loc(#loc142)
+      xten_nn.output %464 : tensor<1x672x12x20xbf16> loc(#loc142)
+    } -> tensor<1x672x12x20xbf16> loc(#loc142)
+    %288 = xten_nn.subgraph (%arg5 = %287: tensor<1x672x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_211",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_211",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 21230 : ui64, ofm = 10670 : ui64},
+        computation_cycles = 2517 : ui64,
+        cycle_count = 21230 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x672x12x20xbf16>)  attributes {
+        LayerName = "Div_211",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_211",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 71 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x12x20xbf16> loc(#loc143)
+        xten_nn.output %465 : tensor<1x672x12x20xbf16> loc(#loc143)
+      } -> tensor<1x672x12x20xbf16> loc(#loc143)
+      xten_nn.output %464 : tensor<1x672x12x20xbf16> loc(#loc143)
+    } -> tensor<1x672x12x20xbf16> loc(#loc143)
+    %289 = xten_nn.subgraph (%arg5 = %285: tensor<1x672x12x20xbf16>, %arg6 = %288: tensor<1x672x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_212",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_212",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 21230 : ui64, ifm2 = 21230 : ui64, ofm = 10670 : ui64},
+        computation_cycles = 2199 : ui64,
+        cycle_count = 21230 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x672x12x20xbf16>, %arg8 = %arg6: tensor<1x672x12x20xbf16>)  attributes {
+        LayerName = "Mul_212",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_212",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x12x20xbf16> loc(#loc144)
+        xten_nn.output %465 : tensor<1x672x12x20xbf16> loc(#loc144)
+      } -> tensor<1x672x12x20xbf16> loc(#loc144)
+      xten_nn.output %464 : tensor<1x672x12x20xbf16> loc(#loc144)
+    } -> tensor<1x672x12x20xbf16> loc(#loc144)
+    %290 = xten_nn.subgraph (%arg5 = %289: tensor<1x672x12x20xbf16>, %arg6 = %75: tensor<672x1x3x3xbf16>, %arg7 = %74: tensor<672xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_213",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 8]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 6, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "CMHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 1]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[8, 1, 3, 3]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 1]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[672, 1, 3, 3]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 0, 0, 1]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[672, 1, 3, 3]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_213",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 4]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 4, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 4, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 56658 : ui64, ofm = 16338 : ui64, wts = 1554 : ui64},
+        computation_cycles = 26169 : ui64,
+        cycle_count = 56658 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 4, 3, 0]> : vector<4xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x672x12x20xbf16>, %arg9 = %arg6: tensor<672x1x3x3xbf16>, %arg10 = %arg7: tensor<672xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[1, 1], [1, 1]],
+        LayerName = "Conv_213",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "CMHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[672, 1, 3, 3]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_213",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "DepthwiseConv2dBf16",
+        With = {
+          config.act = 0 : ui8,
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.ifm_sv_depth.size = 8 : ui8,
+          config.ifm_sv_height.size = 6 : ui8,
+          config.ifm_sv_width.size = 26 : ui8,
+          config.kernel_height = 3 : ui8,
+          config.kernel_width = 3 : ui8,
+          config.stride = 1 : ui8,
+          data_io.ifm.dimensions.batch.padding = 0 : ui8,
+          data_io.ifm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.batch.padding = 0 : ui8,
+          data_io.ofm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.width.padding = 0 : ui8
+        },
+        estimation = {
+          compute_cycles = 1099 : ui64,
+          startup_cycles = 30 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x12x20xbf16> loc(#loc145)
+        xten_nn.output %465 : tensor<1x672x12x20xbf16> loc(#loc145)
+      } -> tensor<1x672x12x20xbf16> loc(#loc145)
+      xten_nn.output %464 : tensor<1x672x12x20xbf16> loc(#loc145)
+    } -> tensor<1x672x12x20xbf16> loc(#loc145)
+    %291 = xten_nn.subgraph (%arg5 = %290: tensor<1x672x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_215",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 4, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_215",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 21230 : ui64, ofm = 10670 : ui64},
+        computation_cycles = 2517 : ui64,
+        cycle_count = 21230 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x672x12x20xbf16>)  attributes {
+        LayerName = "Add_215",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_215",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 71 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x12x20xbf16> loc(#loc146)
+        xten_nn.output %465 : tensor<1x672x12x20xbf16> loc(#loc146)
+      } -> tensor<1x672x12x20xbf16> loc(#loc146)
+      xten_nn.output %464 : tensor<1x672x12x20xbf16> loc(#loc146)
+    } -> tensor<1x672x12x20xbf16> loc(#loc146)
+    %292 = xten_nn.subgraph (%arg5 = %291: tensor<1x672x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_218",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_218",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 21230 : ui64, ofm = 10670 : ui64},
+        computation_cycles = 2599 : ui64,
+        cycle_count = 21230 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x672x12x20xbf16>)  attributes {
+        LayerName = "Clip_218",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_218",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 79 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x12x20xbf16> loc(#loc147)
+        xten_nn.output %465 : tensor<1x672x12x20xbf16> loc(#loc147)
+      } -> tensor<1x672x12x20xbf16> loc(#loc147)
+      xten_nn.output %464 : tensor<1x672x12x20xbf16> loc(#loc147)
+    } -> tensor<1x672x12x20xbf16> loc(#loc147)
+    %293 = xten_nn.subgraph (%arg5 = %292: tensor<1x672x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_220",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_220",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 21230 : ui64, ofm = 10670 : ui64},
+        computation_cycles = 2517 : ui64,
+        cycle_count = 21230 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x672x12x20xbf16>)  attributes {
+        LayerName = "Div_220",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_220",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 71 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x12x20xbf16> loc(#loc148)
+        xten_nn.output %465 : tensor<1x672x12x20xbf16> loc(#loc148)
+      } -> tensor<1x672x12x20xbf16> loc(#loc148)
+      xten_nn.output %464 : tensor<1x672x12x20xbf16> loc(#loc148)
+    } -> tensor<1x672x12x20xbf16> loc(#loc148)
+    %294 = xten_nn.subgraph (%arg5 = %290: tensor<1x672x12x20xbf16>, %arg6 = %293: tensor<1x672x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_221",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 4, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_221",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 21230 : ui64, ifm2 = 21230 : ui64, ofm = 10670 : ui64},
+        computation_cycles = 2199 : ui64,
+        cycle_count = 21230 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x672x12x20xbf16>, %arg8 = %arg6: tensor<1x672x12x20xbf16>)  attributes {
+        LayerName = "Mul_221",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_221",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x12x20xbf16> loc(#loc149)
+        xten_nn.output %465 : tensor<1x672x12x20xbf16> loc(#loc149)
+      } -> tensor<1x672x12x20xbf16> loc(#loc149)
+      xten_nn.output %464 : tensor<1x672x12x20xbf16> loc(#loc149)
+    } -> tensor<1x672x12x20xbf16> loc(#loc149)
+    %295 = xten_nn.subgraph (%arg5 = %294: tensor<1x672x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#30",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#31",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 1, 240]> : vector<4xindex>
+        }
+      ],
+      Specializes = "Transpose4dAdf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.dim_0 = 12 : ui32,
+        config.dim_1 = 84 : ui32,
+        config.dim_2 = 20 : ui32,
+        config.dim_3 = 8 : ui32,
+        config.dtype = "bfloat16",
+        config.perm = 6 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x672x1x240xbf16> loc(#loc335)
+      xten_nn.output %464 : tensor<1x672x1x240xbf16> loc(#loc335)
+    } -> tensor<1x672x1x240xbf16> loc(#loc335)
+    %296 = xten_nn.subgraph (%arg5 = %295: tensor<1x672x1x240xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#32",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 56, 1, 32]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 1, 240]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 1, 240]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#33",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 56, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 86256 : ui64, ofm = 10992 : ui64},
+        computation_cycles = 81517 : ui64,
+        cycle_count = 86256 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x672x1x240xbf16>)  attributes {
+        LayerName = "Generated-#32",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 1, 240]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Generated-#33",
+        PadValue = 0.000000e+00 : bf16,
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ReduceMeanC8Bf16",
+        Traits = {
+          Reduce = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.full_channel = 672 : ui32,
+          config.full_height = 1 : ui32,
+          config.full_width = 240 : ui32,
+          config.reduce_dim = "W",
+          config.sv_channel = 56 : ui32,
+          config.sv_height = 1 : ui32,
+          config.sv_width = 32 : ui32
+        },
+        estimation = {
+          compute_cycles = 2285 : ui64,
+          startup_cycles = 190 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x1x1xbf16> loc(#loc150)
+        xten_nn.output %465 : tensor<1x672x1x1xbf16> loc(#loc150)
+      } -> tensor<1x672x1x1xbf16> loc(#loc150)
+      xten_nn.output %464 : tensor<1x672x1x1xbf16> loc(#loc150)
+    } -> tensor<1x672x1x1xbf16> loc(#loc150)
+    %297 = xten_nn.subgraph (%arg5 = %296: tensor<1x672x1x1xbf16>, %arg6 = %73: tensor<168x672x1x1xbf16>, %arg7 = %72: tensor<168xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_223",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 7]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 96, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[48, 96, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[24, 0, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[168, 672, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[24, 0, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[168, 672, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Relu_224",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 7]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 48, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 0, 31]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 168, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 168, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 2758 : ui64, ofm = 906 : ui64, wts = 17542 : ui64},
+        computation_cycles = 10332 : ui64,
+        cycle_count = 17542 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[3, 1, 2, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x672x1x1xbf16>, %arg9 = %arg6: tensor<168x672x1x1xbf16>, %arg10 = %arg7: tensor<168xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_223",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[168, 672, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Relu_224",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 168, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true,
+          NonNegativeOut = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 1 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 12 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 96 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 8 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 0.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 0.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 7 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 48 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 8 : ui8
+        },
+        estimation = {
+          compute_cycles = 9030 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x168x1x1xbf16> loc(#loc152)
+        xten_nn.output %465 : tensor<1x168x1x1xbf16> loc(#loc152)
+      } -> tensor<1x168x1x1xbf16> loc(#loc336)
+      xten_nn.output %464 : tensor<1x168x1x1xbf16> loc(#loc336)
+    } -> tensor<1x168x1x1xbf16> loc(#loc336)
+    %298 = xten_nn.subgraph (%arg5 = %297: tensor<1x168x1x1xbf16>, %arg6 = %71: tensor<672x168x1x1xbf16>, %arg7 = %70: tensor<672xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_225",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 15]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 168, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 0, 31]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 168, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 168, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[16, 168, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[32, 0, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[672, 168, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[32, 0, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[672, 168, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_225",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 15]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 63]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 1354 : ui64, ofm = 8558 : ui64, wts = 15598 : ui64},
+        computation_cycles = 16150 : ui64,
+        cycle_count = 16150 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[3, 1, 2, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x168x1x1xbf16>, %arg9 = %arg6: tensor<672x168x1x1xbf16>, %arg10 = %arg7: tensor<672xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_225",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 168, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[672, 168, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_225",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 12 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 168 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 16 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 1 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 16 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 16 : ui8
+        },
+        estimation = {
+          compute_cycles = 1300 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x1x1xbf16> loc(#loc153)
+        xten_nn.output %465 : tensor<1x672x1x1xbf16> loc(#loc153)
+      } -> tensor<1x672x1x1xbf16> loc(#loc153)
+      xten_nn.output %464 : tensor<1x672x1x1xbf16> loc(#loc153)
+    } -> tensor<1x672x1x1xbf16> loc(#loc153)
+    %299 = xten_nn.subgraph (%arg5 = %298: tensor<1x672x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_227",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 1, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 192, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 63]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_227",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 1, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 192, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 96, 7, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 778 : ui64, ofm = 394 : ui64},
+        computation_cycles = 401 : ui64,
+        cycle_count = 778 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x672x1x1xbf16>)  attributes {
+        LayerName = "Add_227",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_227",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 192 : ui32,
+          config.ifmsv_height = 2 : ui32,
+          config.ifmsv_width = 1 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 35 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x1x1xbf16> loc(#loc154)
+        xten_nn.output %465 : tensor<1x672x1x1xbf16> loc(#loc154)
+      } -> tensor<1x672x1x1xbf16> loc(#loc154)
+      xten_nn.output %464 : tensor<1x672x1x1xbf16> loc(#loc154)
+    } -> tensor<1x672x1x1xbf16> loc(#loc154)
+    %300 = xten_nn.subgraph (%arg5 = %299: tensor<1x672x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_230",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 256, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 96, 7, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_230",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 256, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 352, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 522 : ui64, ofm = 266 : ui64},
+        computation_cycles = 395 : ui64,
+        cycle_count = 522 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x672x1x1xbf16>)  attributes {
+        LayerName = "Clip_230",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_230",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 256 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 1 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 35 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x1x1xbf16> loc(#loc155)
+        xten_nn.output %465 : tensor<1x672x1x1xbf16> loc(#loc155)
+      } -> tensor<1x672x1x1xbf16> loc(#loc155)
+      xten_nn.output %464 : tensor<1x672x1x1xbf16> loc(#loc155)
+    } -> tensor<1x672x1x1xbf16> loc(#loc155)
+    %301 = xten_nn.subgraph (%arg5 = %300: tensor<1x672x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_232",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 1, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 256, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 352, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_232",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 1, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 256, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 352, 7, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 1034 : ui64, ofm = 522 : ui64},
+        computation_cycles = 409 : ui64,
+        cycle_count = 1034 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x672x1x1xbf16>)  attributes {
+        LayerName = "Div_232",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_232",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 256 : ui32,
+          config.ifmsv_height = 2 : ui32,
+          config.ifmsv_width = 1 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 43 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x1x1xbf16> loc(#loc156)
+        xten_nn.output %465 : tensor<1x672x1x1xbf16> loc(#loc156)
+      } -> tensor<1x672x1x1xbf16> loc(#loc156)
+      xten_nn.output %464 : tensor<1x672x1x1xbf16> loc(#loc156)
+    } -> tensor<1x672x1x1xbf16> loc(#loc156)
+    %302 = xten_nn.subgraph (%arg5 = %301: tensor<1x672x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#34",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#35",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      Specializes = "TileAdf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.dtype = "bfloat16",
+        config.i_dim_c = 672 : ui32,
+        config.i_dim_h = 1 : ui32,
+        config.i_dim_n = 1 : ui32,
+        config.i_dim_w = 1 : ui32,
+        config.rep_dim_c = 1 : ui32,
+        config.rep_dim_h = 12 : ui32,
+        config.rep_dim_w = 20 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x672x12x20xbf16> loc(#loc157)
+      xten_nn.output %464 : tensor<1x672x12x20xbf16> loc(#loc157)
+    } -> tensor<1x672x12x20xbf16> loc(#loc157)
+    %303 = xten_nn.subgraph (%arg5 = %302: tensor<1x672x12x20xbf16>, %arg6 = %294: tensor<1x672x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_233",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_233",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 21230 : ui64, ifm2 = 21230 : ui64, ofm = 10670 : ui64},
+        computation_cycles = 2199 : ui64,
+        cycle_count = 21230 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x672x12x20xbf16>, %arg8 = %arg6: tensor<1x672x12x20xbf16>)  attributes {
+        LayerName = "Mul_233",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_233",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x12x20xbf16> loc(#loc157)
+        xten_nn.output %465 : tensor<1x672x12x20xbf16> loc(#loc157)
+      } -> tensor<1x672x12x20xbf16> loc(#loc157)
+      xten_nn.output %464 : tensor<1x672x12x20xbf16> loc(#loc157)
+    } -> tensor<1x672x12x20xbf16> loc(#loc157)
+    %304 = xten_nn.subgraph (%arg5 = %303: tensor<1x672x12x20xbf16>, %arg6 = %69: tensor<112x672x1x1xbf16>, %arg7 = %68: tensor<112xbf16>, %arg8 = %284: tensor<1x112x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 3 : index],
+      LayerName = "Conv_234",
+      OfmShare = 3 : index,
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 96, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[32, 96, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[16, 0, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[112, 672, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[16, 0, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[112, 672, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 112, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 112, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_235",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 112, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 112, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 32466 : ui64, ifm2 = 6174 : ui64, ofm = 3102 : ui64, wts = 11718 : ui64},
+        computation_cycles = 35198 : ui64,
+        cycle_count = 35198 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg9 = %arg5: tensor<1x672x12x20xbf16>, %arg10 = %arg6: tensor<112x672x1x1xbf16>, %arg11 = %arg7: tensor<112xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_234",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[112, 672, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_234",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 112, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 0 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 96 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 32 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 7 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 32 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 10577 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %466 = tensor.empty() : tensor<1x112x12x20xbf16> loc(#loc158)
+        xten_nn.output %466 : tensor<1x112x12x20xbf16> loc(#loc158)
+      } -> tensor<1x112x12x20xbf16> loc(#loc158)
+      %465 = xten_nn.subgraph (%arg9 = %464: tensor<1x112x12x20xbf16>, %arg10 = %arg8: tensor<1x112x12x20xbf16>)  attributes {
+        LayerName = "Add_235",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 112, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 112, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_235",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 112, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.act = 0 : ui8,
+          config.act_type = "LINEAR",
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 32 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 32 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 75 : ui64,
+          startup_cycles = 22 : ui64
+        }} {
+        %466 = tensor.empty() : tensor<1x112x12x20xbf16> loc(#loc159)
+        xten_nn.output %466 : tensor<1x112x12x20xbf16> loc(#loc159)
+      } -> tensor<1x112x12x20xbf16> loc(#loc159)
+      xten_nn.output %465 : tensor<1x112x12x20xbf16> loc(#loc159)
+    } -> tensor<1x112x12x20xbf16> loc(#loc337)
+    %305 = xten_nn.subgraph (%arg5 = %304: tensor<1x112x12x20xbf16>, %arg6 = %67: tensor<672x112x1x1xbf16>, %arg7 = %66: tensor<672xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_236",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 64, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 112, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 112, 12, 20]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[56, 64, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[672, 112, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 16, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[672, 112, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_236",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 56, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 6204 : ui64, ofm = 18522 : ui64, wts = 12156 : ui64},
+        computation_cycles = 34007 : ui64,
+        cycle_count = 34007 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x112x12x20xbf16>, %arg9 = %arg6: tensor<672x112x1x1xbf16>, %arg10 = %arg7: tensor<672xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_236",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 112, 12, 20]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[672, 112, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_236",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 64 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 32 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 2 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 56 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 3464 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x12x20xbf16> loc(#loc160)
+        xten_nn.output %465 : tensor<1x672x12x20xbf16> loc(#loc160)
+      } -> tensor<1x672x12x20xbf16> loc(#loc160)
+      xten_nn.output %464 : tensor<1x672x12x20xbf16> loc(#loc160)
+    } -> tensor<1x672x12x20xbf16> loc(#loc160)
+    %306 = xten_nn.subgraph (%arg5 = %305: tensor<1x672x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_238",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_238",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 21230 : ui64, ofm = 10670 : ui64},
+        computation_cycles = 2517 : ui64,
+        cycle_count = 21230 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x672x12x20xbf16>)  attributes {
+        LayerName = "Add_238",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_238",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 71 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x12x20xbf16> loc(#loc161)
+        xten_nn.output %465 : tensor<1x672x12x20xbf16> loc(#loc161)
+      } -> tensor<1x672x12x20xbf16> loc(#loc161)
+      xten_nn.output %464 : tensor<1x672x12x20xbf16> loc(#loc161)
+    } -> tensor<1x672x12x20xbf16> loc(#loc161)
+    %307 = xten_nn.subgraph (%arg5 = %306: tensor<1x672x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_241",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_241",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 21230 : ui64, ofm = 10670 : ui64},
+        computation_cycles = 2599 : ui64,
+        cycle_count = 21230 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x672x12x20xbf16>)  attributes {
+        LayerName = "Clip_241",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_241",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 79 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x12x20xbf16> loc(#loc162)
+        xten_nn.output %465 : tensor<1x672x12x20xbf16> loc(#loc162)
+      } -> tensor<1x672x12x20xbf16> loc(#loc162)
+      xten_nn.output %464 : tensor<1x672x12x20xbf16> loc(#loc162)
+    } -> tensor<1x672x12x20xbf16> loc(#loc162)
+    %308 = xten_nn.subgraph (%arg5 = %307: tensor<1x672x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_243",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_243",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 21230 : ui64, ofm = 10670 : ui64},
+        computation_cycles = 2517 : ui64,
+        cycle_count = 21230 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x672x12x20xbf16>)  attributes {
+        LayerName = "Div_243",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_243",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 71 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x12x20xbf16> loc(#loc163)
+        xten_nn.output %465 : tensor<1x672x12x20xbf16> loc(#loc163)
+      } -> tensor<1x672x12x20xbf16> loc(#loc163)
+      xten_nn.output %464 : tensor<1x672x12x20xbf16> loc(#loc163)
+    } -> tensor<1x672x12x20xbf16> loc(#loc163)
+    %309 = xten_nn.subgraph (%arg5 = %305: tensor<1x672x12x20xbf16>, %arg6 = %308: tensor<1x672x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_244",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_244",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 21230 : ui64, ifm2 = 21230 : ui64, ofm = 10670 : ui64},
+        computation_cycles = 2199 : ui64,
+        cycle_count = 21230 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x672x12x20xbf16>, %arg8 = %arg6: tensor<1x672x12x20xbf16>)  attributes {
+        LayerName = "Mul_244",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_244",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x12x20xbf16> loc(#loc164)
+        xten_nn.output %465 : tensor<1x672x12x20xbf16> loc(#loc164)
+      } -> tensor<1x672x12x20xbf16> loc(#loc164)
+      xten_nn.output %464 : tensor<1x672x12x20xbf16> loc(#loc164)
+    } -> tensor<1x672x12x20xbf16> loc(#loc164)
+    %310 = xten_nn.subgraph (%arg5 = %309: tensor<1x672x12x20xbf16>, %arg6 = %65: tensor<672x1x9x9xbf16>, %arg7 = %64: tensor<672xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_245",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 10, 16]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "CMHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 3]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[8, 1, 9, 9]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 3]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[672, 1, 9, 9]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 0, 0, 3]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[672, 1, 9, 9]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_245",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 2, 8]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 4, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 323820 : ui64, ofm = 17388 : ui64, wts = 9618 : ui64},
+        computation_cycles = 110589 : ui64,
+        cycle_count = 323820 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 4, 3, 0]> : vector<4xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x672x12x20xbf16>, %arg9 = %arg6: tensor<672x1x9x9xbf16>, %arg10 = %arg7: tensor<672xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[4, 4], [4, 4]],
+        LayerName = "Conv_245",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "CMHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[672, 1, 9, 9]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_245",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "DepthwiseConv2dBf16",
+        With = {
+          config.act = 0 : ui8,
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.ifm_sv_depth.size = 8 : ui8,
+          config.ifm_sv_height.size = 10 : ui8,
+          config.ifm_sv_width.size = 16 : ui8,
+          config.kernel_height = 9 : ui8,
+          config.kernel_width = 9 : ui8,
+          config.stride = 1 : ui8,
+          data_io.ifm.dimensions.batch.padding = 0 : ui8,
+          data_io.ifm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.batch.padding = 0 : ui8,
+          data_io.ofm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.width.padding = 0 : ui8
+        },
+        estimation = {
+          compute_cycles = 739 : ui64,
+          startup_cycles = 30 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x12x20xbf16> loc(#loc165)
+        xten_nn.output %465 : tensor<1x672x12x20xbf16> loc(#loc165)
+      } -> tensor<1x672x12x20xbf16> loc(#loc165)
+      xten_nn.output %464 : tensor<1x672x12x20xbf16> loc(#loc165)
+    } -> tensor<1x672x12x20xbf16> loc(#loc165)
+    %311 = xten_nn.subgraph (%arg5 = %310: tensor<1x672x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_247",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 4, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_247",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 21230 : ui64, ofm = 10670 : ui64},
+        computation_cycles = 2517 : ui64,
+        cycle_count = 21230 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x672x12x20xbf16>)  attributes {
+        LayerName = "Add_247",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_247",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 71 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x12x20xbf16> loc(#loc166)
+        xten_nn.output %465 : tensor<1x672x12x20xbf16> loc(#loc166)
+      } -> tensor<1x672x12x20xbf16> loc(#loc166)
+      xten_nn.output %464 : tensor<1x672x12x20xbf16> loc(#loc166)
+    } -> tensor<1x672x12x20xbf16> loc(#loc166)
+    %312 = xten_nn.subgraph (%arg5 = %311: tensor<1x672x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_250",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_250",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 21230 : ui64, ofm = 10670 : ui64},
+        computation_cycles = 2599 : ui64,
+        cycle_count = 21230 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x672x12x20xbf16>)  attributes {
+        LayerName = "Clip_250",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_250",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 79 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x12x20xbf16> loc(#loc167)
+        xten_nn.output %465 : tensor<1x672x12x20xbf16> loc(#loc167)
+      } -> tensor<1x672x12x20xbf16> loc(#loc167)
+      xten_nn.output %464 : tensor<1x672x12x20xbf16> loc(#loc167)
+    } -> tensor<1x672x12x20xbf16> loc(#loc167)
+    %313 = xten_nn.subgraph (%arg5 = %312: tensor<1x672x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_252",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_252",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 21230 : ui64, ofm = 10670 : ui64},
+        computation_cycles = 2517 : ui64,
+        cycle_count = 21230 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x672x12x20xbf16>)  attributes {
+        LayerName = "Div_252",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_252",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 71 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x12x20xbf16> loc(#loc168)
+        xten_nn.output %465 : tensor<1x672x12x20xbf16> loc(#loc168)
+      } -> tensor<1x672x12x20xbf16> loc(#loc168)
+      xten_nn.output %464 : tensor<1x672x12x20xbf16> loc(#loc168)
+    } -> tensor<1x672x12x20xbf16> loc(#loc168)
+    %314 = xten_nn.subgraph (%arg5 = %310: tensor<1x672x12x20xbf16>, %arg6 = %313: tensor<1x672x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_253",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 4, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_253",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 21230 : ui64, ifm2 = 21230 : ui64, ofm = 10670 : ui64},
+        computation_cycles = 2199 : ui64,
+        cycle_count = 21230 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x672x12x20xbf16>, %arg8 = %arg6: tensor<1x672x12x20xbf16>)  attributes {
+        LayerName = "Mul_253",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_253",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x12x20xbf16> loc(#loc169)
+        xten_nn.output %465 : tensor<1x672x12x20xbf16> loc(#loc169)
+      } -> tensor<1x672x12x20xbf16> loc(#loc169)
+      xten_nn.output %464 : tensor<1x672x12x20xbf16> loc(#loc169)
+    } -> tensor<1x672x12x20xbf16> loc(#loc169)
+    %315 = xten_nn.subgraph (%arg5 = %314: tensor<1x672x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#36",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#37",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 1, 240]> : vector<4xindex>
+        }
+      ],
+      Specializes = "Transpose4dAdf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.dim_0 = 12 : ui32,
+        config.dim_1 = 84 : ui32,
+        config.dim_2 = 20 : ui32,
+        config.dim_3 = 8 : ui32,
+        config.dtype = "bfloat16",
+        config.perm = 6 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x672x1x240xbf16> loc(#loc338)
+      xten_nn.output %464 : tensor<1x672x1x240xbf16> loc(#loc338)
+    } -> tensor<1x672x1x240xbf16> loc(#loc338)
+    %316 = xten_nn.subgraph (%arg5 = %315: tensor<1x672x1x240xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#38",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 56, 1, 32]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 1, 240]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 1, 240]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#39",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 56, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 86256 : ui64, ofm = 10992 : ui64},
+        computation_cycles = 81517 : ui64,
+        cycle_count = 86256 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x672x1x240xbf16>)  attributes {
+        LayerName = "Generated-#38",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 1, 240]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Generated-#39",
+        PadValue = 0.000000e+00 : bf16,
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ReduceMeanC8Bf16",
+        Traits = {
+          Reduce = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.full_channel = 672 : ui32,
+          config.full_height = 1 : ui32,
+          config.full_width = 240 : ui32,
+          config.reduce_dim = "W",
+          config.sv_channel = 56 : ui32,
+          config.sv_height = 1 : ui32,
+          config.sv_width = 32 : ui32
+        },
+        estimation = {
+          compute_cycles = 2285 : ui64,
+          startup_cycles = 190 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x1x1xbf16> loc(#loc170)
+        xten_nn.output %465 : tensor<1x672x1x1xbf16> loc(#loc170)
+      } -> tensor<1x672x1x1xbf16> loc(#loc170)
+      xten_nn.output %464 : tensor<1x672x1x1xbf16> loc(#loc170)
+    } -> tensor<1x672x1x1xbf16> loc(#loc170)
+    %317 = xten_nn.subgraph (%arg5 = %316: tensor<1x672x1x1xbf16>, %arg6 = %63: tensor<168x672x1x1xbf16>, %arg7 = %62: tensor<168xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_255",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 7]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 96, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[48, 96, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[24, 0, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[168, 672, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[24, 0, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[168, 672, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Relu_256",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 7]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 48, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 0, 31]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 168, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 168, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 2758 : ui64, ofm = 906 : ui64, wts = 17542 : ui64},
+        computation_cycles = 10332 : ui64,
+        cycle_count = 17542 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[3, 1, 2, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x672x1x1xbf16>, %arg9 = %arg6: tensor<168x672x1x1xbf16>, %arg10 = %arg7: tensor<168xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_255",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[168, 672, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Relu_256",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 168, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true,
+          NonNegativeOut = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 1 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 12 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 96 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 8 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 0.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 0.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 7 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 48 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 8 : ui8
+        },
+        estimation = {
+          compute_cycles = 9030 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x168x1x1xbf16> loc(#loc172)
+        xten_nn.output %465 : tensor<1x168x1x1xbf16> loc(#loc172)
+      } -> tensor<1x168x1x1xbf16> loc(#loc339)
+      xten_nn.output %464 : tensor<1x168x1x1xbf16> loc(#loc339)
+    } -> tensor<1x168x1x1xbf16> loc(#loc339)
+    %318 = xten_nn.subgraph (%arg5 = %317: tensor<1x168x1x1xbf16>, %arg6 = %61: tensor<672x168x1x1xbf16>, %arg7 = %60: tensor<672xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_257",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 15]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 168, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 0, 31]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 168, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 168, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[16, 168, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[32, 0, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[672, 168, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[32, 0, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[672, 168, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_257",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 15]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 63]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 1354 : ui64, ofm = 8558 : ui64, wts = 15598 : ui64},
+        computation_cycles = 16150 : ui64,
+        cycle_count = 16150 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[3, 1, 2, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x168x1x1xbf16>, %arg9 = %arg6: tensor<672x168x1x1xbf16>, %arg10 = %arg7: tensor<672xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_257",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 168, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[672, 168, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_257",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 12 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 168 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 16 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 1 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 16 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 16 : ui8
+        },
+        estimation = {
+          compute_cycles = 1300 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x1x1xbf16> loc(#loc173)
+        xten_nn.output %465 : tensor<1x672x1x1xbf16> loc(#loc173)
+      } -> tensor<1x672x1x1xbf16> loc(#loc173)
+      xten_nn.output %464 : tensor<1x672x1x1xbf16> loc(#loc173)
+    } -> tensor<1x672x1x1xbf16> loc(#loc173)
+    %319 = xten_nn.subgraph (%arg5 = %318: tensor<1x672x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_259",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 1, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 192, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 63]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_259",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 1, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 192, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 96, 7, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 778 : ui64, ofm = 394 : ui64},
+        computation_cycles = 401 : ui64,
+        cycle_count = 778 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x672x1x1xbf16>)  attributes {
+        LayerName = "Add_259",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_259",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 192 : ui32,
+          config.ifmsv_height = 2 : ui32,
+          config.ifmsv_width = 1 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 35 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x1x1xbf16> loc(#loc174)
+        xten_nn.output %465 : tensor<1x672x1x1xbf16> loc(#loc174)
+      } -> tensor<1x672x1x1xbf16> loc(#loc174)
+      xten_nn.output %464 : tensor<1x672x1x1xbf16> loc(#loc174)
+    } -> tensor<1x672x1x1xbf16> loc(#loc174)
+    %320 = xten_nn.subgraph (%arg5 = %319: tensor<1x672x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_262",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 256, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 96, 7, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_262",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 256, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 352, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 522 : ui64, ofm = 266 : ui64},
+        computation_cycles = 395 : ui64,
+        cycle_count = 522 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x672x1x1xbf16>)  attributes {
+        LayerName = "Clip_262",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_262",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 256 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 1 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 35 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x1x1xbf16> loc(#loc175)
+        xten_nn.output %465 : tensor<1x672x1x1xbf16> loc(#loc175)
+      } -> tensor<1x672x1x1xbf16> loc(#loc175)
+      xten_nn.output %464 : tensor<1x672x1x1xbf16> loc(#loc175)
+    } -> tensor<1x672x1x1xbf16> loc(#loc175)
+    %321 = xten_nn.subgraph (%arg5 = %320: tensor<1x672x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_264",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 1, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 256, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 352, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_264",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 1, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 256, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 352, 7, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 1034 : ui64, ofm = 522 : ui64},
+        computation_cycles = 409 : ui64,
+        cycle_count = 1034 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x672x1x1xbf16>)  attributes {
+        LayerName = "Div_264",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_264",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 256 : ui32,
+          config.ifmsv_height = 2 : ui32,
+          config.ifmsv_width = 1 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 43 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x1x1xbf16> loc(#loc176)
+        xten_nn.output %465 : tensor<1x672x1x1xbf16> loc(#loc176)
+      } -> tensor<1x672x1x1xbf16> loc(#loc176)
+      xten_nn.output %464 : tensor<1x672x1x1xbf16> loc(#loc176)
+    } -> tensor<1x672x1x1xbf16> loc(#loc176)
+    %322 = xten_nn.subgraph (%arg5 = %321: tensor<1x672x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#40",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#41",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      Specializes = "TileAdf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.dtype = "bfloat16",
+        config.i_dim_c = 672 : ui32,
+        config.i_dim_h = 1 : ui32,
+        config.i_dim_n = 1 : ui32,
+        config.i_dim_w = 1 : ui32,
+        config.rep_dim_c = 1 : ui32,
+        config.rep_dim_h = 12 : ui32,
+        config.rep_dim_w = 20 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x672x12x20xbf16> loc(#loc177)
+      xten_nn.output %464 : tensor<1x672x12x20xbf16> loc(#loc177)
+    } -> tensor<1x672x12x20xbf16> loc(#loc177)
+    %323 = xten_nn.subgraph (%arg5 = %322: tensor<1x672x12x20xbf16>, %arg6 = %314: tensor<1x672x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_265",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_265",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 21230 : ui64, ifm2 = 21230 : ui64, ofm = 10670 : ui64},
+        computation_cycles = 2199 : ui64,
+        cycle_count = 21230 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x672x12x20xbf16>, %arg8 = %arg6: tensor<1x672x12x20xbf16>)  attributes {
+        LayerName = "Mul_265",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_265",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x672x12x20xbf16> loc(#loc177)
+        xten_nn.output %465 : tensor<1x672x12x20xbf16> loc(#loc177)
+      } -> tensor<1x672x12x20xbf16> loc(#loc177)
+      xten_nn.output %464 : tensor<1x672x12x20xbf16> loc(#loc177)
+    } -> tensor<1x672x12x20xbf16> loc(#loc177)
+    %324 = xten_nn.subgraph (%arg5 = %323: tensor<1x672x12x20xbf16>, %arg6 = %59: tensor<160x672x1x1xbf16>, %arg7 = %58: tensor<160xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_266",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[40, 80, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 48, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[160, 672, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 48, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[160, 672, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_266",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 40, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 34830 : ui64, ofm = 4638 : ui64, wts = 15930 : ui64},
+        computation_cycles = 47156 : ui64,
+        cycle_count = 47156 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x672x12x20xbf16>, %arg9 = %arg6: tensor<160x672x1x1xbf16>, %arg10 = %arg7: tensor<160xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_266",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 672, 12, 20]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[160, 672, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_266",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 80 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 32 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 9 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 40 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 14364 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x160x12x20xbf16> loc(#loc178)
+        xten_nn.output %465 : tensor<1x160x12x20xbf16> loc(#loc178)
+      } -> tensor<1x160x12x20xbf16> loc(#loc178)
+      xten_nn.output %464 : tensor<1x160x12x20xbf16> loc(#loc178)
+    } -> tensor<1x160x12x20xbf16> loc(#loc178)
+    %325 = xten_nn.subgraph (%arg5 = %324: tensor<1x160x12x20xbf16>, %arg6 = %57: tensor<960x160x1x1xbf16>, %arg7 = %56: tensor<960xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_267",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[40, 80, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[960, 160, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[960, 160, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_267",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 40, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 7740 : ui64, ofm = 27828 : ui64, wts = 21240 : ui64},
+        computation_cycles = 62753 : ui64,
+        cycle_count = 62753 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x160x12x20xbf16>, %arg9 = %arg6: tensor<960x160x1x1xbf16>, %arg10 = %arg7: tensor<960xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_267",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[960, 160, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_267",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 80 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 32 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 2 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 40 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 3192 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc179)
+        xten_nn.output %465 : tensor<1x960x12x20xbf16> loc(#loc179)
+      } -> tensor<1x960x12x20xbf16> loc(#loc179)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc179)
+    } -> tensor<1x960x12x20xbf16> loc(#loc179)
+    %326 = xten_nn.subgraph (%arg5 = %325: tensor<1x960x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_269",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_269",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 28890 : ui64, ofm = 14490 : ui64},
+        computation_cycles = 2461 : ui64,
+        cycle_count = 28890 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x960x12x20xbf16>)  attributes {
+        LayerName = "Add_269",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_269",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 80 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 111 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc180)
+        xten_nn.output %465 : tensor<1x960x12x20xbf16> loc(#loc180)
+      } -> tensor<1x960x12x20xbf16> loc(#loc180)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc180)
+    } -> tensor<1x960x12x20xbf16> loc(#loc180)
+    %327 = xten_nn.subgraph (%arg5 = %326: tensor<1x960x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_272",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_272",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 28890 : ui64, ofm = 14490 : ui64},
+        computation_cycles = 2527 : ui64,
+        cycle_count = 28890 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x960x12x20xbf16>)  attributes {
+        LayerName = "Clip_272",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_272",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 80 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 119 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc181)
+        xten_nn.output %465 : tensor<1x960x12x20xbf16> loc(#loc181)
+      } -> tensor<1x960x12x20xbf16> loc(#loc181)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc181)
+    } -> tensor<1x960x12x20xbf16> loc(#loc181)
+    %328 = xten_nn.subgraph (%arg5 = %327: tensor<1x960x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_274",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_274",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 28890 : ui64, ofm = 14490 : ui64},
+        computation_cycles = 2461 : ui64,
+        cycle_count = 28890 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x960x12x20xbf16>)  attributes {
+        LayerName = "Div_274",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_274",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 80 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 111 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc182)
+        xten_nn.output %465 : tensor<1x960x12x20xbf16> loc(#loc182)
+      } -> tensor<1x960x12x20xbf16> loc(#loc182)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc182)
+    } -> tensor<1x960x12x20xbf16> loc(#loc182)
+    %329 = xten_nn.subgraph (%arg5 = %325: tensor<1x960x12x20xbf16>, %arg6 = %328: tensor<1x960x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_275",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 24, 2, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_force_single_buffering = true,
+          l2_tile_count = dense<[1, 960, 6, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 24, 2, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_force_single_buffering = true,
+          l2_tile_count = dense<[1, 960, 6, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_275",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 24, 2, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 2, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_force_single_buffering = true,
+          l2_tile_count = dense<[1, 960, 6, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 38600 : ui64, ifm2 = 38600 : ui64, ofm = 19400 : ui64},
+        computation_cycles = 3828 : ui64,
+        cycle_count = 77200 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x960x12x20xbf16>, %arg8 = %arg6: tensor<1x960x12x20xbf16>)  attributes {
+        LayerName = "Mul_275",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_275",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 24 : ui32,
+          config.ifmsv_height = 2 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc183)
+        xten_nn.output %465 : tensor<1x960x12x20xbf16> loc(#loc183)
+      } -> tensor<1x960x12x20xbf16> loc(#loc183)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc183)
+    } -> tensor<1x960x12x20xbf16> loc(#loc183)
+    %330 = xten_nn.subgraph (%arg5 = %329: tensor<1x960x12x20xbf16>, %arg6 = %55: tensor<960x1x9x9xbf16>, %arg7 = %54: tensor<960xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_276",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 10, 16]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "CMHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 3]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[8, 1, 9, 9]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 3]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[960, 1, 9, 9]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 0, 0, 3]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[960, 1, 9, 9]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_276",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 2, 8]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 4, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 462600 : ui64, ofm = 24840 : ui64, wts = 13740 : ui64},
+        computation_cycles = 157893 : ui64,
+        cycle_count = 462600 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 4, 3, 0]> : vector<4xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x960x12x20xbf16>, %arg9 = %arg6: tensor<960x1x9x9xbf16>, %arg10 = %arg7: tensor<960xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[4, 4], [4, 4]],
+        LayerName = "Conv_276",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "CMHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[960, 1, 9, 9]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_276",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "DepthwiseConv2dBf16",
+        With = {
+          config.act = 0 : ui8,
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.ifm_sv_depth.size = 8 : ui8,
+          config.ifm_sv_height.size = 10 : ui8,
+          config.ifm_sv_width.size = 16 : ui8,
+          config.kernel_height = 9 : ui8,
+          config.kernel_width = 9 : ui8,
+          config.stride = 1 : ui8,
+          data_io.ifm.dimensions.batch.padding = 0 : ui8,
+          data_io.ifm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.batch.padding = 0 : ui8,
+          data_io.ofm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.width.padding = 0 : ui8
+        },
+        estimation = {
+          compute_cycles = 739 : ui64,
+          startup_cycles = 30 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc184)
+        xten_nn.output %465 : tensor<1x960x12x20xbf16> loc(#loc184)
+      } -> tensor<1x960x12x20xbf16> loc(#loc184)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc184)
+    } -> tensor<1x960x12x20xbf16> loc(#loc184)
+    %331 = xten_nn.subgraph (%arg5 = %330: tensor<1x960x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_278",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 4, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_278",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 28890 : ui64, ofm = 14490 : ui64},
+        computation_cycles = 2461 : ui64,
+        cycle_count = 28890 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x960x12x20xbf16>)  attributes {
+        LayerName = "Add_278",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_278",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 80 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 111 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc185)
+        xten_nn.output %465 : tensor<1x960x12x20xbf16> loc(#loc185)
+      } -> tensor<1x960x12x20xbf16> loc(#loc185)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc185)
+    } -> tensor<1x960x12x20xbf16> loc(#loc185)
+    %332 = xten_nn.subgraph (%arg5 = %331: tensor<1x960x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_281",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_281",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 28890 : ui64, ofm = 14490 : ui64},
+        computation_cycles = 2527 : ui64,
+        cycle_count = 28890 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x960x12x20xbf16>)  attributes {
+        LayerName = "Clip_281",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_281",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 80 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 119 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc186)
+        xten_nn.output %465 : tensor<1x960x12x20xbf16> loc(#loc186)
+      } -> tensor<1x960x12x20xbf16> loc(#loc186)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc186)
+    } -> tensor<1x960x12x20xbf16> loc(#loc186)
+    %333 = xten_nn.subgraph (%arg5 = %332: tensor<1x960x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_283",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_283",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 28890 : ui64, ofm = 14490 : ui64},
+        computation_cycles = 2461 : ui64,
+        cycle_count = 28890 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x960x12x20xbf16>)  attributes {
+        LayerName = "Div_283",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_283",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 80 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 111 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc187)
+        xten_nn.output %465 : tensor<1x960x12x20xbf16> loc(#loc187)
+      } -> tensor<1x960x12x20xbf16> loc(#loc187)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc187)
+    } -> tensor<1x960x12x20xbf16> loc(#loc187)
+    %334 = xten_nn.subgraph (%arg5 = %330: tensor<1x960x12x20xbf16>, %arg6 = %333: tensor<1x960x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_284",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 24, 2, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_force_single_buffering = true,
+          l2_tile_count = dense<[1, 960, 6, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 24, 2, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_force_single_buffering = true,
+          l2_tile_count = dense<[1, 960, 6, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_284",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 24, 2, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 2, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_force_single_buffering = true,
+          l2_tile_count = dense<[1, 960, 6, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 38600 : ui64, ifm2 = 38600 : ui64, ofm = 19400 : ui64},
+        computation_cycles = 3828 : ui64,
+        cycle_count = 77200 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x960x12x20xbf16>, %arg8 = %arg6: tensor<1x960x12x20xbf16>)  attributes {
+        LayerName = "Mul_284",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_284",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 24 : ui32,
+          config.ifmsv_height = 2 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc188)
+        xten_nn.output %465 : tensor<1x960x12x20xbf16> loc(#loc188)
+      } -> tensor<1x960x12x20xbf16> loc(#loc188)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc188)
+    } -> tensor<1x960x12x20xbf16> loc(#loc188)
+    %335 = xten_nn.subgraph (%arg5 = %334: tensor<1x960x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#42",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#43",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 240]> : vector<4xindex>
+        }
+      ],
+      Specializes = "Transpose4dAdf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.dim_0 = 12 : ui32,
+        config.dim_1 = 120 : ui32,
+        config.dim_2 = 20 : ui32,
+        config.dim_3 = 8 : ui32,
+        config.dtype = "bfloat16",
+        config.perm = 6 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x960x1x240xbf16> loc(#loc340)
+      xten_nn.output %464 : tensor<1x960x1x240xbf16> loc(#loc340)
+    } -> tensor<1x960x1x240xbf16> loc(#loc340)
+    %336 = xten_nn.subgraph (%arg5 = %335: tensor<1x960x1x240xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#44",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 40, 1, 48]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 1, 240]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 240]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#45",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 40, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 115500 : ui64, ofm = 9900 : ui64},
+        computation_cycles = 90253 : ui64,
+        cycle_count = 115500 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x960x1x240xbf16>)  attributes {
+        LayerName = "Generated-#44",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 1, 240]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Generated-#45",
+        PadValue = 0.000000e+00 : bf16,
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ReduceMeanC8Bf16",
+        Traits = {
+          Reduce = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.full_channel = 960 : ui32,
+          config.full_height = 1 : ui32,
+          config.full_width = 240 : ui32,
+          config.reduce_dim = "W",
+          config.sv_channel = 40 : ui32,
+          config.sv_height = 1 : ui32,
+          config.sv_width = 48 : ui32
+        },
+        estimation = {
+          compute_cycles = 2311 : ui64,
+          startup_cycles = 190 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x1x1xbf16> loc(#loc189)
+        xten_nn.output %465 : tensor<1x960x1x1xbf16> loc(#loc189)
+      } -> tensor<1x960x1x1xbf16> loc(#loc189)
+      xten_nn.output %464 : tensor<1x960x1x1xbf16> loc(#loc189)
+    } -> tensor<1x960x1x1xbf16> loc(#loc189)
+    %337 = xten_nn.subgraph (%arg5 = %336: tensor<1x960x1x1xbf16>, %arg6 = %53: tensor<240x960x1x1xbf16>, %arg7 = %52: tensor<240xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_286",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 15]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 192, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[16, 192, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[16, 0, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[240, 960, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[16, 0, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[240, 960, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Relu_287",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 15]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 63]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 240, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 7730 : ui64, ofm = 3112 : ui64, wts = 32200 : ui64},
+        computation_cycles = 31903 : ui64,
+        cycle_count = 32200 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[3, 1, 2, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x960x1x1xbf16>, %arg9 = %arg6: tensor<240x960x1x1xbf16>, %arg10 = %arg7: tensor<240xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_286",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[240, 960, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Relu_287",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 240, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true,
+          NonNegativeOut = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 1 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 12 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 192 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 16 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 0.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 0.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 5 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 16 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 16 : ui8
+        },
+        estimation = {
+          compute_cycles = 7205 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x240x1x1xbf16> loc(#loc191)
+        xten_nn.output %465 : tensor<1x240x1x1xbf16> loc(#loc191)
+      } -> tensor<1x240x1x1xbf16> loc(#loc341)
+      xten_nn.output %464 : tensor<1x240x1x1xbf16> loc(#loc341)
+    } -> tensor<1x240x1x1xbf16> loc(#loc341)
+    %338 = xten_nn.subgraph (%arg5 = %337: tensor<1x240x1x1xbf16>, %arg6 = %51: tensor<960x240x1x1xbf16>, %arg7 = %50: tensor<960xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_288",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 7]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 80, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 63]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 240, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[48, 80, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[960, 240, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[960, 240, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_288",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 7]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 48, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 31]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 990 : ui64, ofm = 4530 : ui64, wts = 31830 : ui64},
+        computation_cycles = 19498 : ui64,
+        cycle_count = 31830 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[3, 1, 2, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x240x1x1xbf16>, %arg9 = %arg6: tensor<960x240x1x1xbf16>, %arg10 = %arg7: tensor<960xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_288",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 240, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[960, 240, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_288",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 12 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 80 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 8 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 3 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 48 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 8 : ui8
+        },
+        estimation = {
+          compute_cycles = 3420 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x1x1xbf16> loc(#loc192)
+        xten_nn.output %465 : tensor<1x960x1x1xbf16> loc(#loc192)
+      } -> tensor<1x960x1x1xbf16> loc(#loc192)
+      xten_nn.output %464 : tensor<1x960x1x1xbf16> loc(#loc192)
+    } -> tensor<1x960x1x1xbf16> loc(#loc192)
+    %339 = xten_nn.subgraph (%arg5 = %338: tensor<1x960x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_290",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 384, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 31]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_290",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 384, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 576, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 778 : ui64, ofm = 394 : ui64},
+        computation_cycles = 401 : ui64,
+        cycle_count = 778 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x960x1x1xbf16>)  attributes {
+        LayerName = "Add_290",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_290",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 384 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 1 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 35 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x1x1xbf16> loc(#loc193)
+        xten_nn.output %465 : tensor<1x960x1x1xbf16> loc(#loc193)
+      } -> tensor<1x960x1x1xbf16> loc(#loc193)
+      xten_nn.output %464 : tensor<1x960x1x1xbf16> loc(#loc193)
+    } -> tensor<1x960x1x1xbf16> loc(#loc193)
+    %340 = xten_nn.subgraph (%arg5 = %339: tensor<1x960x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_293",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 256, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 576, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_293",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 256, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 64, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 522 : ui64, ofm = 266 : ui64},
+        computation_cycles = 395 : ui64,
+        cycle_count = 522 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x960x1x1xbf16>)  attributes {
+        LayerName = "Clip_293",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_293",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 256 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 1 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 35 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x1x1xbf16> loc(#loc194)
+        xten_nn.output %465 : tensor<1x960x1x1xbf16> loc(#loc194)
+      } -> tensor<1x960x1x1xbf16> loc(#loc194)
+      xten_nn.output %464 : tensor<1x960x1x1xbf16> loc(#loc194)
+    } -> tensor<1x960x1x1xbf16> loc(#loc194)
+    %341 = xten_nn.subgraph (%arg5 = %340: tensor<1x960x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_295",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 1, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 256, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 64, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_295",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 1, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 256, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 64, 7, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 1034 : ui64, ofm = 522 : ui64},
+        computation_cycles = 409 : ui64,
+        cycle_count = 1034 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x960x1x1xbf16>)  attributes {
+        LayerName = "Div_295",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_295",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 256 : ui32,
+          config.ifmsv_height = 2 : ui32,
+          config.ifmsv_width = 1 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 43 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x1x1xbf16> loc(#loc195)
+        xten_nn.output %465 : tensor<1x960x1x1xbf16> loc(#loc195)
+      } -> tensor<1x960x1x1xbf16> loc(#loc195)
+      xten_nn.output %464 : tensor<1x960x1x1xbf16> loc(#loc195)
+    } -> tensor<1x960x1x1xbf16> loc(#loc195)
+    %342 = xten_nn.subgraph (%arg5 = %341: tensor<1x960x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#46",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#47",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      Specializes = "TileAdf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.dtype = "bfloat16",
+        config.i_dim_c = 960 : ui32,
+        config.i_dim_h = 1 : ui32,
+        config.i_dim_n = 1 : ui32,
+        config.i_dim_w = 1 : ui32,
+        config.rep_dim_c = 1 : ui32,
+        config.rep_dim_h = 12 : ui32,
+        config.rep_dim_w = 20 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc196)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc196)
+    } -> tensor<1x960x12x20xbf16> loc(#loc196)
+    %343 = xten_nn.subgraph (%arg5 = %342: tensor<1x960x12x20xbf16>, %arg6 = %334: tensor<1x960x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_296",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_296",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 28950 : ui64, ifm2 = 28950 : ui64, ofm = 14550 : ui64},
+        computation_cycles = 2923 : ui64,
+        cycle_count = 28950 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x960x12x20xbf16>, %arg8 = %arg6: tensor<1x960x12x20xbf16>)  attributes {
+        LayerName = "Mul_296",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_296",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc196)
+        xten_nn.output %465 : tensor<1x960x12x20xbf16> loc(#loc196)
+      } -> tensor<1x960x12x20xbf16> loc(#loc196)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc196)
+    } -> tensor<1x960x12x20xbf16> loc(#loc196)
+    %344 = xten_nn.subgraph (%arg5 = %343: tensor<1x960x12x20xbf16>, %arg6 = %49: tensor<160x960x1x1xbf16>, %arg7 = %48: tensor<160xbf16>, %arg8 = %324: tensor<1x160x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 3 : index],
+      LayerName = "Conv_297",
+      OfmShare = 3 : index,
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 112, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[24, 112, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[32, 48, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[160, 960, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[32, 48, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[160, 960, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 24, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_298",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 24, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 48654 : ui64, ifm2 = 9276 : ui64, ofm = 4668 : ui64, wts = 26100 : ui64},
+        computation_cycles = 89679 : ui64,
+        cycle_count = 89679 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg9 = %arg5: tensor<1x960x12x20xbf16>, %arg10 = %arg6: tensor<160x960x1x1xbf16>, %arg11 = %arg7: tensor<160xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_297",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[160, 960, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_297",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 112 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 32 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 9 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 24 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 13590 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %466 = tensor.empty() : tensor<1x160x12x20xbf16> loc(#loc197)
+        xten_nn.output %466 : tensor<1x160x12x20xbf16> loc(#loc197)
+      } -> tensor<1x160x12x20xbf16> loc(#loc197)
+      %465 = xten_nn.subgraph (%arg9 = %464: tensor<1x160x12x20xbf16>, %arg10 = %arg8: tensor<1x160x12x20xbf16>)  attributes {
+        LayerName = "Add_298",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_298",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.act = 0 : ui8,
+          config.act_type = "LINEAR",
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 24 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 32 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 59 : ui64,
+          startup_cycles = 22 : ui64
+        }} {
+        %466 = tensor.empty() : tensor<1x160x12x20xbf16> loc(#loc198)
+        xten_nn.output %466 : tensor<1x160x12x20xbf16> loc(#loc198)
+      } -> tensor<1x160x12x20xbf16> loc(#loc198)
+      xten_nn.output %465 : tensor<1x160x12x20xbf16> loc(#loc198)
+    } -> tensor<1x160x12x20xbf16> loc(#loc342)
+    %345 = xten_nn.subgraph (%arg5 = %344: tensor<1x160x12x20xbf16>, %arg6 = %47: tensor<960x160x1x1xbf16>, %arg7 = %46: tensor<960xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_299",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[40, 80, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[960, 160, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[960, 160, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_299",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 40, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 7740 : ui64, ofm = 27828 : ui64, wts = 21240 : ui64},
+        computation_cycles = 62753 : ui64,
+        cycle_count = 62753 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x160x12x20xbf16>, %arg9 = %arg6: tensor<960x160x1x1xbf16>, %arg10 = %arg7: tensor<960xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_299",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[960, 160, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_299",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 80 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 32 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 2 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 40 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 3192 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc199)
+        xten_nn.output %465 : tensor<1x960x12x20xbf16> loc(#loc199)
+      } -> tensor<1x960x12x20xbf16> loc(#loc199)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc199)
+    } -> tensor<1x960x12x20xbf16> loc(#loc199)
+    %346 = xten_nn.subgraph (%arg5 = %345: tensor<1x960x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_301",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_301",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 28890 : ui64, ofm = 14490 : ui64},
+        computation_cycles = 2461 : ui64,
+        cycle_count = 28890 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x960x12x20xbf16>)  attributes {
+        LayerName = "Add_301",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_301",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 80 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 111 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc200)
+        xten_nn.output %465 : tensor<1x960x12x20xbf16> loc(#loc200)
+      } -> tensor<1x960x12x20xbf16> loc(#loc200)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc200)
+    } -> tensor<1x960x12x20xbf16> loc(#loc200)
+    %347 = xten_nn.subgraph (%arg5 = %346: tensor<1x960x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_304",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_304",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 28890 : ui64, ofm = 14490 : ui64},
+        computation_cycles = 2527 : ui64,
+        cycle_count = 28890 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x960x12x20xbf16>)  attributes {
+        LayerName = "Clip_304",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_304",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 80 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 119 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc201)
+        xten_nn.output %465 : tensor<1x960x12x20xbf16> loc(#loc201)
+      } -> tensor<1x960x12x20xbf16> loc(#loc201)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc201)
+    } -> tensor<1x960x12x20xbf16> loc(#loc201)
+    %348 = xten_nn.subgraph (%arg5 = %347: tensor<1x960x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_306",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_306",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 28890 : ui64, ofm = 14490 : ui64},
+        computation_cycles = 2461 : ui64,
+        cycle_count = 28890 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x960x12x20xbf16>)  attributes {
+        LayerName = "Div_306",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_306",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 80 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 111 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc202)
+        xten_nn.output %465 : tensor<1x960x12x20xbf16> loc(#loc202)
+      } -> tensor<1x960x12x20xbf16> loc(#loc202)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc202)
+    } -> tensor<1x960x12x20xbf16> loc(#loc202)
+    %349 = xten_nn.subgraph (%arg5 = %345: tensor<1x960x12x20xbf16>, %arg6 = %348: tensor<1x960x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_307",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 24, 2, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_force_single_buffering = true,
+          l2_tile_count = dense<[1, 960, 6, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 24, 2, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_force_single_buffering = true,
+          l2_tile_count = dense<[1, 960, 6, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_307",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 24, 2, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 2, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_force_single_buffering = true,
+          l2_tile_count = dense<[1, 960, 6, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 38600 : ui64, ifm2 = 38600 : ui64, ofm = 19400 : ui64},
+        computation_cycles = 3828 : ui64,
+        cycle_count = 77200 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x960x12x20xbf16>, %arg8 = %arg6: tensor<1x960x12x20xbf16>)  attributes {
+        LayerName = "Mul_307",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_307",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 24 : ui32,
+          config.ifmsv_height = 2 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc203)
+        xten_nn.output %465 : tensor<1x960x12x20xbf16> loc(#loc203)
+      } -> tensor<1x960x12x20xbf16> loc(#loc203)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc203)
+    } -> tensor<1x960x12x20xbf16> loc(#loc203)
+    %350 = xten_nn.subgraph (%arg5 = %349: tensor<1x960x12x20xbf16>, %arg6 = %45: tensor<960x1x9x9xbf16>, %arg7 = %44: tensor<960xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_308",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 10, 16]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "CMHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 3]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[8, 1, 9, 9]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 3]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[960, 1, 9, 9]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 0, 0, 3]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[960, 1, 9, 9]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_308",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 2, 8]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 4, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 462600 : ui64, ofm = 24840 : ui64, wts = 13740 : ui64},
+        computation_cycles = 157893 : ui64,
+        cycle_count = 462600 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 4, 3, 0]> : vector<4xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x960x12x20xbf16>, %arg9 = %arg6: tensor<960x1x9x9xbf16>, %arg10 = %arg7: tensor<960xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[4, 4], [4, 4]],
+        LayerName = "Conv_308",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "CMHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[960, 1, 9, 9]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_308",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "DepthwiseConv2dBf16",
+        With = {
+          config.act = 0 : ui8,
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.ifm_sv_depth.size = 8 : ui8,
+          config.ifm_sv_height.size = 10 : ui8,
+          config.ifm_sv_width.size = 16 : ui8,
+          config.kernel_height = 9 : ui8,
+          config.kernel_width = 9 : ui8,
+          config.stride = 1 : ui8,
+          data_io.ifm.dimensions.batch.padding = 0 : ui8,
+          data_io.ifm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.batch.padding = 0 : ui8,
+          data_io.ofm.dimensions.batch.size = 1 : ui8,
+          data_io.ofm.dimensions.width.padding = 0 : ui8
+        },
+        estimation = {
+          compute_cycles = 739 : ui64,
+          startup_cycles = 30 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc204)
+        xten_nn.output %465 : tensor<1x960x12x20xbf16> loc(#loc204)
+      } -> tensor<1x960x12x20xbf16> loc(#loc204)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc204)
+    } -> tensor<1x960x12x20xbf16> loc(#loc204)
+    %351 = xten_nn.subgraph (%arg5 = %350: tensor<1x960x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_310",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 4, 4]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_310",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 28890 : ui64, ofm = 14490 : ui64},
+        computation_cycles = 2461 : ui64,
+        cycle_count = 28890 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x960x12x20xbf16>)  attributes {
+        LayerName = "Add_310",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_310",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 80 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 111 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc205)
+        xten_nn.output %465 : tensor<1x960x12x20xbf16> loc(#loc205)
+      } -> tensor<1x960x12x20xbf16> loc(#loc205)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc205)
+    } -> tensor<1x960x12x20xbf16> loc(#loc205)
+    %352 = xten_nn.subgraph (%arg5 = %351: tensor<1x960x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_313",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_313",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 28890 : ui64, ofm = 14490 : ui64},
+        computation_cycles = 2527 : ui64,
+        cycle_count = 28890 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x960x12x20xbf16>)  attributes {
+        LayerName = "Clip_313",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_313",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 80 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 119 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc206)
+        xten_nn.output %465 : tensor<1x960x12x20xbf16> loc(#loc206)
+      } -> tensor<1x960x12x20xbf16> loc(#loc206)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc206)
+    } -> tensor<1x960x12x20xbf16> loc(#loc206)
+    %353 = xten_nn.subgraph (%arg5 = %352: tensor<1x960x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_315",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_315",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 28890 : ui64, ofm = 14490 : ui64},
+        computation_cycles = 2461 : ui64,
+        cycle_count = 28890 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x960x12x20xbf16>)  attributes {
+        LayerName = "Div_315",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_315",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 80 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 111 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc207)
+        xten_nn.output %465 : tensor<1x960x12x20xbf16> loc(#loc207)
+      } -> tensor<1x960x12x20xbf16> loc(#loc207)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc207)
+    } -> tensor<1x960x12x20xbf16> loc(#loc207)
+    %354 = xten_nn.subgraph (%arg5 = %350: tensor<1x960x12x20xbf16>, %arg6 = %353: tensor<1x960x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_316",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 24, 2, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_force_single_buffering = true,
+          l2_tile_count = dense<[1, 960, 6, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 24, 2, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_force_single_buffering = true,
+          l2_tile_count = dense<[1, 960, 6, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_316",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 24, 2, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 2, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_force_single_buffering = true,
+          l2_tile_count = dense<[1, 960, 6, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 38600 : ui64, ifm2 = 38600 : ui64, ofm = 19400 : ui64},
+        computation_cycles = 3828 : ui64,
+        cycle_count = 77200 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x960x12x20xbf16>, %arg8 = %arg6: tensor<1x960x12x20xbf16>)  attributes {
+        LayerName = "Mul_316",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_316",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 24 : ui32,
+          config.ifmsv_height = 2 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc208)
+        xten_nn.output %465 : tensor<1x960x12x20xbf16> loc(#loc208)
+      } -> tensor<1x960x12x20xbf16> loc(#loc208)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc208)
+    } -> tensor<1x960x12x20xbf16> loc(#loc208)
+    %355 = xten_nn.subgraph (%arg5 = %354: tensor<1x960x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#48",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#49",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 240]> : vector<4xindex>
+        }
+      ],
+      Specializes = "Transpose4dAdf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.dim_0 = 12 : ui32,
+        config.dim_1 = 120 : ui32,
+        config.dim_2 = 20 : ui32,
+        config.dim_3 = 8 : ui32,
+        config.dtype = "bfloat16",
+        config.perm = 6 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x960x1x240xbf16> loc(#loc343)
+      xten_nn.output %464 : tensor<1x960x1x240xbf16> loc(#loc343)
+    } -> tensor<1x960x1x240xbf16> loc(#loc343)
+    %356 = xten_nn.subgraph (%arg5 = %355: tensor<1x960x1x240xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#50",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 40, 1, 48]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 1, 240]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 240]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#51",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 40, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 115500 : ui64, ofm = 9900 : ui64},
+        computation_cycles = 90253 : ui64,
+        cycle_count = 115500 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x960x1x240xbf16>)  attributes {
+        LayerName = "Generated-#50",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 1, 240]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Generated-#51",
+        PadValue = 0.000000e+00 : bf16,
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ReduceMeanC8Bf16",
+        Traits = {
+          Reduce = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.full_channel = 960 : ui32,
+          config.full_height = 1 : ui32,
+          config.full_width = 240 : ui32,
+          config.reduce_dim = "W",
+          config.sv_channel = 40 : ui32,
+          config.sv_height = 1 : ui32,
+          config.sv_width = 48 : ui32
+        },
+        estimation = {
+          compute_cycles = 2311 : ui64,
+          startup_cycles = 190 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x1x1xbf16> loc(#loc209)
+        xten_nn.output %465 : tensor<1x960x1x1xbf16> loc(#loc209)
+      } -> tensor<1x960x1x1xbf16> loc(#loc209)
+      xten_nn.output %464 : tensor<1x960x1x1xbf16> loc(#loc209)
+    } -> tensor<1x960x1x1xbf16> loc(#loc209)
+    %357 = xten_nn.subgraph (%arg5 = %356: tensor<1x960x1x1xbf16>, %arg6 = %43: tensor<240x960x1x1xbf16>, %arg7 = %42: tensor<240xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_318",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 15]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 192, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[16, 192, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[16, 0, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[240, 960, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[16, 0, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[240, 960, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Relu_319",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 15]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 63]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 240, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 7730 : ui64, ofm = 3112 : ui64, wts = 32200 : ui64},
+        computation_cycles = 31903 : ui64,
+        cycle_count = 32200 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[3, 1, 2, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x960x1x1xbf16>, %arg9 = %arg6: tensor<240x960x1x1xbf16>, %arg10 = %arg7: tensor<240xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_318",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[240, 960, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Relu_319",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 240, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true,
+          NonNegativeOut = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 1 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 12 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 192 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 16 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 0.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 0.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 5 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 16 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 16 : ui8
+        },
+        estimation = {
+          compute_cycles = 7205 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x240x1x1xbf16> loc(#loc211)
+        xten_nn.output %465 : tensor<1x240x1x1xbf16> loc(#loc211)
+      } -> tensor<1x240x1x1xbf16> loc(#loc344)
+      xten_nn.output %464 : tensor<1x240x1x1xbf16> loc(#loc344)
+    } -> tensor<1x240x1x1xbf16> loc(#loc344)
+    %358 = xten_nn.subgraph (%arg5 = %357: tensor<1x240x1x1xbf16>, %arg6 = %41: tensor<960x240x1x1xbf16>, %arg7 = %40: tensor<960xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_320",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 7]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 80, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 63]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 240, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 240, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[48, 80, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[960, 240, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[960, 240, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_320",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 7]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 48, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 31]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 990 : ui64, ofm = 4530 : ui64, wts = 31830 : ui64},
+        computation_cycles = 19498 : ui64,
+        cycle_count = 31830 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[3, 1, 2, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x240x1x1xbf16>, %arg9 = %arg6: tensor<960x240x1x1xbf16>, %arg10 = %arg7: tensor<960xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_320",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 240, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[960, 240, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_320",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 12 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 80 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 8 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 3 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 48 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 8 : ui8
+        },
+        estimation = {
+          compute_cycles = 3420 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x1x1xbf16> loc(#loc212)
+        xten_nn.output %465 : tensor<1x960x1x1xbf16> loc(#loc212)
+      } -> tensor<1x960x1x1xbf16> loc(#loc212)
+      xten_nn.output %464 : tensor<1x960x1x1xbf16> loc(#loc212)
+    } -> tensor<1x960x1x1xbf16> loc(#loc212)
+    %359 = xten_nn.subgraph (%arg5 = %358: tensor<1x960x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_322",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 384, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 31]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_322",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 384, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 576, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 778 : ui64, ofm = 394 : ui64},
+        computation_cycles = 401 : ui64,
+        cycle_count = 778 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x960x1x1xbf16>)  attributes {
+        LayerName = "Add_322",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_322",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 384 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 1 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 35 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x1x1xbf16> loc(#loc213)
+        xten_nn.output %465 : tensor<1x960x1x1xbf16> loc(#loc213)
+      } -> tensor<1x960x1x1xbf16> loc(#loc213)
+      xten_nn.output %464 : tensor<1x960x1x1xbf16> loc(#loc213)
+    } -> tensor<1x960x1x1xbf16> loc(#loc213)
+    %360 = xten_nn.subgraph (%arg5 = %359: tensor<1x960x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_325",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 256, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 576, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_325",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 256, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 64, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 522 : ui64, ofm = 266 : ui64},
+        computation_cycles = 395 : ui64,
+        cycle_count = 522 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x960x1x1xbf16>)  attributes {
+        LayerName = "Clip_325",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_325",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 256 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 1 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 35 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x1x1xbf16> loc(#loc214)
+        xten_nn.output %465 : tensor<1x960x1x1xbf16> loc(#loc214)
+      } -> tensor<1x960x1x1xbf16> loc(#loc214)
+      xten_nn.output %464 : tensor<1x960x1x1xbf16> loc(#loc214)
+    } -> tensor<1x960x1x1xbf16> loc(#loc214)
+    %361 = xten_nn.subgraph (%arg5 = %360: tensor<1x960x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_327",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 1, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 256, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 64, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_327",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 1, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 256, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 64, 7, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 1034 : ui64, ofm = 522 : ui64},
+        computation_cycles = 409 : ui64,
+        cycle_count = 1034 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x960x1x1xbf16>)  attributes {
+        LayerName = "Div_327",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_327",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 256 : ui32,
+          config.ifmsv_height = 2 : ui32,
+          config.ifmsv_width = 1 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 43 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x1x1xbf16> loc(#loc215)
+        xten_nn.output %465 : tensor<1x960x1x1xbf16> loc(#loc215)
+      } -> tensor<1x960x1x1xbf16> loc(#loc215)
+      xten_nn.output %464 : tensor<1x960x1x1xbf16> loc(#loc215)
+    } -> tensor<1x960x1x1xbf16> loc(#loc215)
+    %362 = xten_nn.subgraph (%arg5 = %361: tensor<1x960x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#52",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#53",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      Specializes = "TileAdf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.dtype = "bfloat16",
+        config.i_dim_c = 960 : ui32,
+        config.i_dim_h = 1 : ui32,
+        config.i_dim_n = 1 : ui32,
+        config.i_dim_w = 1 : ui32,
+        config.rep_dim_c = 1 : ui32,
+        config.rep_dim_h = 12 : ui32,
+        config.rep_dim_w = 20 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc216)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc216)
+    } -> tensor<1x960x12x20xbf16> loc(#loc216)
+    %363 = xten_nn.subgraph (%arg5 = %362: tensor<1x960x12x20xbf16>, %arg6 = %354: tensor<1x960x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_328",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_328",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 28950 : ui64, ifm2 = 28950 : ui64, ofm = 14550 : ui64},
+        computation_cycles = 2923 : ui64,
+        cycle_count = 28950 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x960x12x20xbf16>, %arg8 = %arg6: tensor<1x960x12x20xbf16>)  attributes {
+        LayerName = "Mul_328",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_328",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc216)
+        xten_nn.output %465 : tensor<1x960x12x20xbf16> loc(#loc216)
+      } -> tensor<1x960x12x20xbf16> loc(#loc216)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc216)
+    } -> tensor<1x960x12x20xbf16> loc(#loc216)
+    %364 = xten_nn.subgraph (%arg5 = %363: tensor<1x960x12x20xbf16>, %arg6 = %39: tensor<160x960x1x1xbf16>, %arg7 = %38: tensor<160xbf16>, %arg8 = %344: tensor<1x160x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 3 : index],
+      LayerName = "Conv_329",
+      OfmShare = 3 : index,
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 112, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[24, 112, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[32, 48, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[160, 960, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[32, 48, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[160, 960, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 24, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_330",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 24, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 48654 : ui64, ifm2 = 9276 : ui64, ofm = 4668 : ui64, wts = 26100 : ui64},
+        computation_cycles = 89679 : ui64,
+        cycle_count = 89679 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg9 = %arg5: tensor<1x960x12x20xbf16>, %arg10 = %arg6: tensor<160x960x1x1xbf16>, %arg11 = %arg7: tensor<160xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_329",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[160, 960, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_329",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 112 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 32 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 9 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 24 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 13590 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %466 = tensor.empty() : tensor<1x160x12x20xbf16> loc(#loc217)
+        xten_nn.output %466 : tensor<1x160x12x20xbf16> loc(#loc217)
+      } -> tensor<1x160x12x20xbf16> loc(#loc217)
+      %465 = xten_nn.subgraph (%arg9 = %464: tensor<1x160x12x20xbf16>, %arg10 = %arg8: tensor<1x160x12x20xbf16>)  attributes {
+        LayerName = "Add_330",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_330",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.act = 0 : ui8,
+          config.act_type = "LINEAR",
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 24 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 32 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 59 : ui64,
+          startup_cycles = 22 : ui64
+        }} {
+        %466 = tensor.empty() : tensor<1x160x12x20xbf16> loc(#loc218)
+        xten_nn.output %466 : tensor<1x160x12x20xbf16> loc(#loc218)
+      } -> tensor<1x160x12x20xbf16> loc(#loc218)
+      xten_nn.output %465 : tensor<1x160x12x20xbf16> loc(#loc218)
+    } -> tensor<1x160x12x20xbf16> loc(#loc345)
+    %365 = xten_nn.subgraph (%arg5 = %364: tensor<1x160x12x20xbf16>, %arg6 = %37: tensor<960x160x1x1xbf16>, %arg7 = %36: tensor<960xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_331",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 32, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[40, 80, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[960, 160, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[960, 160, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_331",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 40, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 7740 : ui64, ofm = 27828 : ui64, wts = 21240 : ui64},
+        computation_cycles = 62753 : ui64,
+        cycle_count = 62753 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x160x12x20xbf16>, %arg9 = %arg6: tensor<960x160x1x1xbf16>, %arg10 = %arg7: tensor<960xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_331",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 160, 12, 20]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[960, 160, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_331",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 80 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 32 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 2 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 40 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 3192 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc219)
+        xten_nn.output %465 : tensor<1x960x12x20xbf16> loc(#loc219)
+      } -> tensor<1x960x12x20xbf16> loc(#loc219)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc219)
+    } -> tensor<1x960x12x20xbf16> loc(#loc219)
+    %366 = xten_nn.subgraph (%arg5 = %365: tensor<1x960x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Add_333",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_333",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 28890 : ui64, ofm = 14490 : ui64},
+        computation_cycles = 2461 : ui64,
+        cycle_count = 28890 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x960x12x20xbf16>)  attributes {
+        LayerName = "Add_333",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_333",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 80 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 3.000000e+00 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 111 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc220)
+        xten_nn.output %465 : tensor<1x960x12x20xbf16> loc(#loc220)
+      } -> tensor<1x960x12x20xbf16> loc(#loc220)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc220)
+    } -> tensor<1x960x12x20xbf16> loc(#loc220)
+    %367 = xten_nn.subgraph (%arg5 = %366: tensor<1x960x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_336",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_336",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 28890 : ui64, ofm = 14490 : ui64},
+        computation_cycles = 2527 : ui64,
+        cycle_count = 28890 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x960x12x20xbf16>)  attributes {
+        LayerName = "Clip_336",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_336",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 6.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 80 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 119 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc221)
+        xten_nn.output %465 : tensor<1x960x12x20xbf16> loc(#loc221)
+      } -> tensor<1x960x12x20xbf16> loc(#loc221)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc221)
+    } -> tensor<1x960x12x20xbf16> loc(#loc221)
+    %368 = xten_nn.subgraph (%arg5 = %367: tensor<1x960x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Div_338",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Div_338",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 80, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 28890 : ui64, ofm = 14490 : ui64},
+        computation_cycles = 2461 : ui64,
+        cycle_count = 28890 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x960x12x20xbf16>)  attributes {
+        LayerName = "Div_338",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Div_338",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulAttributeBroadcastingBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifmsv_depth = 80 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.scalar = 1.660160e-01 : bf16,
+          config.scalar_position = 1 : ui8
+        },
+        estimation = {
+          compute_cycles = 111 : ui64,
+          startup_cycles = 46 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc222)
+        xten_nn.output %465 : tensor<1x960x12x20xbf16> loc(#loc222)
+      } -> tensor<1x960x12x20xbf16> loc(#loc222)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc222)
+    } -> tensor<1x960x12x20xbf16> loc(#loc222)
+    %369 = xten_nn.subgraph (%arg5 = %365: tensor<1x960x12x20xbf16>, %arg6 = %368: tensor<1x960x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_339",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 24, 2, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_force_single_buffering = true,
+          l2_tile_count = dense<[1, 960, 6, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 24, 2, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_force_single_buffering = true,
+          l2_tile_count = dense<[1, 960, 6, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_339",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 24, 2, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 2, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_force_single_buffering = true,
+          l2_tile_count = dense<[1, 960, 6, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 38600 : ui64, ifm2 = 38600 : ui64, ofm = 19400 : ui64},
+        computation_cycles = 3828 : ui64,
+        cycle_count = 77200 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x960x12x20xbf16>, %arg8 = %arg6: tensor<1x960x12x20xbf16>)  attributes {
+        LayerName = "Mul_339",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_339",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 24 : ui32,
+          config.ifmsv_height = 2 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x12x20xbf16> loc(#loc223)
+        xten_nn.output %465 : tensor<1x960x12x20xbf16> loc(#loc223)
+      } -> tensor<1x960x12x20xbf16> loc(#loc223)
+      xten_nn.output %464 : tensor<1x960x12x20xbf16> loc(#loc223)
+    } -> tensor<1x960x12x20xbf16> loc(#loc223)
+    %370 = xten_nn.subgraph (%arg5 = %369: tensor<1x960x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#54",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#55",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 240]> : vector<4xindex>
+        }
+      ],
+      Specializes = "Transpose4dAdf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.dim_0 = 12 : ui32,
+        config.dim_1 = 120 : ui32,
+        config.dim_2 = 20 : ui32,
+        config.dim_3 = 8 : ui32,
+        config.dtype = "bfloat16",
+        config.perm = 6 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x960x1x240xbf16> loc(#loc346)
+      xten_nn.output %464 : tensor<1x960x1x240xbf16> loc(#loc346)
+    } -> tensor<1x960x1x240xbf16> loc(#loc346)
+    %371 = xten_nn.subgraph (%arg5 = %370: tensor<1x960x1x240xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#56",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 40, 1, 48]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 1, 240]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 240]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#57",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 40, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 115500 : ui64, ofm = 9900 : ui64},
+        computation_cycles = 90253 : ui64,
+        cycle_count = 115500 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x960x1x240xbf16>)  attributes {
+        LayerName = "Generated-#56",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 1, 240]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Generated-#57",
+        PadValue = 0.000000e+00 : bf16,
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ReduceMeanC8Bf16",
+        Traits = {
+          Reduce = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.full_channel = 960 : ui32,
+          config.full_height = 1 : ui32,
+          config.full_width = 240 : ui32,
+          config.reduce_dim = "W",
+          config.sv_channel = 40 : ui32,
+          config.sv_height = 1 : ui32,
+          config.sv_width = 48 : ui32
+        },
+        estimation = {
+          compute_cycles = 2311 : ui64,
+          startup_cycles = 190 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x960x1x1xbf16> loc(#loc224)
+        xten_nn.output %465 : tensor<1x960x1x1xbf16> loc(#loc224)
+      } -> tensor<1x960x1x1xbf16> loc(#loc224)
+      xten_nn.output %464 : tensor<1x960x1x1xbf16> loc(#loc224)
+    } -> tensor<1x960x1x1xbf16> loc(#loc224)
+    %372 = xten_nn.subgraph (%arg5 = %371: tensor<1x960x1x1xbf16>, %arg6 = %35: tensor<128x960x1x1xbf16>, %arg7 = %34: tensor<128xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_343",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 15]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 192, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[16, 192, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[128, 960, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[128, 960, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_343",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 15]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 63]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 128, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 128, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 7730 : ui64, ofm = 1556 : ui64, wts = 16100 : ui64},
+        computation_cycles = 16123 : ui64,
+        cycle_count = 16123 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[3, 1, 2, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x960x1x1xbf16>, %arg9 = %arg6: tensor<128x960x1x1xbf16>, %arg10 = %arg7: tensor<128xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_343",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[128, 960, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_343",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 128, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 12 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 192 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 16 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 5 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 16 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 16 : ui8
+        },
+        estimation = {
+          compute_cycles = 7205 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x128x1x1xbf16> loc(#loc225)
+        xten_nn.output %465 : tensor<1x128x1x1xbf16> loc(#loc225)
+      } -> tensor<1x128x1x1xbf16> loc(#loc225)
+      xten_nn.output %464 : tensor<1x128x1x1xbf16> loc(#loc225)
+    } -> tensor<1x128x1x1xbf16> loc(#loc225)
+    %373 = xten_nn.subgraph (%arg5 = %372: tensor<1x128x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Sigmoid_344",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 15, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 63]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 128, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 128, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Sigmoid_344",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 15, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 63, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 128, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 128, 1, 1]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 1034 : ui64, ofm = 522 : ui64},
+        computation_cycles = 490 : ui64,
+        cycle_count = 1034 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x128x1x1xbf16>)  attributes {
+        LayerName = "Sigmoid_344",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 128, 1, 1]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Sigmoid_344",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 128, 1, 1]> : vector<4xindex>
+          }
+        ],
+        Specializes = "SigmoidTemplatedBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.ENABLE_FP16_AS_BF16 = 0 : ui8,
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 32 : ui32,
+          config.ifmsv_height = 16 : ui32,
+          config.ifmsv_width = 1 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 139 : ui64,
+          startup_cycles = 31 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x128x1x1xbf16> loc(#loc226)
+        xten_nn.output %465 : tensor<1x128x1x1xbf16> loc(#loc226)
+      } -> tensor<1x128x1x1xbf16> loc(#loc226)
+      xten_nn.output %464 : tensor<1x128x1x1xbf16> loc(#loc226)
+    } -> tensor<1x128x1x1xbf16> loc(#loc226)
+    %374 = xten_nn.subgraph (%arg5 = %373: tensor<1x128x1x1xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Generated-#58",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 128, 1, 1]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Generated-#59",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>
+        }
+      ],
+      Specializes = "TileAdf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.dtype = "bfloat16",
+        config.i_dim_c = 128 : ui32,
+        config.i_dim_h = 1 : ui32,
+        config.i_dim_n = 1 : ui32,
+        config.i_dim_w = 1 : ui32,
+        config.rep_dim_c = 1 : ui32,
+        config.rep_dim_h = 12 : ui32,
+        config.rep_dim_w = 20 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x128x12x20xbf16> loc(#loc227)
+      xten_nn.output %464 : tensor<1x128x12x20xbf16> loc(#loc227)
+    } -> tensor<1x128x12x20xbf16> loc(#loc227)
+    %375 = xten_nn.subgraph (%arg5 = %369: tensor<1x960x12x20xbf16>, %arg6 = %33: tensor<128x960x1x1xbf16>, %arg7 = %32: tensor<128xbf16>, %arg8 = %374: tensor<1x128x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 3 : index],
+      LayerName = "Conv_340",
+      OfmShare = 3 : index,
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 96, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[32, 96, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[128, 960, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[128, 960, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_345",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 1, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 46380 : ui64, ifm2 = 6174 : ui64, ofm = 3102 : ui64, wts = 16740 : ui64},
+        computation_cycles = 49946 : ui64,
+        cycle_count = 49946 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg9 = %arg5: tensor<1x960x12x20xbf16>, %arg10 = %arg6: tensor<128x960x1x1xbf16>, %arg11 = %arg7: tensor<128xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_340",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 960, 12, 20]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[128, 960, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Relu_341",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true,
+          NonNegativeOut = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 1 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 0 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 96 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 32 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 0.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 0.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 10 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 32 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 15110 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %466 = tensor.empty() : tensor<1x128x12x20xbf16> loc(#loc229)
+        xten_nn.output %466 : tensor<1x128x12x20xbf16> loc(#loc229)
+      } -> tensor<1x128x12x20xbf16> loc(#loc348)
+      %465 = xten_nn.subgraph (%arg9 = %464: tensor<1x128x12x20xbf16>, %arg10 = %arg8: tensor<1x128x12x20xbf16>)  attributes {
+        LayerName = "Mul_345",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_345",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 32 : ui32,
+          config.ifmsv_height = 1 : ui32,
+          config.ifmsv_width = 32 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 46 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %466 = tensor.empty() : tensor<1x128x12x20xbf16> loc(#loc227)
+        xten_nn.output %466 : tensor<1x128x12x20xbf16> loc(#loc227)
+      } -> tensor<1x128x12x20xbf16> loc(#loc227)
+      xten_nn.output %465 : tensor<1x128x12x20xbf16> loc(#loc227)
+    } -> tensor<1x128x12x20xbf16> loc(#loc347)
+    %376 = xten_nn.subgraph (%arg5 = %375: tensor<1x128x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Split_349_Duplicated#0",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Split_349_Duplicated#0",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        }
+      ],
+      Specializes = "SliceHCWC8Adf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.axis_letter = "C",
+        config.dim_c = 128 : ui32,
+        config.dim_h = 12 : ui32,
+        config.dim_w = 20 : ui32,
+        config.dtype = "bfloat16",
+        config.end = 64 : ui32,
+        config.num_ifm_shim_ch = 2 : ui32,
+        config.num_ofm_shim_ch = 2 : ui32,
+        config.start = 0 : ui32,
+        config.step = 1 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x64x12x20xbf16> loc(#loc230)
+      xten_nn.output %464 : tensor<1x64x12x20xbf16> loc(#loc230)
+    } -> tensor<1x64x12x20xbf16> loc(#loc230)
+    %377 = xten_nn.subgraph (%arg5 = %375: tensor<1x128x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Split_349_Duplicated#1",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Split_349_Duplicated#1",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        }
+      ],
+      Specializes = "SliceHCWC8Adf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.axis_letter = "C",
+        config.dim_c = 128 : ui32,
+        config.dim_h = 12 : ui32,
+        config.dim_w = 20 : ui32,
+        config.dtype = "bfloat16",
+        config.end = 128 : ui32,
+        config.num_ifm_shim_ch = 2 : ui32,
+        config.num_ofm_shim_ch = 2 : ui32,
+        config.start = 64 : ui32,
+        config.step = 1 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x64x12x20xbf16> loc(#loc230)
+      xten_nn.output %464 : tensor<1x64x12x20xbf16> loc(#loc230)
+    } -> tensor<1x64x12x20xbf16> loc(#loc230)
+    %378 = xten_nn.subgraph (%arg5 = %377: tensor<1x64x12x20xbf16>, %arg6 = %arg4: tensor<1x64x12x20xbf16>)  attributes {
+      Axis = 1 : i32,
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Concat_350",
+      Op = "Concat",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm1",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm2",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Concat_350",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "PseudoOp",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>
+        }
+      ],
+      current_data_format = "NCHW",
+      data_format = "HCWN",
+      herd_size = dense<4> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x128x12x20xbf16> loc(#loc231)
+      xten_nn.output %464 : tensor<1x128x12x20xbf16> loc(#loc231)
+    } -> tensor<1x128x12x20xbf16> loc(#loc231)
+    %379 = xten_nn.subgraph (%arg5 = %378: tensor<1x128x12x20xbf16>, %arg6 = %31: tensor<128x128x3x3xbf16>, %arg7 = %30: tensor<128xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_351",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 14]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 5, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[16, 16, 3, 3]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[128, 128, 3, 3]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[128, 128, 3, 3]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_351",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 10960 : ui64, ofm = 6676 : ui64, wts = 19616 : ui64},
+        computation_cycles = 30551 : ui64,
+        cycle_count = 30551 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x128x12x20xbf16>, %arg9 = %arg6: tensor<128x128x3x3xbf16>, %arg10 = %arg7: tensor<128xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[1, 1], [1, 1]],
+        LayerName = "Conv_351",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[128, 128, 3, 3]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_351",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 0 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 16 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 5 : ui8,
+          config.ifm_sv_width.size = 34 : ui8,
+          config.ksize.height = 3 : ui8,
+          config.ksize.width = 3 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 8 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 16 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 14008 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x128x12x20xbf16> loc(#loc232)
+        xten_nn.output %465 : tensor<1x128x12x20xbf16> loc(#loc232)
+      } -> tensor<1x128x12x20xbf16> loc(#loc232)
+      xten_nn.output %464 : tensor<1x128x12x20xbf16> loc(#loc232)
+    } -> tensor<1x128x12x20xbf16> loc(#loc232)
+    %380 = xten_nn.subgraph (%arg5 = %379: tensor<1x128x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Sigmoid_352",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Sigmoid_352",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 32, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 3850 : ui64, ofm = 1930 : ui64},
+        computation_cycles = 732 : ui64,
+        cycle_count = 3850 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x128x12x20xbf16>)  attributes {
+        LayerName = "Sigmoid_352",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Sigmoid_352",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "SigmoidTemplatedBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.ENABLE_FP16_AS_BF16 = 0 : ui8,
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 32 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 381 : ui64,
+          startup_cycles = 31 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x128x12x20xbf16> loc(#loc233)
+        xten_nn.output %465 : tensor<1x128x12x20xbf16> loc(#loc233)
+      } -> tensor<1x128x12x20xbf16> loc(#loc233)
+      xten_nn.output %464 : tensor<1x128x12x20xbf16> loc(#loc233)
+    } -> tensor<1x128x12x20xbf16> loc(#loc233)
+    %381 = xten_nn.subgraph (%arg5 = %380: tensor<1x128x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Split_353_Duplicated#1",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Split_353_Duplicated#1",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        }
+      ],
+      Specializes = "SliceHCWC8Adf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.axis_letter = "C",
+        config.dim_c = 128 : ui32,
+        config.dim_h = 12 : ui32,
+        config.dim_w = 20 : ui32,
+        config.dtype = "bfloat16",
+        config.end = 128 : ui32,
+        config.num_ifm_shim_ch = 2 : ui32,
+        config.num_ofm_shim_ch = 2 : ui32,
+        config.start = 64 : ui32,
+        config.step = 1 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x64x12x20xbf16> loc(#loc234)
+      xten_nn.output %464 : tensor<1x64x12x20xbf16> loc(#loc234)
+    } -> tensor<1x64x12x20xbf16> loc(#loc234)
+    %382 = xten_nn.subgraph (%arg5 = %27: tensor<1x64x12x20xbf16>, %arg6 = %381: tensor<1x64x12x20xbf16>)  attributes {
+      IfmOperands = [1 : index],
+      LayerName = "Sub_359",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Sub_359",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 1930 : ui64, ifm2 = 1930 : ui64, ofm = 970 : ui64},
+        computation_cycles = 414 : ui64,
+        cycle_count = 1930 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x64x12x20xbf16>, %arg8 = %arg6: tensor<1x64x12x20xbf16>)  attributes {
+        LayerName = "Sub_359",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Sub_359",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "SubBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 71 : ui64,
+          startup_cycles = 23 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x64x12x20xbf16> loc(#loc5)
+        xten_nn.output %465 : tensor<1x64x12x20xbf16> loc(#loc5)
+      } -> tensor<1x64x12x20xbf16> loc(#loc5)
+      xten_nn.output %464 : tensor<1x64x12x20xbf16> loc(#loc5)
+    } -> tensor<1x64x12x20xbf16> loc(#loc5)
+    %383 = xten_nn.subgraph (%arg5 = %382: tensor<1x64x12x20xbf16>, %arg6 = %arg4: tensor<1x64x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_360",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_360",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 1930 : ui64, ifm2 = 1930 : ui64, ofm = 970 : ui64},
+        computation_cycles = 389 : ui64,
+        cycle_count = 1930 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x64x12x20xbf16>, %arg8 = %arg6: tensor<1x64x12x20xbf16>)  attributes {
+        LayerName = "Mul_360",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_360",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x64x12x20xbf16> loc(#loc240)
+        xten_nn.output %465 : tensor<1x64x12x20xbf16> loc(#loc240)
+      } -> tensor<1x64x12x20xbf16> loc(#loc240)
+      xten_nn.output %464 : tensor<1x64x12x20xbf16> loc(#loc240)
+    } -> tensor<1x64x12x20xbf16> loc(#loc240)
+    %384 = xten_nn.subgraph (%arg5 = %380: tensor<1x128x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Split_353_Duplicated#0",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Split_353_Duplicated#0",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        }
+      ],
+      Specializes = "SliceHCWC8Adf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.axis_letter = "C",
+        config.dim_c = 128 : ui32,
+        config.dim_h = 12 : ui32,
+        config.dim_w = 20 : ui32,
+        config.dtype = "bfloat16",
+        config.end = 64 : ui32,
+        config.num_ifm_shim_ch = 2 : ui32,
+        config.num_ofm_shim_ch = 2 : ui32,
+        config.start = 0 : ui32,
+        config.step = 1 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x64x12x20xbf16> loc(#loc234)
+      xten_nn.output %464 : tensor<1x64x12x20xbf16> loc(#loc234)
+    } -> tensor<1x64x12x20xbf16> loc(#loc234)
+    %385 = xten_nn.subgraph (%arg5 = %384: tensor<1x64x12x20xbf16>, %arg6 = %arg4: tensor<1x64x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_354",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_354",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 1930 : ui64, ifm2 = 1930 : ui64, ofm = 970 : ui64},
+        computation_cycles = 389 : ui64,
+        cycle_count = 1930 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x64x12x20xbf16>, %arg8 = %arg6: tensor<1x64x12x20xbf16>)  attributes {
+        LayerName = "Mul_354",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_354",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x64x12x20xbf16> loc(#loc235)
+        xten_nn.output %465 : tensor<1x64x12x20xbf16> loc(#loc235)
+      } -> tensor<1x64x12x20xbf16> loc(#loc235)
+      xten_nn.output %464 : tensor<1x64x12x20xbf16> loc(#loc235)
+    } -> tensor<1x64x12x20xbf16> loc(#loc235)
+    %386 = xten_nn.subgraph (%arg5 = %377: tensor<1x64x12x20xbf16>, %arg6 = %385: tensor<1x64x12x20xbf16>)  attributes {
+      Axis = 1 : i32,
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Concat_355",
+      Op = "Concat",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm1",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm2",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Concat_355",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "PseudoOp",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>
+        }
+      ],
+      current_data_format = "NCHW",
+      data_format = "HCWN",
+      herd_size = dense<4> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x128x12x20xbf16> loc(#loc236)
+      xten_nn.output %464 : tensor<1x128x12x20xbf16> loc(#loc236)
+    } -> tensor<1x128x12x20xbf16> loc(#loc236)
+    %387 = xten_nn.subgraph (%arg5 = %386: tensor<1x128x12x20xbf16>, %arg6 = %29: tensor<64x128x3x3xbf16>, %arg7 = %28: tensor<64xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_356",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 14]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 5, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[16, 16, 3, 3]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[64, 128, 3, 3]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[64, 128, 3, 3]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_356",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 10960 : ui64, ofm = 3338 : ui64, wts = 9808 : ui64},
+        computation_cycles = 15447 : ui64,
+        cycle_count = 15447 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x128x12x20xbf16>, %arg9 = %arg6: tensor<64x128x3x3xbf16>, %arg10 = %arg7: tensor<64xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[1, 1], [1, 1]],
+        LayerName = "Conv_356",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[64, 128, 3, 3]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_356",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 0 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 16 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 5 : ui8,
+          config.ifm_sv_width.size = 34 : ui8,
+          config.ksize.height = 3 : ui8,
+          config.ksize.width = 3 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 8 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 16 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 14008 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x64x12x20xbf16> loc(#loc237)
+        xten_nn.output %465 : tensor<1x64x12x20xbf16> loc(#loc237)
+      } -> tensor<1x64x12x20xbf16> loc(#loc237)
+      xten_nn.output %464 : tensor<1x64x12x20xbf16> loc(#loc237)
+    } -> tensor<1x64x12x20xbf16> loc(#loc237)
+    %388 = xten_nn.subgraph (%arg5 = %387: tensor<1x64x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Tanh_357",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 0, 12]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Tanh_357",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 1930 : ui64, ofm = 970 : ui64},
+        computation_cycles = 2690 : ui64,
+        cycle_count = 2690 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x64x12x20xbf16>)  attributes {
+        LayerName = "Tanh_357",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Tanh_357",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "TanhTemplatedBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.ENABLE_FP16_AS_BF16 = 0 : ui8,
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 2346 : ui64,
+          startup_cycles = 24 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x64x12x20xbf16> loc(#loc238)
+        xten_nn.output %465 : tensor<1x64x12x20xbf16> loc(#loc238)
+      } -> tensor<1x64x12x20xbf16> loc(#loc238)
+      xten_nn.output %464 : tensor<1x64x12x20xbf16> loc(#loc238)
+    } -> tensor<1x64x12x20xbf16> loc(#loc238)
+    %389 = xten_nn.subgraph (%arg5 = %381: tensor<1x64x12x20xbf16>, %arg6 = %388: tensor<1x64x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_361",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_361",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 1930 : ui64, ifm2 = 1930 : ui64, ofm = 970 : ui64},
+        computation_cycles = 389 : ui64,
+        cycle_count = 1930 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x64x12x20xbf16>, %arg8 = %arg6: tensor<1x64x12x20xbf16>)  attributes {
+        LayerName = "Mul_361",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_361",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x64x12x20xbf16> loc(#loc239)
+        xten_nn.output %465 : tensor<1x64x12x20xbf16> loc(#loc239)
+      } -> tensor<1x64x12x20xbf16> loc(#loc239)
+      xten_nn.output %464 : tensor<1x64x12x20xbf16> loc(#loc239)
+    } -> tensor<1x64x12x20xbf16> loc(#loc239)
+    %390 = xten_nn.subgraph (%arg5 = %383: tensor<1x64x12x20xbf16>, %arg6 = %389: tensor<1x64x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Add_362",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_362",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 20]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 1930 : ui64, ifm2 = 1930 : ui64, ofm = 970 : ui64},
+        computation_cycles = 413 : ui64,
+        cycle_count = 1930 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x64x12x20xbf16>, %arg8 = %arg6: tensor<1x64x12x20xbf16>)  attributes {
+        LayerName = "Add_362",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_362",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.act = 0 : ui8,
+          config.act_type = "LINEAR",
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 3 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 71 : ui64,
+          startup_cycles = 22 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x64x12x20xbf16> loc(#loc241)
+        xten_nn.output %465 : tensor<1x64x12x20xbf16> loc(#loc241)
+      } -> tensor<1x64x12x20xbf16> loc(#loc241)
+      xten_nn.output %464 : tensor<1x64x12x20xbf16> loc(#loc241)
+    } -> tensor<1x64x12x20xbf16> loc(#loc241)
+    %391 = xten_nn.subgraph (%arg5 = %376: tensor<1x64x12x20xbf16>, %arg6 = %390: tensor<1x64x12x20xbf16>)  attributes {
+      Axis = 1 : i32,
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Concat_363",
+      Op = "Concat",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm1",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm2",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 64, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Concat_363",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "PseudoOp",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>
+        }
+      ],
+      current_data_format = "NCHW",
+      data_format = "HCWN",
+      herd_size = dense<4> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x128x12x20xbf16> loc(#loc242)
+      xten_nn.output %464 : tensor<1x128x12x20xbf16> loc(#loc242)
+    } -> tensor<1x128x12x20xbf16> loc(#loc242)
+    %392 = xten_nn.subgraph (%arg5 = %391: tensor<1x128x12x20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Resize_365",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 128, 12, 20]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Resize_365",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 128, 24, 40]> : vector<4xindex>
+        }
+      ],
+      Specializes = "ResizeAdf",
+      With = {
+        config.co_trans_mode = 1 : ui32,
+        config.dim_0 = 1 : ui32,
+        config.dim_1 = 128 : ui32,
+        config.dim_2 = 12 : ui32,
+        config.dim_3 = 20 : ui32,
+        config.dtype = "bfloat16",
+        config.mode = 1 : ui32,
+        config.nearest_mode = 0 : ui32,
+        config.num_ifm_shim_ch = 2 : ui32,
+        config.num_ofm_shim_ch = 2 : ui32,
+        config.output_H = 24 : ui32,
+        config.output_W = 40 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x128x24x40xbf16> loc(#loc243)
+      xten_nn.output %464 : tensor<1x128x24x40xbf16> loc(#loc243)
+    } -> tensor<1x128x24x40xbf16> loc(#loc243)
+    %393 = xten_nn.subgraph (%arg5 = %392: tensor<1x128x24x40xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Slice_371",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 128, 24, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Slice_371",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 128, 23, 40]> : vector<4xindex>
+        }
+      ],
+      Specializes = "SliceHCWC8Adf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.axis_letter = "H",
+        config.dim_c = 128 : ui32,
+        config.dim_h = 24 : ui32,
+        config.dim_w = 40 : ui32,
+        config.dtype = "bfloat16",
+        config.end = 23 : ui32,
+        config.num_ifm_shim_ch = 2 : ui32,
+        config.num_ofm_shim_ch = 2 : ui32,
+        config.start = 0 : ui32,
+        config.step = 1 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x128x23x40xbf16> loc(#loc244)
+      xten_nn.output %464 : tensor<1x128x23x40xbf16> loc(#loc244)
+    } -> tensor<1x128x23x40xbf16> loc(#loc244)
+    %394 = xten_nn.subgraph (%arg5 = %166: tensor<1x3x180x320xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "AveragePool_346",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 3, 2, 80]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 8, 60, 320]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+        }
+      ],
+      OutputName = "AveragePool_346",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 3, 1, 40]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 2, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 8, 30, 160]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 3, 90, 160]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 246720 : ui64, ofm = 31680 : ui64},
+        computation_cycles = 26024 : ui64,
+        cycle_count = 740160 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 0]> : vector<4xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "double", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x3x180x320xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        HWPaddingNotCounted = [[0, 0], [0, 0]],
+        LayerName = "AveragePool_346",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+          }
+        ],
+        OutputName = "AveragePool_346",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 3, 90, 160]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AvgPool2dBf16",
+        With = {
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifm_sv_depth.size = 8 : ui8,
+          config.ifm_sv_height.size = 2 : ui8,
+          config.ifm_sv_width.size = 80 : ui8,
+          config.ksize = 2 : ui8,
+          config.manual_ba_pad_val = 0 : si8,
+          config.stride_log2 = 1 : ui8,
+          data_io.ofm.dimensions.width.padding = 0 : ui8,
+          data_io.ofm.dimensions.width.size = 40 : ui8
+        },
+        estimation = {
+          compute_cycles = 131 : ui64,
+          startup_cycles = 113 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x3x90x160xbf16> loc(#loc12)
+        xten_nn.output %465 : tensor<1x3x90x160xbf16> loc(#loc12)
+      } -> tensor<1x3x90x160xbf16> loc(#loc12)
+      xten_nn.output %464 : tensor<1x3x90x160xbf16> loc(#loc12)
+    } -> tensor<1x3x90x160xbf16> loc(#loc12)
+    %395 = xten_nn.subgraph (%arg5 = %394: tensor<1x3x90x160xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "AveragePool_347",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 3, 12, 16]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 8, 90, 160]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 3, 90, 160]> : vector<4xindex>
+        }
+      ],
+      OutputName = "AveragePool_347",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 3, 6, 8]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 8, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 3, 45, 80]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 61640 : ui64, ofm = 7880 : ui64},
+        computation_cycles = 6036 : ui64,
+        cycle_count = 61640 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 0]> : vector<4xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "double", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x3x90x160xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        HWPaddingNotCounted = [[0, 0], [0, 0]],
+        LayerName = "AveragePool_347",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 3, 90, 160]> : vector<4xindex>
+          }
+        ],
+        OutputName = "AveragePool_347",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 3, 45, 80]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AvgPool2dBf16",
+        With = {
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifm_sv_depth.size = 8 : ui8,
+          config.ifm_sv_height.size = 12 : ui8,
+          config.ifm_sv_width.size = 16 : ui8,
+          config.ksize = 2 : ui8,
+          config.manual_ba_pad_val = 0 : si8,
+          config.stride_log2 = 1 : ui8,
+          data_io.ofm.dimensions.width.padding = 0 : ui8,
+          data_io.ofm.dimensions.width.size = 8 : ui8
+        },
+        estimation = {
+          compute_cycles = 150 : ui64,
+          startup_cycles = 113 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x3x45x80xbf16> loc(#loc245)
+        xten_nn.output %465 : tensor<1x3x45x80xbf16> loc(#loc245)
+      } -> tensor<1x3x45x80xbf16> loc(#loc245)
+      xten_nn.output %464 : tensor<1x3x45x80xbf16> loc(#loc245)
+    } -> tensor<1x3x45x80xbf16> loc(#loc245)
+    %396 = xten_nn.subgraph (%arg5 = %395: tensor<1x3x45x80xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "AveragePool_348",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 3, 12, 16]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 8, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 3, 45, 80]> : vector<4xindex>
+        }
+      ],
+      OutputName = "AveragePool_348",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 3, 6, 8]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 8, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 3, 23, 40]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 15410 : ui64, ofm = 1970 : ui64},
+        computation_cycles = 1731 : ui64,
+        cycle_count = 15410 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 0]> : vector<4xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "double", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x3x45x80xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 1], [0, 0]],
+        HWPaddingNotCounted = [[0, 1], [0, 0]],
+        LayerName = "AveragePool_348",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 3, 45, 80]> : vector<4xindex>
+          }
+        ],
+        OutputName = "AveragePool_348",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 3, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AvgPool2dBf16",
+        With = {
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifm_sv_depth.size = 8 : ui8,
+          config.ifm_sv_height.size = 12 : ui8,
+          config.ifm_sv_width.size = 16 : ui8,
+          config.ksize = 2 : ui8,
+          config.manual_ba_pad_val = 0 : si8,
+          config.stride_log2 = 1 : ui8,
+          data_io.ofm.dimensions.width.padding = 0 : ui8,
+          data_io.ofm.dimensions.width.size = 8 : ui8
+        },
+        estimation = {
+          compute_cycles = 150 : ui64,
+          startup_cycles = 113 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x3x23x40xbf16> loc(#loc246)
+        xten_nn.output %465 : tensor<1x3x23x40xbf16> loc(#loc246)
+      } -> tensor<1x3x23x40xbf16> loc(#loc246)
+      xten_nn.output %464 : tensor<1x3x23x40xbf16> loc(#loc246)
+    } -> tensor<1x3x23x40xbf16> loc(#loc246)
+    %397 = xten_nn.subgraph (%arg5 = %393: tensor<1x128x23x40xbf16>, %arg6 = %219: tensor<1x40x23x40xbf16>, %arg7 = %396: tensor<1x3x23x40xbf16>)  attributes {
+      Axis = 1 : i32,
+      IfmOperands = [0 : index, 1 : index, 2 : index],
+      LayerName = "Concat_372",
+      Op = "Concat",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm1",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 128, 23, 40]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm2",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm3",
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 3, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Concat_372",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "PseudoOp",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 171, 23, 40]> : vector<4xindex>
+        }
+      ],
+      current_data_format = "NCHW",
+      data_format = "HCWN",
+      herd_size = dense<4> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x171x23x40xbf16> loc(#loc247)
+      xten_nn.output %464 : tensor<1x171x23x40xbf16> loc(#loc247)
+    } -> tensor<1x171x23x40xbf16> loc(#loc247)
+    %398 = xten_nn.subgraph (%arg5 = %397: tensor<1x171x23x40xbf16>, %arg6 = %26: tensor<80x171x3x3xbf16>, %arg7 = %25: tensor<80xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_373",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 10]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 5, 40]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 176, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 171, 23, 40]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[16, 16, 3, 3]> : vector<4xindex>,
+          l2_extend_end = dense<[48, 5, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[80, 171, 3, 3]> : vector<4xindex>,
+          l3_extend_end = dense<[48, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[80, 171, 3, 3]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Relu_374",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 8]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 40]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 48, 1, 8]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 80, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 23, 40]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 44220 : ui64, ofm = 20008 : ui64, wts = 26972 : ui64},
+        computation_cycles = 110123 : ui64,
+        cycle_count = 110123 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x171x23x40xbf16>, %arg9 = %arg6: tensor<80x171x3x3xbf16>, %arg10 = %arg7: tensor<80xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[1, 1], [1, 1]],
+        LayerName = "Conv_373",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 171, 23, 40]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[80, 171, 3, 3]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Relu_374",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 80, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true,
+          NonNegativeOut = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 1 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 0 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 16 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 5 : ui8,
+          config.ifm_sv_width.size = 50 : ui8,
+          config.ksize.height = 3 : ui8,
+          config.ksize.width = 3 : ui8,
+          config.lrelu_alpha = 0.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 0.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 11 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 16 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 48 : ui8
+        },
+        estimation = {
+          compute_cycles = 25938 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x80x23x40xbf16> loc(#loc249)
+        xten_nn.output %465 : tensor<1x80x23x40xbf16> loc(#loc249)
+      } -> tensor<1x80x23x40xbf16> loc(#loc349)
+      xten_nn.output %464 : tensor<1x80x23x40xbf16> loc(#loc349)
+    } -> tensor<1x80x23x40xbf16> loc(#loc349)
+    %399 = xten_nn.subgraph (%arg5 = %398: tensor<1x80x23x40xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Split_375_Duplicated#0",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Split_375_Duplicated#0",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        }
+      ],
+      Specializes = "SliceHCWC8Adf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.axis_letter = "C",
+        config.dim_c = 80 : ui32,
+        config.dim_h = 23 : ui32,
+        config.dim_w = 40 : ui32,
+        config.dtype = "bfloat16",
+        config.end = 40 : ui32,
+        config.num_ifm_shim_ch = 2 : ui32,
+        config.num_ofm_shim_ch = 2 : ui32,
+        config.start = 0 : ui32,
+        config.step = 1 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x40x23x40xbf16> loc(#loc250)
+      xten_nn.output %464 : tensor<1x40x23x40xbf16> loc(#loc250)
+    } -> tensor<1x40x23x40xbf16> loc(#loc250)
+    %400 = xten_nn.subgraph (%arg5 = %398: tensor<1x80x23x40xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Split_375_Duplicated#1",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Split_375_Duplicated#1",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        }
+      ],
+      Specializes = "SliceHCWC8Adf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.axis_letter = "C",
+        config.dim_c = 80 : ui32,
+        config.dim_h = 23 : ui32,
+        config.dim_w = 40 : ui32,
+        config.dtype = "bfloat16",
+        config.end = 80 : ui32,
+        config.num_ifm_shim_ch = 2 : ui32,
+        config.num_ofm_shim_ch = 2 : ui32,
+        config.start = 40 : ui32,
+        config.step = 1 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x40x23x40xbf16> loc(#loc250)
+      xten_nn.output %464 : tensor<1x40x23x40xbf16> loc(#loc250)
+    } -> tensor<1x40x23x40xbf16> loc(#loc250)
+    %401 = xten_nn.subgraph (%arg5 = %400: tensor<1x40x23x40xbf16>, %arg6 = %arg3: tensor<1x40x23x40xbf16>)  attributes {
+      Axis = 1 : i32,
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Concat_376",
+      Op = "Concat",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm1",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm2",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Concat_376",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "PseudoOp",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 23, 40]> : vector<4xindex>
+        }
+      ],
+      current_data_format = "NCHW",
+      data_format = "HCWN",
+      herd_size = dense<4> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x80x23x40xbf16> loc(#loc251)
+      xten_nn.output %464 : tensor<1x80x23x40xbf16> loc(#loc251)
+    } -> tensor<1x80x23x40xbf16> loc(#loc251)
+    %402 = xten_nn.subgraph (%arg5 = %401: tensor<1x80x23x40xbf16>, %arg6 = %24: tensor<80x80x3x3xbf16>, %arg7 = %23: tensor<80xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_377",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 10]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 5, 40]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 80, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 23, 40]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[16, 16, 3, 3]> : vector<4xindex>,
+          l2_extend_end = dense<[48, 0, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[80, 80, 3, 3]> : vector<4xindex>,
+          l3_extend_end = dense<[48, 0, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[80, 80, 3, 3]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_377",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 8]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 40]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 48, 1, 8]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 80, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 23, 40]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 20100 : ui64, ofm = 20008 : ui64, wts = 12260 : ui64},
+        computation_cycles = 50243 : ui64,
+        cycle_count = 50243 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x80x23x40xbf16>, %arg9 = %arg6: tensor<80x80x3x3xbf16>, %arg10 = %arg7: tensor<80xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[1, 1], [1, 1]],
+        LayerName = "Conv_377",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 80, 23, 40]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[80, 80, 3, 3]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_377",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 80, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 0 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 16 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 5 : ui8,
+          config.ifm_sv_width.size = 50 : ui8,
+          config.ksize.height = 3 : ui8,
+          config.ksize.width = 3 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 5 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 16 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 48 : ui8
+        },
+        estimation = {
+          compute_cycles = 11790 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x80x23x40xbf16> loc(#loc252)
+        xten_nn.output %465 : tensor<1x80x23x40xbf16> loc(#loc252)
+      } -> tensor<1x80x23x40xbf16> loc(#loc252)
+      xten_nn.output %464 : tensor<1x80x23x40xbf16> loc(#loc252)
+    } -> tensor<1x80x23x40xbf16> loc(#loc252)
+    %403 = xten_nn.subgraph (%arg5 = %402: tensor<1x80x23x40xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Sigmoid_378",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 24, 2, 40]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 48, 1, 8]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 80, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Sigmoid_378",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 24, 2, 40]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 80, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 23, 40]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 11550 : ui64, ofm = 5790 : ui64},
+        computation_cycles = 1768 : ui64,
+        cycle_count = 11550 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x80x23x40xbf16>)  attributes {
+        LayerName = "Sigmoid_378",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 80, 23, 40]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Sigmoid_378",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 80, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "SigmoidTemplatedBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.ENABLE_FP16_AS_BF16 = 0 : ui8,
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 24 : ui32,
+          config.ifmsv_height = 2 : ui32,
+          config.ifmsv_width = 40 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 381 : ui64,
+          startup_cycles = 31 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x80x23x40xbf16> loc(#loc253)
+        xten_nn.output %465 : tensor<1x80x23x40xbf16> loc(#loc253)
+      } -> tensor<1x80x23x40xbf16> loc(#loc253)
+      xten_nn.output %464 : tensor<1x80x23x40xbf16> loc(#loc253)
+    } -> tensor<1x80x23x40xbf16> loc(#loc253)
+    %404 = xten_nn.subgraph (%arg5 = %403: tensor<1x80x23x40xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Split_379_Duplicated#1",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Split_379_Duplicated#1",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        }
+      ],
+      Specializes = "SliceHCWC8Adf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.axis_letter = "C",
+        config.dim_c = 80 : ui32,
+        config.dim_h = 23 : ui32,
+        config.dim_w = 40 : ui32,
+        config.dtype = "bfloat16",
+        config.end = 80 : ui32,
+        config.num_ifm_shim_ch = 2 : ui32,
+        config.num_ofm_shim_ch = 2 : ui32,
+        config.start = 40 : ui32,
+        config.step = 1 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x40x23x40xbf16> loc(#loc254)
+      xten_nn.output %464 : tensor<1x40x23x40xbf16> loc(#loc254)
+    } -> tensor<1x40x23x40xbf16> loc(#loc254)
+    %405 = xten_nn.subgraph (%arg5 = %20: tensor<1x40x23x40xbf16>, %arg6 = %404: tensor<1x40x23x40xbf16>)  attributes {
+      IfmOperands = [1 : index],
+      LayerName = "Sub_385",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 6, 10]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 6, 10]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Sub_385",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 6, 10]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 7720 : ui64, ifm2 = 7720 : ui64, ofm = 3880 : ui64},
+        computation_cycles = 1038 : ui64,
+        cycle_count = 7720 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x40x23x40xbf16>, %arg8 = %arg6: tensor<1x40x23x40xbf16>)  attributes {
+        LayerName = "Sub_385",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Sub_385",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "SubBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 6 : ui32,
+          config.ifmsv_width = 10 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 71 : ui64,
+          startup_cycles = 23 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x40x23x40xbf16> loc(#loc4)
+        xten_nn.output %465 : tensor<1x40x23x40xbf16> loc(#loc4)
+      } -> tensor<1x40x23x40xbf16> loc(#loc4)
+      xten_nn.output %464 : tensor<1x40x23x40xbf16> loc(#loc4)
+    } -> tensor<1x40x23x40xbf16> loc(#loc4)
+    %406 = xten_nn.subgraph (%arg5 = %405: tensor<1x40x23x40xbf16>, %arg6 = %arg3: tensor<1x40x23x40xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_386",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 6, 10]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 6, 10]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_386",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 6, 10]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 7720 : ui64, ifm2 = 7720 : ui64, ofm = 3880 : ui64},
+        computation_cycles = 932 : ui64,
+        cycle_count = 7720 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x40x23x40xbf16>, %arg8 = %arg6: tensor<1x40x23x40xbf16>)  attributes {
+        LayerName = "Mul_386",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_386",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 6 : ui32,
+          config.ifmsv_width = 10 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x40x23x40xbf16> loc(#loc260)
+        xten_nn.output %465 : tensor<1x40x23x40xbf16> loc(#loc260)
+      } -> tensor<1x40x23x40xbf16> loc(#loc260)
+      xten_nn.output %464 : tensor<1x40x23x40xbf16> loc(#loc260)
+    } -> tensor<1x40x23x40xbf16> loc(#loc260)
+    %407 = xten_nn.subgraph (%arg5 = %403: tensor<1x80x23x40xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Split_379_Duplicated#0",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Split_379_Duplicated#0",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        }
+      ],
+      Specializes = "SliceHCWC8Adf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.axis_letter = "C",
+        config.dim_c = 80 : ui32,
+        config.dim_h = 23 : ui32,
+        config.dim_w = 40 : ui32,
+        config.dtype = "bfloat16",
+        config.end = 40 : ui32,
+        config.num_ifm_shim_ch = 2 : ui32,
+        config.num_ofm_shim_ch = 2 : ui32,
+        config.start = 0 : ui32,
+        config.step = 1 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x40x23x40xbf16> loc(#loc254)
+      xten_nn.output %464 : tensor<1x40x23x40xbf16> loc(#loc254)
+    } -> tensor<1x40x23x40xbf16> loc(#loc254)
+    %408 = xten_nn.subgraph (%arg5 = %407: tensor<1x40x23x40xbf16>, %arg6 = %arg3: tensor<1x40x23x40xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_380",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 6, 10]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 6, 10]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_380",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 6, 10]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 7720 : ui64, ifm2 = 7720 : ui64, ofm = 3880 : ui64},
+        computation_cycles = 932 : ui64,
+        cycle_count = 7720 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x40x23x40xbf16>, %arg8 = %arg6: tensor<1x40x23x40xbf16>)  attributes {
+        LayerName = "Mul_380",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_380",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 6 : ui32,
+          config.ifmsv_width = 10 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x40x23x40xbf16> loc(#loc255)
+        xten_nn.output %465 : tensor<1x40x23x40xbf16> loc(#loc255)
+      } -> tensor<1x40x23x40xbf16> loc(#loc255)
+      xten_nn.output %464 : tensor<1x40x23x40xbf16> loc(#loc255)
+    } -> tensor<1x40x23x40xbf16> loc(#loc255)
+    %409 = xten_nn.subgraph (%arg5 = %400: tensor<1x40x23x40xbf16>, %arg6 = %408: tensor<1x40x23x40xbf16>)  attributes {
+      Axis = 1 : i32,
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Concat_381",
+      Op = "Concat",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm1",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm2",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Concat_381",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "PseudoOp",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 23, 40]> : vector<4xindex>
+        }
+      ],
+      current_data_format = "NCHW",
+      data_format = "HCWN",
+      herd_size = dense<4> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x80x23x40xbf16> loc(#loc256)
+      xten_nn.output %464 : tensor<1x80x23x40xbf16> loc(#loc256)
+    } -> tensor<1x80x23x40xbf16> loc(#loc256)
+    %410 = xten_nn.subgraph (%arg5 = %409: tensor<1x80x23x40xbf16>, %arg6 = %22: tensor<40x80x3x3xbf16>, %arg7 = %21: tensor<40xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_382",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 10]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 5, 40]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 80, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 23, 40]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[16, 16, 3, 3]> : vector<4xindex>,
+          l2_extend_end = dense<[24, 0, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[40, 80, 3, 3]> : vector<4xindex>,
+          l3_extend_end = dense<[24, 0, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[40, 80, 3, 3]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_382",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 0, 0, 8]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 3, 40]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 1, 8]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 20100 : ui64, ofm = 10004 : ui64, wts = 6130 : ui64},
+        computation_cycles = 25293 : ui64,
+        cycle_count = 25293 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x80x23x40xbf16>, %arg9 = %arg6: tensor<40x80x3x3xbf16>, %arg10 = %arg7: tensor<40xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[1, 1], [1, 1]],
+        LayerName = "Conv_382",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 80, 23, 40]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[40, 80, 3, 3]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_382",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 0 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 16 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 5 : ui8,
+          config.ifm_sv_width.size = 50 : ui8,
+          config.ksize.height = 3 : ui8,
+          config.ksize.width = 3 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 5 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 16 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 48 : ui8
+        },
+        estimation = {
+          compute_cycles = 11790 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x40x23x40xbf16> loc(#loc257)
+        xten_nn.output %465 : tensor<1x40x23x40xbf16> loc(#loc257)
+      } -> tensor<1x40x23x40xbf16> loc(#loc257)
+      xten_nn.output %464 : tensor<1x40x23x40xbf16> loc(#loc257)
+    } -> tensor<1x40x23x40xbf16> loc(#loc257)
+    %411 = xten_nn.subgraph (%arg5 = %410: tensor<1x40x23x40xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Tanh_383",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 6, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 1, 8]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Tanh_383",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 6, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 7700 : ui64, ofm = 3860 : ui64},
+        computation_cycles = 9373 : ui64,
+        cycle_count = 9373 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x40x23x40xbf16>)  attributes {
+        LayerName = "Tanh_383",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Tanh_383",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "TanhTemplatedBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.ENABLE_FP16_AS_BF16 = 0 : ui8,
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 6 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 4446 : ui64,
+          startup_cycles = 24 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x40x23x40xbf16> loc(#loc258)
+        xten_nn.output %465 : tensor<1x40x23x40xbf16> loc(#loc258)
+      } -> tensor<1x40x23x40xbf16> loc(#loc258)
+      xten_nn.output %464 : tensor<1x40x23x40xbf16> loc(#loc258)
+    } -> tensor<1x40x23x40xbf16> loc(#loc258)
+    %412 = xten_nn.subgraph (%arg5 = %404: tensor<1x40x23x40xbf16>, %arg6 = %411: tensor<1x40x23x40xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_387",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 6, 10]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 6, 10]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_387",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 6, 10]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 7720 : ui64, ifm2 = 7720 : ui64, ofm = 3880 : ui64},
+        computation_cycles = 932 : ui64,
+        cycle_count = 7720 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x40x23x40xbf16>, %arg8 = %arg6: tensor<1x40x23x40xbf16>)  attributes {
+        LayerName = "Mul_387",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_387",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 6 : ui32,
+          config.ifmsv_width = 10 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x40x23x40xbf16> loc(#loc259)
+        xten_nn.output %465 : tensor<1x40x23x40xbf16> loc(#loc259)
+      } -> tensor<1x40x23x40xbf16> loc(#loc259)
+      xten_nn.output %464 : tensor<1x40x23x40xbf16> loc(#loc259)
+    } -> tensor<1x40x23x40xbf16> loc(#loc259)
+    %413 = xten_nn.subgraph (%arg5 = %406: tensor<1x40x23x40xbf16>, %arg6 = %412: tensor<1x40x23x40xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Add_388",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 6, 10]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 6, 10]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_388",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 6, 10]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 7720 : ui64, ifm2 = 7720 : ui64, ofm = 3880 : ui64},
+        computation_cycles = 1037 : ui64,
+        cycle_count = 7720 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x40x23x40xbf16>, %arg8 = %arg6: tensor<1x40x23x40xbf16>)  attributes {
+        LayerName = "Add_388",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_388",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.act = 0 : ui8,
+          config.act_type = "LINEAR",
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 6 : ui32,
+          config.ifmsv_width = 10 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 71 : ui64,
+          startup_cycles = 22 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x40x23x40xbf16> loc(#loc261)
+        xten_nn.output %465 : tensor<1x40x23x40xbf16> loc(#loc261)
+      } -> tensor<1x40x23x40xbf16> loc(#loc261)
+      xten_nn.output %464 : tensor<1x40x23x40xbf16> loc(#loc261)
+    } -> tensor<1x40x23x40xbf16> loc(#loc261)
+    %414 = xten_nn.subgraph (%arg5 = %399: tensor<1x40x23x40xbf16>, %arg6 = %413: tensor<1x40x23x40xbf16>)  attributes {
+      Axis = 1 : i32,
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Concat_389",
+      Op = "Concat",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm1",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm2",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Concat_389",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "PseudoOp",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 23, 40]> : vector<4xindex>
+        }
+      ],
+      current_data_format = "NCHW",
+      data_format = "HCWN",
+      herd_size = dense<4> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x80x23x40xbf16> loc(#loc262)
+      xten_nn.output %464 : tensor<1x80x23x40xbf16> loc(#loc262)
+    } -> tensor<1x80x23x40xbf16> loc(#loc262)
+    %415 = xten_nn.subgraph (%arg5 = %414: tensor<1x80x23x40xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Resize_391",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 23, 40]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Resize_391",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 46, 80]> : vector<4xindex>
+        }
+      ],
+      Specializes = "ResizeAdf",
+      With = {
+        config.co_trans_mode = 1 : ui32,
+        config.dim_0 = 1 : ui32,
+        config.dim_1 = 80 : ui32,
+        config.dim_2 = 23 : ui32,
+        config.dim_3 = 40 : ui32,
+        config.dtype = "bfloat16",
+        config.mode = 1 : ui32,
+        config.nearest_mode = 0 : ui32,
+        config.num_ifm_shim_ch = 2 : ui32,
+        config.num_ofm_shim_ch = 2 : ui32,
+        config.output_H = 46 : ui32,
+        config.output_W = 80 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x80x46x80xbf16> loc(#loc263)
+      xten_nn.output %464 : tensor<1x80x46x80xbf16> loc(#loc263)
+    } -> tensor<1x80x46x80xbf16> loc(#loc263)
+    %416 = xten_nn.subgraph (%arg5 = %415: tensor<1x80x46x80xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Slice_397",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 46, 80]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Slice_397",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 45, 80]> : vector<4xindex>
+        }
+      ],
+      Specializes = "SliceHCWC8Adf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.axis_letter = "H",
+        config.dim_c = 80 : ui32,
+        config.dim_h = 46 : ui32,
+        config.dim_w = 80 : ui32,
+        config.dtype = "bfloat16",
+        config.end = 45 : ui32,
+        config.num_ifm_shim_ch = 2 : ui32,
+        config.num_ofm_shim_ch = 2 : ui32,
+        config.start = 0 : ui32,
+        config.step = 1 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x80x45x80xbf16> loc(#loc264)
+      xten_nn.output %464 : tensor<1x80x45x80xbf16> loc(#loc264)
+    } -> tensor<1x80x45x80xbf16> loc(#loc264)
+    %417 = xten_nn.subgraph (%arg5 = %416: tensor<1x80x45x80xbf16>, %arg6 = %183: tensor<1x24x45x80xbf16>, %arg7 = %395: tensor<1x3x45x80xbf16>)  attributes {
+      Axis = 1 : i32,
+      IfmOperands = [0 : index, 1 : index, 2 : index],
+      LayerName = "Concat_398",
+      Op = "Concat",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm1",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 80, 45, 80]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm2",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm3",
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 3, 45, 80]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Concat_398",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "PseudoOp",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 107, 45, 80]> : vector<4xindex>
+        }
+      ],
+      current_data_format = "NCHW",
+      data_format = "HCWN",
+      herd_size = dense<4> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x107x45x80xbf16> loc(#loc265)
+      xten_nn.output %464 : tensor<1x107x45x80xbf16> loc(#loc265)
+    } -> tensor<1x107x45x80xbf16> loc(#loc265)
+    %418 = xten_nn.subgraph (%arg5 = %417: tensor<1x107x45x80xbf16>, %arg6 = %19: tensor<40x107x3x3xbf16>, %arg7 = %18: tensor<40xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_399",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 14, 18]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 112, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 107, 45, 80]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[16, 16, 3, 3]> : vector<4xindex>,
+          l2_extend_end = dense<[24, 5, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[40, 107, 3, 3]> : vector<4xindex>,
+          l3_extend_end = dense<[24, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[40, 107, 3, 3]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Relu_400",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 12, 16]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 45, 80]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 70910 : ui64, ofm = 31410 : ui64, wts = 8582 : ui64},
+        computation_cycles = 107863 : ui64,
+        cycle_count = 107863 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x107x45x80xbf16>, %arg9 = %arg6: tensor<40x107x3x3xbf16>, %arg10 = %arg7: tensor<40xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[1, 1], [1, 1]],
+        LayerName = "Conv_399",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 107, 45, 80]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[40, 107, 3, 3]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Relu_400",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 45, 80]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true,
+          NonNegativeOut = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 1 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 0 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 16 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 14 : ui8,
+          config.ifm_sv_width.size = 18 : ui8,
+          config.ksize.height = 3 : ui8,
+          config.ksize.width = 3 : ui8,
+          config.lrelu_alpha = 0.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 0.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 7 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 16 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 16 : ui8
+        },
+        estimation = {
+          compute_cycles = 20545 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x40x45x80xbf16> loc(#loc267)
+        xten_nn.output %465 : tensor<1x40x45x80xbf16> loc(#loc267)
+      } -> tensor<1x40x45x80xbf16> loc(#loc350)
+      xten_nn.output %464 : tensor<1x40x45x80xbf16> loc(#loc350)
+    } -> tensor<1x40x45x80xbf16> loc(#loc350)
+    %419 = xten_nn.subgraph (%arg5 = %418: tensor<1x40x45x80xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Split_401_Duplicated#0",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 45, 80]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Split_401_Duplicated#0",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        }
+      ],
+      Specializes = "SliceHCWC8Adf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.axis_letter = "C",
+        config.dim_c = 40 : ui32,
+        config.dim_h = 45 : ui32,
+        config.dim_w = 80 : ui32,
+        config.dtype = "bfloat16",
+        config.end = 20 : ui32,
+        config.num_ifm_shim_ch = 2 : ui32,
+        config.num_ofm_shim_ch = 2 : ui32,
+        config.start = 0 : ui32,
+        config.step = 1 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x20x45x80xbf16> loc(#loc268)
+      xten_nn.output %464 : tensor<1x20x45x80xbf16> loc(#loc268)
+    } -> tensor<1x20x45x80xbf16> loc(#loc268)
+    %420 = xten_nn.subgraph (%arg5 = %418: tensor<1x40x45x80xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Split_401_Duplicated#1",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 45, 80]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Split_401_Duplicated#1",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        }
+      ],
+      Specializes = "SliceHCWC8Adf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.axis_letter = "C",
+        config.dim_c = 40 : ui32,
+        config.dim_h = 45 : ui32,
+        config.dim_w = 80 : ui32,
+        config.dtype = "bfloat16",
+        config.end = 40 : ui32,
+        config.num_ifm_shim_ch = 2 : ui32,
+        config.num_ofm_shim_ch = 2 : ui32,
+        config.start = 20 : ui32,
+        config.step = 1 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x20x45x80xbf16> loc(#loc268)
+      xten_nn.output %464 : tensor<1x20x45x80xbf16> loc(#loc268)
+    } -> tensor<1x20x45x80xbf16> loc(#loc268)
+    %421 = xten_nn.subgraph (%arg5 = %420: tensor<1x20x45x80xbf16>, %arg6 = %arg2: tensor<1x20x45x80xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Concat_402",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm1",
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm2",
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Concat_402",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 45, 80]> : vector<4xindex>
+        }
+      ],
+      Specializes = "ConcatC8Adf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.dtype = "bfloat16",
+        config.in1_dim_c = 24 : ui32,
+        config.in1_dim_h = 45 : ui32,
+        config.in1_dim_w = 80 : ui32,
+        config.in2_dim_c = 24 : ui32,
+        config.in2_dim_h = 45 : ui32,
+        config.in2_dim_w = 80 : ui32,
+        config.num_eff_concat_input0_size = 20 : ui32,
+        config.num_eff_concat_input0_start = 0 : ui32,
+        config.num_eff_concat_input1_size = 20 : ui32,
+        config.num_eff_concat_input1_start = 0 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x40x45x80xbf16> loc(#loc269)
+      xten_nn.output %464 : tensor<1x40x45x80xbf16> loc(#loc269)
+    } -> tensor<1x40x45x80xbf16> loc(#loc269)
+    %422 = xten_nn.subgraph (%arg5 = %421: tensor<1x40x45x80xbf16>, %arg6 = %17: tensor<40x40x3x3xbf16>, %arg7 = %16: tensor<40xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_403",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 14, 18]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 45, 80]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[16, 16, 3, 3]> : vector<4xindex>,
+          l2_extend_end = dense<[24, 8, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[40, 40, 3, 3]> : vector<4xindex>,
+          l3_extend_end = dense<[24, 8, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[40, 40, 3, 3]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_403",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 12, 16]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 45, 80]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 30390 : ui64, ofm = 31410 : ui64, wts = 3678 : ui64},
+        computation_cycles = 46423 : ui64,
+        cycle_count = 46423 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x40x45x80xbf16>, %arg9 = %arg6: tensor<40x40x3x3xbf16>, %arg10 = %arg7: tensor<40xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[1, 1], [1, 1]],
+        LayerName = "Conv_403",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 45, 80]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[40, 40, 3, 3]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_403",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 45, 80]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 0 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 16 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 14 : ui8,
+          config.ifm_sv_width.size = 18 : ui8,
+          config.ksize.height = 3 : ui8,
+          config.ksize.width = 3 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 3 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 16 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 16 : ui8
+        },
+        estimation = {
+          compute_cycles = 8805 : ui64,
+          startup_cycles = 160 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x40x45x80xbf16> loc(#loc270)
+        xten_nn.output %465 : tensor<1x40x45x80xbf16> loc(#loc270)
+      } -> tensor<1x40x45x80xbf16> loc(#loc270)
+      xten_nn.output %464 : tensor<1x40x45x80xbf16> loc(#loc270)
+    } -> tensor<1x40x45x80xbf16> loc(#loc270)
+    %423 = xten_nn.subgraph (%arg5 = %422: tensor<1x40x45x80xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Sigmoid_404",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 12, 10]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 45, 80]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Sigmoid_404",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 16, 12, 10]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 45, 80]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 30800 : ui64, ofm = 15440 : ui64},
+        computation_cycles = 4358 : ui64,
+        cycle_count = 30800 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x40x45x80xbf16>)  attributes {
+        LayerName = "Sigmoid_404",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 45, 80]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Sigmoid_404",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 45, 80]> : vector<4xindex>
+          }
+        ],
+        Specializes = "SigmoidTemplatedBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.ENABLE_FP16_AS_BF16 = 0 : ui8,
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 16 : ui32,
+          config.ifmsv_height = 12 : ui32,
+          config.ifmsv_width = 10 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 381 : ui64,
+          startup_cycles = 31 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x40x45x80xbf16> loc(#loc271)
+        xten_nn.output %465 : tensor<1x40x45x80xbf16> loc(#loc271)
+      } -> tensor<1x40x45x80xbf16> loc(#loc271)
+      xten_nn.output %464 : tensor<1x40x45x80xbf16> loc(#loc271)
+    } -> tensor<1x40x45x80xbf16> loc(#loc271)
+    %424 = xten_nn.subgraph (%arg5 = %423: tensor<1x40x45x80xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Split_405_Duplicated#1",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 45, 80]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Split_405_Duplicated#1",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        }
+      ],
+      Specializes = "SliceHCWC8Adf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.axis_letter = "C",
+        config.dim_c = 40 : ui32,
+        config.dim_h = 45 : ui32,
+        config.dim_w = 80 : ui32,
+        config.dtype = "bfloat16",
+        config.end = 40 : ui32,
+        config.num_ifm_shim_ch = 2 : ui32,
+        config.num_ofm_shim_ch = 2 : ui32,
+        config.start = 20 : ui32,
+        config.step = 1 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x20x45x80xbf16> loc(#loc272)
+      xten_nn.output %464 : tensor<1x20x45x80xbf16> loc(#loc272)
+    } -> tensor<1x20x45x80xbf16> loc(#loc272)
+    %425 = xten_nn.subgraph (%arg5 = %13: tensor<1x20x45x80xbf16>, %arg6 = %424: tensor<1x20x45x80xbf16>)  attributes {
+      IfmOperands = [1 : index],
+      LayerName = "Sub_411",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 12, 10]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 12, 10]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Sub_411",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 12, 10]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 15440 : ui64, ifm2 = 15440 : ui64, ofm = 7760 : ui64},
+        computation_cycles = 1870 : ui64,
+        cycle_count = 15440 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x20x45x80xbf16>, %arg8 = %arg6: tensor<1x20x45x80xbf16>)  attributes {
+        LayerName = "Sub_411",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Sub_411",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+          }
+        ],
+        Specializes = "SubBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 8 : ui32,
+          config.ifmsv_height = 12 : ui32,
+          config.ifmsv_width = 10 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 71 : ui64,
+          startup_cycles = 23 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x20x45x80xbf16> loc(#loc3)
+        xten_nn.output %465 : tensor<1x20x45x80xbf16> loc(#loc3)
+      } -> tensor<1x20x45x80xbf16> loc(#loc3)
+      xten_nn.output %464 : tensor<1x20x45x80xbf16> loc(#loc3)
+    } -> tensor<1x20x45x80xbf16> loc(#loc3)
+    %426 = xten_nn.subgraph (%arg5 = %425: tensor<1x20x45x80xbf16>, %arg6 = %arg2: tensor<1x20x45x80xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_412",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 12, 10]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 12, 10]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_412",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 12, 10]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 15440 : ui64, ifm2 = 15440 : ui64, ofm = 7760 : ui64},
+        computation_cycles = 1656 : ui64,
+        cycle_count = 15440 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x20x45x80xbf16>, %arg8 = %arg6: tensor<1x20x45x80xbf16>)  attributes {
+        LayerName = "Mul_412",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_412",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 8 : ui32,
+          config.ifmsv_height = 12 : ui32,
+          config.ifmsv_width = 10 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x20x45x80xbf16> loc(#loc278)
+        xten_nn.output %465 : tensor<1x20x45x80xbf16> loc(#loc278)
+      } -> tensor<1x20x45x80xbf16> loc(#loc278)
+      xten_nn.output %464 : tensor<1x20x45x80xbf16> loc(#loc278)
+    } -> tensor<1x20x45x80xbf16> loc(#loc278)
+    %427 = xten_nn.subgraph (%arg5 = %423: tensor<1x40x45x80xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Split_405_Duplicated#0",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 45, 80]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Split_405_Duplicated#0",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        }
+      ],
+      Specializes = "SliceHCWC8Adf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.axis_letter = "C",
+        config.dim_c = 40 : ui32,
+        config.dim_h = 45 : ui32,
+        config.dim_w = 80 : ui32,
+        config.dtype = "bfloat16",
+        config.end = 20 : ui32,
+        config.num_ifm_shim_ch = 2 : ui32,
+        config.num_ofm_shim_ch = 2 : ui32,
+        config.start = 0 : ui32,
+        config.step = 1 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x20x45x80xbf16> loc(#loc272)
+      xten_nn.output %464 : tensor<1x20x45x80xbf16> loc(#loc272)
+    } -> tensor<1x20x45x80xbf16> loc(#loc272)
+    %428 = xten_nn.subgraph (%arg5 = %427: tensor<1x20x45x80xbf16>, %arg6 = %arg2: tensor<1x20x45x80xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_406",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 12, 10]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 12, 10]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_406",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 12, 10]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 15440 : ui64, ifm2 = 15440 : ui64, ofm = 7760 : ui64},
+        computation_cycles = 1656 : ui64,
+        cycle_count = 15440 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x20x45x80xbf16>, %arg8 = %arg6: tensor<1x20x45x80xbf16>)  attributes {
+        LayerName = "Mul_406",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_406",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 8 : ui32,
+          config.ifmsv_height = 12 : ui32,
+          config.ifmsv_width = 10 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x20x45x80xbf16> loc(#loc273)
+        xten_nn.output %465 : tensor<1x20x45x80xbf16> loc(#loc273)
+      } -> tensor<1x20x45x80xbf16> loc(#loc273)
+      xten_nn.output %464 : tensor<1x20x45x80xbf16> loc(#loc273)
+    } -> tensor<1x20x45x80xbf16> loc(#loc273)
+    %429 = xten_nn.subgraph (%arg5 = %420: tensor<1x20x45x80xbf16>, %arg6 = %428: tensor<1x20x45x80xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Concat_407",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm1",
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm2",
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Concat_407",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 45, 80]> : vector<4xindex>
+        }
+      ],
+      Specializes = "ConcatC8Adf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.dtype = "bfloat16",
+        config.in1_dim_c = 24 : ui32,
+        config.in1_dim_h = 45 : ui32,
+        config.in1_dim_w = 80 : ui32,
+        config.in2_dim_c = 24 : ui32,
+        config.in2_dim_h = 45 : ui32,
+        config.in2_dim_w = 80 : ui32,
+        config.num_eff_concat_input0_size = 20 : ui32,
+        config.num_eff_concat_input0_start = 0 : ui32,
+        config.num_eff_concat_input1_size = 20 : ui32,
+        config.num_eff_concat_input1_start = 0 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x40x45x80xbf16> loc(#loc274)
+      xten_nn.output %464 : tensor<1x40x45x80xbf16> loc(#loc274)
+    } -> tensor<1x40x45x80xbf16> loc(#loc274)
+    %430 = xten_nn.subgraph (%arg5 = %429: tensor<1x40x45x80xbf16>, %arg6 = %15: tensor<20x40x3x3xbf16>, %arg7 = %14: tensor<20xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_408",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 14, 34]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 45, 80]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[8, 8, 3, 3]> : vector<4xindex>,
+          l2_extend_end = dense<[12, 0, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[20, 40, 3, 3]> : vector<4xindex>,
+          l3_extend_end = dense<[12, 0, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[20, 40, 3, 3]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_408",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 12, 32]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 3, 16]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 28710 : ui64, ofm = 10014 : ui64, wts = 1650 : ui64},
+        computation_cycles = 36245 : ui64,
+        cycle_count = 36245 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x40x45x80xbf16>, %arg9 = %arg6: tensor<20x40x3x3xbf16>, %arg10 = %arg7: tensor<20xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[1, 1], [1, 1]],
+        LayerName = "Conv_408",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 40, 45, 80]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<[4, 0, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[20, 40, 3, 3]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_408",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 8 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 14 : ui8,
+          config.ifm_sv_width.size = 34 : ui8,
+          config.ksize.height = 3 : ui8,
+          config.ksize.width = 3 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 5 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 8 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 11275 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x20x45x80xbf16> loc(#loc275)
+        xten_nn.output %465 : tensor<1x20x45x80xbf16> loc(#loc275)
+      } -> tensor<1x20x45x80xbf16> loc(#loc275)
+      xten_nn.output %464 : tensor<1x20x45x80xbf16> loc(#loc275)
+    } -> tensor<1x20x45x80xbf16> loc(#loc275)
+    %431 = xten_nn.subgraph (%arg5 = %430: tensor<1x20x45x80xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Tanh_409",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 12, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 3, 16]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Tanh_409",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 12, 20]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 15400 : ui64, ofm = 7720 : ui64},
+        computation_cycles = 18539 : ui64,
+        cycle_count = 18539 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x20x45x80xbf16>)  attributes {
+        LayerName = "Tanh_409",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Tanh_409",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+          }
+        ],
+        Specializes = "TanhTemplatedBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.ENABLE_FP16_AS_BF16 = 0 : ui8,
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 8 : ui32,
+          config.ifmsv_height = 12 : ui32,
+          config.ifmsv_width = 20 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 4446 : ui64,
+          startup_cycles = 24 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x20x45x80xbf16> loc(#loc276)
+        xten_nn.output %465 : tensor<1x20x45x80xbf16> loc(#loc276)
+      } -> tensor<1x20x45x80xbf16> loc(#loc276)
+      xten_nn.output %464 : tensor<1x20x45x80xbf16> loc(#loc276)
+    } -> tensor<1x20x45x80xbf16> loc(#loc276)
+    %432 = xten_nn.subgraph (%arg5 = %424: tensor<1x20x45x80xbf16>, %arg6 = %431: tensor<1x20x45x80xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_413",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 12, 10]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 12, 10]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_413",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 12, 10]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 15440 : ui64, ifm2 = 15440 : ui64, ofm = 7760 : ui64},
+        computation_cycles = 1656 : ui64,
+        cycle_count = 15440 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x20x45x80xbf16>, %arg8 = %arg6: tensor<1x20x45x80xbf16>)  attributes {
+        LayerName = "Mul_413",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_413",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 8 : ui32,
+          config.ifmsv_height = 12 : ui32,
+          config.ifmsv_width = 10 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 44 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x20x45x80xbf16> loc(#loc277)
+        xten_nn.output %465 : tensor<1x20x45x80xbf16> loc(#loc277)
+      } -> tensor<1x20x45x80xbf16> loc(#loc277)
+      xten_nn.output %464 : tensor<1x20x45x80xbf16> loc(#loc277)
+    } -> tensor<1x20x45x80xbf16> loc(#loc277)
+    %433 = xten_nn.subgraph (%arg5 = %426: tensor<1x20x45x80xbf16>, %arg6 = %432: tensor<1x20x45x80xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Add_414",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 12, 10]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 12, 10]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_414",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 12, 10]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 8, 3, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 24, 45, 80]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 15440 : ui64, ifm2 = 15440 : ui64, ofm = 7760 : ui64},
+        computation_cycles = 1869 : ui64,
+        cycle_count = 15440 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x20x45x80xbf16>, %arg8 = %arg6: tensor<1x20x45x80xbf16>)  attributes {
+        LayerName = "Add_414",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_414",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.act = 0 : ui8,
+          config.act_type = "LINEAR",
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 8 : ui32,
+          config.ifmsv_height = 12 : ui32,
+          config.ifmsv_width = 10 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 71 : ui64,
+          startup_cycles = 22 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x20x45x80xbf16> loc(#loc279)
+        xten_nn.output %465 : tensor<1x20x45x80xbf16> loc(#loc279)
+      } -> tensor<1x20x45x80xbf16> loc(#loc279)
+      xten_nn.output %464 : tensor<1x20x45x80xbf16> loc(#loc279)
+    } -> tensor<1x20x45x80xbf16> loc(#loc279)
+    %434 = xten_nn.subgraph (%arg5 = %419: tensor<1x20x45x80xbf16>, %arg6 = %433: tensor<1x20x45x80xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Concat_415",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm1",
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm2",
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 20, 45, 80]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Concat_415",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 45, 80]> : vector<4xindex>
+        }
+      ],
+      Specializes = "ConcatC8Adf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.dtype = "bfloat16",
+        config.in1_dim_c = 24 : ui32,
+        config.in1_dim_h = 45 : ui32,
+        config.in1_dim_w = 80 : ui32,
+        config.in2_dim_c = 24 : ui32,
+        config.in2_dim_h = 45 : ui32,
+        config.in2_dim_w = 80 : ui32,
+        config.num_eff_concat_input0_size = 20 : ui32,
+        config.num_eff_concat_input0_start = 0 : ui32,
+        config.num_eff_concat_input1_size = 20 : ui32,
+        config.num_eff_concat_input1_start = 0 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x40x45x80xbf16> loc(#loc280)
+      xten_nn.output %464 : tensor<1x40x45x80xbf16> loc(#loc280)
+    } -> tensor<1x40x45x80xbf16> loc(#loc280)
+    %435 = xten_nn.subgraph (%arg5 = %434: tensor<1x40x45x80xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Resize_417",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 45, 80]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Resize_417",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 90, 160]> : vector<4xindex>
+        }
+      ],
+      Specializes = "ResizeAdf",
+      With = {
+        config.co_trans_mode = 1 : ui32,
+        config.dim_0 = 1 : ui32,
+        config.dim_1 = 40 : ui32,
+        config.dim_2 = 45 : ui32,
+        config.dim_3 = 80 : ui32,
+        config.dtype = "bfloat16",
+        config.mode = 1 : ui32,
+        config.nearest_mode = 0 : ui32,
+        config.num_ifm_shim_ch = 2 : ui32,
+        config.num_ofm_shim_ch = 2 : ui32,
+        config.output_H = 90 : ui32,
+        config.output_W = 160 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x40x90x160xbf16> loc(#loc281)
+      xten_nn.output %464 : tensor<1x40x90x160xbf16> loc(#loc281)
+    } -> tensor<1x40x90x160xbf16> loc(#loc281)
+    %436 = xten_nn.subgraph (%arg5 = %435: tensor<1x40x90x160xbf16>, %arg6 = %175: tensor<1x16x90x160xbf16>, %arg7 = %394: tensor<1x3x90x160xbf16>)  attributes {
+      Axis = 1 : i32,
+      IfmOperands = [0 : index, 1 : index, 2 : index],
+      LayerName = "Concat_418",
+      Op = "Concat",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm1",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 40, 90, 160]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm2",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm3",
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 3, 90, 160]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Concat_418",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "PseudoOp",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 59, 90, 160]> : vector<4xindex>
+        }
+      ],
+      current_data_format = "NCHW",
+      data_format = "HCWN",
+      herd_size = dense<4> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x59x90x160xbf16> loc(#loc282)
+      xten_nn.output %464 : tensor<1x59x90x160xbf16> loc(#loc282)
+    } -> tensor<1x59x90x160xbf16> loc(#loc282)
+    %437 = xten_nn.subgraph (%arg5 = %436: tensor<1x59x90x160xbf16>, %arg6 = %12: tensor<32x59x3x3xbf16>, %arg7 = %11: tensor<32xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_419",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 7, 34]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 64, 20, 160]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 59, 90, 160]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[8, 16, 3, 3]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[32, 59, 3, 3]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[32, 59, 3, 3]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Relu_420",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 5, 32]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 2, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 32, 18, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 32, 90, 160]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 191400 : ui64, ofm = 38650 : ui64, wts = 2472 : ui64},
+        computation_cycles = 190465 : ui64,
+        cycle_count = 957000 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "double", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x59x90x160xbf16>, %arg9 = %arg6: tensor<32x59x3x3xbf16>, %arg10 = %arg7: tensor<32xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[1, 1], [1, 1]],
+        LayerName = "Conv_419",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 59, 90, 160]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[32, 59, 3, 3]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Relu_420",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 32, 90, 160]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true,
+          NonNegativeOut = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 1 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 16 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 7 : ui8,
+          config.ifm_sv_width.size = 34 : ui8,
+          config.ksize.height = 3 : ui8,
+          config.ksize.width = 3 : ui8,
+          config.lrelu_alpha = 0.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 0.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 4 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 8 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 7056 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x32x90x160xbf16> loc(#loc284)
+        xten_nn.output %465 : tensor<1x32x90x160xbf16> loc(#loc284)
+      } -> tensor<1x32x90x160xbf16> loc(#loc351)
+      xten_nn.output %464 : tensor<1x32x90x160xbf16> loc(#loc351)
+    } -> tensor<1x32x90x160xbf16> loc(#loc351)
+    %438 = xten_nn.subgraph (%arg5 = %437: tensor<1x32x90x160xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Split_421_Duplicated#0",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 32, 90, 160]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Split_421_Duplicated#0",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      Specializes = "SliceHCWC8Adf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.axis_letter = "C",
+        config.dim_c = 32 : ui32,
+        config.dim_h = 90 : ui32,
+        config.dim_w = 160 : ui32,
+        config.dtype = "bfloat16",
+        config.end = 16 : ui32,
+        config.num_ifm_shim_ch = 2 : ui32,
+        config.num_ofm_shim_ch = 2 : ui32,
+        config.start = 0 : ui32,
+        config.step = 1 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x16x90x160xbf16> loc(#loc285)
+      xten_nn.output %464 : tensor<1x16x90x160xbf16> loc(#loc285)
+    } -> tensor<1x16x90x160xbf16> loc(#loc285)
+    %439 = xten_nn.subgraph (%arg5 = %437: tensor<1x32x90x160xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Split_421_Duplicated#1",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 32, 90, 160]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Split_421_Duplicated#1",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      Specializes = "SliceHCWC8Adf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.axis_letter = "C",
+        config.dim_c = 32 : ui32,
+        config.dim_h = 90 : ui32,
+        config.dim_w = 160 : ui32,
+        config.dtype = "bfloat16",
+        config.end = 32 : ui32,
+        config.num_ifm_shim_ch = 2 : ui32,
+        config.num_ofm_shim_ch = 2 : ui32,
+        config.start = 16 : ui32,
+        config.step = 1 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x16x90x160xbf16> loc(#loc285)
+      xten_nn.output %464 : tensor<1x16x90x160xbf16> loc(#loc285)
+    } -> tensor<1x16x90x160xbf16> loc(#loc285)
+    %440 = xten_nn.subgraph (%arg5 = %439: tensor<1x16x90x160xbf16>, %arg6 = %arg1: tensor<1x16x90x160xbf16>)  attributes {
+      Axis = 1 : i32,
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Concat_422",
+      Op = "Concat",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm1",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm2",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Concat_422",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "PseudoOp",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 32, 90, 160]> : vector<4xindex>
+        }
+      ],
+      current_data_format = "NCHW",
+      data_format = "HCWN",
+      herd_size = dense<4> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x32x90x160xbf16> loc(#loc286)
+      xten_nn.output %464 : tensor<1x32x90x160xbf16> loc(#loc286)
+    } -> tensor<1x32x90x160xbf16> loc(#loc286)
+    %441 = xten_nn.subgraph (%arg5 = %440: tensor<1x32x90x160xbf16>, %arg6 = %10: tensor<32x32x3x3xbf16>, %arg7 = %9: tensor<32xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_423",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 6, 34]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 32, 32, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 32, 90, 160]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[8, 16, 3, 3]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[32, 32, 3, 3]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[32, 32, 3, 3]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_423",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 4, 32]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 2, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 32, 30, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 32, 90, 160]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 98520 : ui64, ofm = 38700 : ui64, wts = 1236 : ui64},
+        computation_cycles = 99125 : ui64,
+        cycle_count = 297375 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "double", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x32x90x160xbf16>, %arg9 = %arg6: tensor<32x32x3x3xbf16>, %arg10 = %arg7: tensor<32xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[1, 1], [1, 1]],
+        LayerName = "Conv_423",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 32, 90, 160]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[32, 32, 3, 3]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_423",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 32, 90, 160]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 16 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 6 : ui8,
+          config.ifm_sv_width.size = 34 : ui8,
+          config.ksize.height = 3 : ui8,
+          config.ksize.width = 3 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 2 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 8 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 3018 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x32x90x160xbf16> loc(#loc287)
+        xten_nn.output %465 : tensor<1x32x90x160xbf16> loc(#loc287)
+      } -> tensor<1x32x90x160xbf16> loc(#loc287)
+      xten_nn.output %464 : tensor<1x32x90x160xbf16> loc(#loc287)
+    } -> tensor<1x32x90x160xbf16> loc(#loc287)
+    %442 = xten_nn.subgraph (%arg5 = %441: tensor<1x32x90x160xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Sigmoid_424",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 8, 32]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 32, 30, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 32, 90, 160]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Sigmoid_424",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 8, 32]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 0, 2, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 32, 30, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 32, 90, 160]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 61590 : ui64, ofm = 30870 : ui64},
+        computation_cycles = 8314 : ui64,
+        cycle_count = 184770 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "double", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x32x90x160xbf16>)  attributes {
+        LayerName = "Sigmoid_424",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 32, 90, 160]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Sigmoid_424",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 32, 90, 160]> : vector<4xindex>
+          }
+        ],
+        Specializes = "SigmoidTemplatedBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.ENABLE_FP16_AS_BF16 = 0 : ui8,
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 8 : ui32,
+          config.ifmsv_height = 8 : ui32,
+          config.ifmsv_width = 32 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 403 : ui64,
+          startup_cycles = 31 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x32x90x160xbf16> loc(#loc288)
+        xten_nn.output %465 : tensor<1x32x90x160xbf16> loc(#loc288)
+      } -> tensor<1x32x90x160xbf16> loc(#loc288)
+      xten_nn.output %464 : tensor<1x32x90x160xbf16> loc(#loc288)
+    } -> tensor<1x32x90x160xbf16> loc(#loc288)
+    %443 = xten_nn.subgraph (%arg5 = %442: tensor<1x32x90x160xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Split_425_Duplicated#1",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 32, 90, 160]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Split_425_Duplicated#1",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      Specializes = "SliceHCWC8Adf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.axis_letter = "C",
+        config.dim_c = 32 : ui32,
+        config.dim_h = 90 : ui32,
+        config.dim_w = 160 : ui32,
+        config.dtype = "bfloat16",
+        config.end = 32 : ui32,
+        config.num_ifm_shim_ch = 2 : ui32,
+        config.num_ofm_shim_ch = 2 : ui32,
+        config.start = 16 : ui32,
+        config.step = 1 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x16x90x160xbf16> loc(#loc289)
+      xten_nn.output %464 : tensor<1x16x90x160xbf16> loc(#loc289)
+    } -> tensor<1x16x90x160xbf16> loc(#loc289)
+    %444 = xten_nn.subgraph (%arg5 = %6: tensor<1x16x90x160xbf16>, %arg6 = %443: tensor<1x16x90x160xbf16>)  attributes {
+      IfmOperands = [1 : index],
+      LayerName = "Sub_431",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 8, 16]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 30, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 8, 16]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 30, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Sub_431",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 8, 16]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 2, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 30, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 61740 : ui64, ifm2 = 61740 : ui64, ofm = 31020 : ui64},
+        computation_cycles = 6566 : ui64,
+        cycle_count = 185220 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "double", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x16x90x160xbf16>, %arg8 = %arg6: tensor<1x16x90x160xbf16>)  attributes {
+        LayerName = "Sub_431",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Sub_431",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          }
+        ],
+        Specializes = "SubBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 8 : ui32,
+          config.ifmsv_height = 8 : ui32,
+          config.ifmsv_width = 16 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 75 : ui64,
+          startup_cycles = 23 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x16x90x160xbf16> loc(#loc2)
+        xten_nn.output %465 : tensor<1x16x90x160xbf16> loc(#loc2)
+      } -> tensor<1x16x90x160xbf16> loc(#loc2)
+      xten_nn.output %464 : tensor<1x16x90x160xbf16> loc(#loc2)
+    } -> tensor<1x16x90x160xbf16> loc(#loc2)
+    %445 = xten_nn.subgraph (%arg5 = %444: tensor<1x16x90x160xbf16>, %arg6 = %arg1: tensor<1x16x90x160xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_432",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 8, 16]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 30, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 8, 16]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 30, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_432",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 8, 16]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 2, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 30, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 61740 : ui64, ifm2 = 61740 : ui64, ofm = 31020 : ui64},
+        computation_cycles = 5698 : ui64,
+        cycle_count = 185220 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "double", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x16x90x160xbf16>, %arg8 = %arg6: tensor<1x16x90x160xbf16>)  attributes {
+        LayerName = "Mul_432",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_432",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 8 : ui32,
+          config.ifmsv_height = 8 : ui32,
+          config.ifmsv_width = 16 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 46 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x16x90x160xbf16> loc(#loc295)
+        xten_nn.output %465 : tensor<1x16x90x160xbf16> loc(#loc295)
+      } -> tensor<1x16x90x160xbf16> loc(#loc295)
+      xten_nn.output %464 : tensor<1x16x90x160xbf16> loc(#loc295)
+    } -> tensor<1x16x90x160xbf16> loc(#loc295)
+    %446 = xten_nn.subgraph (%arg5 = %442: tensor<1x32x90x160xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Split_425_Duplicated#0",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 32, 90, 160]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Split_425_Duplicated#0",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      Specializes = "SliceHCWC8Adf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.axis_letter = "C",
+        config.dim_c = 32 : ui32,
+        config.dim_h = 90 : ui32,
+        config.dim_w = 160 : ui32,
+        config.dtype = "bfloat16",
+        config.end = 16 : ui32,
+        config.num_ifm_shim_ch = 2 : ui32,
+        config.num_ofm_shim_ch = 2 : ui32,
+        config.start = 0 : ui32,
+        config.step = 1 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x16x90x160xbf16> loc(#loc289)
+      xten_nn.output %464 : tensor<1x16x90x160xbf16> loc(#loc289)
+    } -> tensor<1x16x90x160xbf16> loc(#loc289)
+    %447 = xten_nn.subgraph (%arg5 = %446: tensor<1x16x90x160xbf16>, %arg6 = %arg1: tensor<1x16x90x160xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_426",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 8, 16]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 30, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 8, 16]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 30, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_426",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 8, 16]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 2, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 30, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 61740 : ui64, ifm2 = 61740 : ui64, ofm = 31020 : ui64},
+        computation_cycles = 5698 : ui64,
+        cycle_count = 185220 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "double", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x16x90x160xbf16>, %arg8 = %arg6: tensor<1x16x90x160xbf16>)  attributes {
+        LayerName = "Mul_426",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_426",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 8 : ui32,
+          config.ifmsv_height = 8 : ui32,
+          config.ifmsv_width = 16 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 46 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x16x90x160xbf16> loc(#loc290)
+        xten_nn.output %465 : tensor<1x16x90x160xbf16> loc(#loc290)
+      } -> tensor<1x16x90x160xbf16> loc(#loc290)
+      xten_nn.output %464 : tensor<1x16x90x160xbf16> loc(#loc290)
+    } -> tensor<1x16x90x160xbf16> loc(#loc290)
+    %448 = xten_nn.subgraph (%arg5 = %439: tensor<1x16x90x160xbf16>, %arg6 = %447: tensor<1x16x90x160xbf16>)  attributes {
+      Axis = 1 : i32,
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Concat_427",
+      Op = "Concat",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm1",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm2",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Concat_427",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "PseudoOp",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 32, 90, 160]> : vector<4xindex>
+        }
+      ],
+      current_data_format = "NCHW",
+      data_format = "HCWN",
+      herd_size = dense<4> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x32x90x160xbf16> loc(#loc291)
+      xten_nn.output %464 : tensor<1x32x90x160xbf16> loc(#loc291)
+    } -> tensor<1x32x90x160xbf16> loc(#loc291)
+    %449 = xten_nn.subgraph (%arg5 = %448: tensor<1x32x90x160xbf16>, %arg6 = %8: tensor<16x32x3x3xbf16>, %arg7 = %7: tensor<16xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_428",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 6, 34]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 32, 32, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 32, 90, 160]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[8, 16, 3, 3]> : vector<4xindex>,
+          l2_extend_end = dense<[16, 0, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[16, 32, 3, 3]> : vector<4xindex>,
+          l3_extend_end = dense<[16, 0, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[16, 32, 3, 3]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_428",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 4, 32]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 2, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 30, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 98520 : ui64, ofm = 38700 : ui64, wts = 1236 : ui64},
+        computation_cycles = 99125 : ui64,
+        cycle_count = 297375 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "double", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x32x90x160xbf16>, %arg9 = %arg6: tensor<16x32x3x3xbf16>, %arg10 = %arg7: tensor<16xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[1, 1], [1, 1]],
+        LayerName = "Conv_428",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 32, 90, 160]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[16, 32, 3, 3]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_428",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 16 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 6 : ui8,
+          config.ifm_sv_width.size = 34 : ui8,
+          config.ksize.height = 3 : ui8,
+          config.ksize.width = 3 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 2 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 8 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 3018 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x16x90x160xbf16> loc(#loc292)
+        xten_nn.output %465 : tensor<1x16x90x160xbf16> loc(#loc292)
+      } -> tensor<1x16x90x160xbf16> loc(#loc292)
+      xten_nn.output %464 : tensor<1x16x90x160xbf16> loc(#loc292)
+    } -> tensor<1x16x90x160xbf16> loc(#loc292)
+    %450 = xten_nn.subgraph (%arg5 = %449: tensor<1x16x90x160xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Tanh_429",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 23, 8]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Tanh_429",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 23, 8]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 2, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 59080 : ui64, ofm = 29640 : ui64},
+        computation_cycles = 72267 : ui64,
+        cycle_count = 72267 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "single", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x16x90x160xbf16>)  attributes {
+        LayerName = "Tanh_429",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Tanh_429",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          }
+        ],
+        Specializes = "TanhTemplatedBf16",
+        Traits = {
+          Elementwise = true,
+          Unary = true
+        },
+        With = {
+          config.ENABLE_FP16_AS_BF16 = 0 : ui8,
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 8 : ui32,
+          config.ifmsv_height = 23 : ui32,
+          config.ifmsv_width = 8 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 3466 : ui64,
+          startup_cycles = 24 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x16x90x160xbf16> loc(#loc293)
+        xten_nn.output %465 : tensor<1x16x90x160xbf16> loc(#loc293)
+      } -> tensor<1x16x90x160xbf16> loc(#loc293)
+      xten_nn.output %464 : tensor<1x16x90x160xbf16> loc(#loc293)
+    } -> tensor<1x16x90x160xbf16> loc(#loc293)
+    %451 = xten_nn.subgraph (%arg5 = %443: tensor<1x16x90x160xbf16>, %arg6 = %450: tensor<1x16x90x160xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Mul_433",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 8, 16]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 30, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 8, 16]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 30, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Mul_433",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 8, 16]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 2, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 30, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 61740 : ui64, ifm2 = 61740 : ui64, ofm = 31020 : ui64},
+        computation_cycles = 5698 : ui64,
+        cycle_count = 185220 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "double", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x16x90x160xbf16>, %arg8 = %arg6: tensor<1x16x90x160xbf16>)  attributes {
+        LayerName = "Mul_433",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Mul_433",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          }
+        ],
+        Specializes = "MulBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 8 : ui32,
+          config.ifmsv_height = 8 : ui32,
+          config.ifmsv_width = 16 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 46 : ui64,
+          startup_cycles = 25 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x16x90x160xbf16> loc(#loc294)
+        xten_nn.output %465 : tensor<1x16x90x160xbf16> loc(#loc294)
+      } -> tensor<1x16x90x160xbf16> loc(#loc294)
+      xten_nn.output %464 : tensor<1x16x90x160xbf16> loc(#loc294)
+    } -> tensor<1x16x90x160xbf16> loc(#loc294)
+    %452 = xten_nn.subgraph (%arg5 = %445: tensor<1x16x90x160xbf16>, %arg6 = %451: tensor<1x16x90x160xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Add_434",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 8, 16]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 30, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 8, 16]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 30, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_434",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 8, 16]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 2, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 30, 160]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 61740 : ui64, ifm2 = 61740 : ui64, ofm = 31020 : ui64},
+        computation_cycles = 6565 : ui64,
+        cycle_count = 185220 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "double", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x16x90x160xbf16>, %arg8 = %arg6: tensor<1x16x90x160xbf16>)  attributes {
+        LayerName = "Add_434",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_434",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.act = 0 : ui8,
+          config.act_type = "LINEAR",
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 8 : ui32,
+          config.ifmsv_height = 8 : ui32,
+          config.ifmsv_width = 16 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 75 : ui64,
+          startup_cycles = 22 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x16x90x160xbf16> loc(#loc296)
+        xten_nn.output %465 : tensor<1x16x90x160xbf16> loc(#loc296)
+      } -> tensor<1x16x90x160xbf16> loc(#loc296)
+      xten_nn.output %464 : tensor<1x16x90x160xbf16> loc(#loc296)
+    } -> tensor<1x16x90x160xbf16> loc(#loc296)
+    %453 = xten_nn.subgraph (%arg5 = %438: tensor<1x16x90x160xbf16>, %arg6 = %452: tensor<1x16x90x160xbf16>)  attributes {
+      Axis = 1 : i32,
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Concat_435",
+      Op = "Concat",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm1",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm2",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 90, 160]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Concat_435",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "PseudoOp",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 32, 90, 160]> : vector<4xindex>
+        }
+      ],
+      current_data_format = "NCHW",
+      data_format = "HCWN",
+      herd_size = dense<4> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x32x90x160xbf16> loc(#loc297)
+      xten_nn.output %464 : tensor<1x32x90x160xbf16> loc(#loc297)
+    } -> tensor<1x32x90x160xbf16> loc(#loc297)
+    %454 = xten_nn.subgraph (%arg5 = %453: tensor<1x32x90x160xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Resize_437",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 32, 90, 160]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Resize_437",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 32, 180, 320]> : vector<4xindex>
+        }
+      ],
+      Specializes = "ResizeAdf",
+      With = {
+        config.co_trans_mode = 1 : ui32,
+        config.dim_0 = 1 : ui32,
+        config.dim_1 = 32 : ui32,
+        config.dim_2 = 90 : ui32,
+        config.dim_3 = 160 : ui32,
+        config.dtype = "bfloat16",
+        config.mode = 1 : ui32,
+        config.nearest_mode = 0 : ui32,
+        config.num_ifm_shim_ch = 2 : ui32,
+        config.num_ofm_shim_ch = 2 : ui32,
+        config.output_H = 180 : ui32,
+        config.output_W = 320 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x32x180x320xbf16> loc(#loc298)
+      xten_nn.output %464 : tensor<1x32x180x320xbf16> loc(#loc298)
+    } -> tensor<1x32x180x320xbf16> loc(#loc298)
+    %455 = xten_nn.subgraph (%arg5 = %454: tensor<1x32x180x320xbf16>, %arg6 = %166: tensor<1x3x180x320xbf16>)  attributes {
+      Axis = 1 : i32,
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Concat_438",
+      Op = "Concat",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm1",
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 32, 180, 320]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm2",
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Concat_438",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "PseudoOp",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 35, 180, 320]> : vector<4xindex>
+        }
+      ],
+      current_data_format = "NCHW",
+      data_format = "HCWN",
+      herd_size = dense<4> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x35x180x320xbf16> loc(#loc299)
+      xten_nn.output %464 : tensor<1x35x180x320xbf16> loc(#loc299)
+    } -> tensor<1x35x180x320xbf16> loc(#loc299)
+    %456 = xten_nn.subgraph (%arg5 = %455: tensor<1x35x180x320xbf16>, %arg6 = %5: tensor<16x35x3x3xbf16>, %arg7 = %4: tensor<16xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_439",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 8, 6, 66]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 40, 17, 320]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 35, 180, 320]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[8, 8, 3, 3]> : vector<4xindex>,
+          l2_extend_end = dense<[16, 5, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[16, 35, 3, 3]> : vector<4xindex>,
+          l3_extend_end = dense<[16, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[16, 35, 3, 3]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Relu_440",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 4, 64]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 1, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 15, 320]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 180, 320]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 478200 : ui64, ofm = 154200 : ui64, wts = 1650 : ui64},
+        computation_cycles = 534365 : ui64,
+        cycle_count = 6412380 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "double", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x35x180x320xbf16>, %arg9 = %arg6: tensor<16x35x3x3xbf16>, %arg10 = %arg7: tensor<16xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[1, 1], [1, 1]],
+        LayerName = "Conv_439",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 35, 180, 320]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[16, 35, 3, 3]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Relu_440",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 180, 320]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true,
+          NonNegativeOut = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 1 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 8 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 6 : ui8,
+          config.ifm_sv_width.size = 66 : ui8,
+          config.ksize.height = 3 : ui8,
+          config.ksize.width = 3 : ui8,
+          config.lrelu_alpha = 0.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 0.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 5 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 8 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 64 : ui8
+        },
+        estimation = {
+          compute_cycles = 8215 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x16x180x320xbf16> loc(#loc301)
+        xten_nn.output %465 : tensor<1x16x180x320xbf16> loc(#loc301)
+      } -> tensor<1x16x180x320xbf16> loc(#loc352)
+      xten_nn.output %464 : tensor<1x16x180x320xbf16> loc(#loc352)
+    } -> tensor<1x16x180x320xbf16> loc(#loc352)
+    %457 = xten_nn.subgraph (%arg5 = %456: tensor<1x16x180x320xbf16>, %arg6 = %3: tensor<16x16x3x3xbf16>, %arg7 = %2: tensor<16xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_441",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 7, 34]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 22, 320]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 180, 320]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[8, 16, 3, 3]> : vector<4xindex>,
+          l2_extend_end = dense<[16, 0, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[16, 16, 3, 3]> : vector<4xindex>,
+          l3_extend_end = dense<[16, 0, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[16, 16, 3, 3]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Relu_442",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<0> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 8, 5, 32]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 16, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 20, 320]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 180, 320]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 172260 : ui64, ofm = 139140 : ui64, wts = 618 : ui64},
+        computation_cycles = 171455 : ui64,
+        cycle_count = 1550340 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "double", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x16x180x320xbf16>, %arg9 = %arg6: tensor<16x16x3x3xbf16>, %arg10 = %arg7: tensor<16xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[1, 1], [1, 1]],
+        LayerName = "Conv_441",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 180, 320]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[16, 16, 3, 3]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Relu_442",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 180, 320]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true,
+          NonNegativeOut = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 1 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 16 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 7 : ui8,
+          config.ifm_sv_width.size = 34 : ui8,
+          config.ksize.height = 3 : ui8,
+          config.ksize.width = 3 : ui8,
+          config.lrelu_alpha = 0.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 0.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 1 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 8 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 32 : ui8
+        },
+        estimation = {
+          compute_cycles = 1764 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x16x180x320xbf16> loc(#loc303)
+        xten_nn.output %465 : tensor<1x16x180x320xbf16> loc(#loc303)
+      } -> tensor<1x16x180x320xbf16> loc(#loc353)
+      xten_nn.output %464 : tensor<1x16x180x320xbf16> loc(#loc353)
+    } -> tensor<1x16x180x320xbf16> loc(#loc353)
+    %458 = xten_nn.subgraph (%arg5 = %457: tensor<1x16x180x320xbf16>, %arg6 = %1: tensor<4x16x1x1xbf16>, %arg7 = %0: tensor<4xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Conv_443",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 48, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[1, 16, 1, 64]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 16, 20, 320]> : vector<4xindex>,
+          l3_extend_end = dense<0> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 16, 180, 320]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true,
+          l1_extend_end = dense<[4, 48, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<-1> : vector<2xindex>,
+          l1_tile_count = dense<[4, 16, 1, 1]> : vector<4xindex>,
+          l2_extend_end = dense<[28, 48, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[4, 16, 1, 1]> : vector<4xindex>,
+          l3_extend_end = dense<[28, 48, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[4, 16, 1, 1]> : vector<4xindex>
+        },
+        {
+          UnknownDataFormat = true
+        }
+      ],
+      OutputName = "Conv_443",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 4, 1, 64]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 8, 20, 320]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 4, 180, 320]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 463050 : ui64, ofm = 232650 : ui64, wts = 298 : ui64},
+        computation_cycles = 264965 : ui64,
+        cycle_count = 4167450 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3, 4, 0]> : vector<5xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "double", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg8 = %arg5: tensor<1x16x180x320xbf16>, %arg9 = %arg6: tensor<4x16x1x1xbf16>, %arg10 = %arg7: tensor<4xbf16>)  attributes {
+        Dilations = array<i64: 1, 1>,
+        HWPadding = [[0, 0], [0, 0]],
+        LayerName = "Conv_443",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<0> : vector<4xindex>,
+            l3_tile_count = dense<[1, 16, 180, 320]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "wts_data",
+            UnknownDataFormat = true,
+            l3_extend_end = dense<[4, 0, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[4, 16, 1, 1]> : vector<4xindex>
+          },
+          {
+            Port = "data_io.wts",
+            SubPort = "bias",
+            UnknownDataFormat = true
+          }
+        ],
+        OutputName = "Conv_443",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 4, 180, 320]> : vector<4xindex>
+          }
+        ],
+        Specializes = "Conv2DBf16",
+        Traits = {
+          AllowDMAOptimization = true
+        },
+        With = {
+          config.AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 = 1 : ui8,
+          config.act = 0 : ui8,
+          config.act_type = "RELU",
+          config.aie_arch = "aie2p",
+          config.batch_size = 1 : ui8,
+          config.compiler = "chess",
+          config.conv_type = 64 : ui8,
+          config.dtype_ifm = "bfloat16",
+          config.dtype_ofm = "bfloat16",
+          config.dtype_wts = "bfloat16",
+          config.force_och_gran_8 = 1 : ui8,
+          config.ifm_sv_depth.size = 64 : ui16,
+          config.ifm_sv_height.padding = 0 : ui8,
+          config.ifm_sv_height.size = 1 : ui8,
+          config.ifm_sv_width.size = 64 : ui8,
+          config.ksize.height = 1 : ui8,
+          config.ksize.width = 1 : ui8,
+          config.lrelu_alpha = 1.000000e+00 : bf16,
+          config.lrelu_alpha_kernel = 1.000000e+00 : bf16,
+          config.num_ifm_depth_iters = 1 : ui8,
+          config.ofm_offset_packed.left = 0 : ui4,
+          config.ofm_offset_packed.top = 0 : ui4,
+          config.ofm_sv_depth.size = 8 : ui16,
+          config.ofm_width_pad = 0 : ui8,
+          config.stride_h = 1 : ui8,
+          config.stride_w = 1 : ui8,
+          data_io.ofm.dimensions.width.size = 64 : ui8
+        },
+        estimation = {
+          compute_cycles = 1039 : ui64,
+          startup_cycles = 182 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x4x180x320xbf16> loc(#loc304)
+        xten_nn.output %465 : tensor<1x4x180x320xbf16> loc(#loc304)
+      } -> tensor<1x4x180x320xbf16> loc(#loc304)
+      xten_nn.output %464 : tensor<1x4x180x320xbf16> loc(#loc304)
+    } -> tensor<1x4x180x320xbf16> loc(#loc304)
+    %459 = xten_nn.subgraph (%arg5 = %458: tensor<1x4x180x320xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Split_444_Duplicated#1",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 4, 180, 320]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Split_444_Duplicated#1",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<[0, 7, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 1, 180, 320]> : vector<4xindex>
+        }
+      ],
+      Specializes = "SliceHCWC8Adf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.axis_letter = "C",
+        config.dim_c = 8 : ui32,
+        config.dim_h = 180 : ui32,
+        config.dim_w = 320 : ui32,
+        config.dtype = "bfloat16",
+        config.end = 4 : ui32,
+        config.num_ifm_shim_ch = 2 : ui32,
+        config.num_ofm_shim_ch = 2 : ui32,
+        config.start = 3 : ui32,
+        config.step = 1 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x1x180x320xbf16> loc(#loc305)
+      xten_nn.output %464 : tensor<1x1x180x320xbf16> loc(#loc305)
+    } -> tensor<1x1x180x320xbf16> loc(#loc305)
+    %460 = xten_nn.subgraph (%arg5 = %459: tensor<1x1x180x320xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_447",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 7, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 1, 5, 40]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 8, 20, 320]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 7, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 1, 180, 320]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_447",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 7, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 1, 5, 40]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 8, 20, 320]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 7, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 1, 180, 320]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 231120 : ui64, ofm = 115920 : ui64},
+        computation_cycles = 18655 : ui64,
+        cycle_count = 2080080 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "double", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x1x180x320xbf16>)  attributes {
+        LayerName = "Clip_447",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<[0, 7, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 1, 180, 320]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_447",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<[0, 7, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 1, 180, 320]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 1.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 8 : ui32,
+          config.ifmsv_height = 5 : ui32,
+          config.ifmsv_width = 40 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 119 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x1x180x320xbf16> loc(#loc307)
+        xten_nn.output %465 : tensor<1x1x180x320xbf16> loc(#loc307)
+      } -> tensor<1x1x180x320xbf16> loc(#loc307)
+      xten_nn.output %464 : tensor<1x1x180x320xbf16> loc(#loc307)
+    } -> tensor<1x1x180x320xbf16> loc(#loc307)
+    %461 = xten_nn.subgraph (%arg5 = %458: tensor<1x4x180x320xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Split_444_Duplicated#0",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          External = false,
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ifm",
+          l3_extend_end = dense<[0, 4, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 4, 180, 320]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Split_444_Duplicated#0",
+      Overlay = "1x1_1x1_unspecifiedConnectivity",
+      Reason = "TemplatedGraph",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          Port = "data_io.ofm",
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+        }
+      ],
+      Specializes = "SliceHCWC8Adf",
+      With = {
+        config.aie_arch = "aie2p",
+        config.axis_letter = "C",
+        config.dim_c = 8 : ui32,
+        config.dim_h = 180 : ui32,
+        config.dim_w = 320 : ui32,
+        config.dtype = "bfloat16",
+        config.end = 3 : ui32,
+        config.num_ifm_shim_ch = 2 : ui32,
+        config.num_ofm_shim_ch = 2 : ui32,
+        config.start = 0 : ui32,
+        config.step = 1 : ui32
+      },
+      herd_size = dense<1> : vector<2xindex>} {
+      %464 = tensor.empty() : tensor<1x3x180x320xbf16> loc(#loc305)
+      xten_nn.output %464 : tensor<1x3x180x320xbf16> loc(#loc305)
+    } -> tensor<1x3x180x320xbf16> loc(#loc305)
+    %462 = xten_nn.subgraph (%arg5 = %461: tensor<1x3x180x320xbf16>, %arg6 = %166: tensor<1x3x180x320xbf16>)  attributes {
+      IfmOperands = [0 : index, 1 : index],
+      LayerName = "Add_445",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 3, 5, 16]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 8, 20, 320]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+        },
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 3, 5, 16]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 8, 20, 320]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Add_445",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 3, 5, 16]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 8, 20, 320]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 232200 : ui64, ifm2 = 232200 : ui64, ofm = 117000 : ui64},
+        computation_cycles = 34045 : ui64,
+        cycle_count = 2089800 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "double", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg7 = %arg5: tensor<1x3x180x320xbf16>, %arg8 = %arg6: tensor<1x3x180x320xbf16>)  attributes {
+        LayerName = "Add_445",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm1",
+            l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+          },
+          {
+            CurrentDataFormat = "NCHW",
+            External = false,
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm2",
+            l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Add_445",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+          }
+        ],
+        Specializes = "AddBf16",
+        Traits = {
+          Binary = true,
+          Elementwise = true
+        },
+        With = {
+          config.act = 0 : ui8,
+          config.act_type = "LINEAR",
+          config.aie_arch = "aie2p",
+          config.compiler = "chess",
+          config.dtype = "bfloat16",
+          config.ifmsv_depth = 8 : ui32,
+          config.ifmsv_height = 5 : ui32,
+          config.ifmsv_width = 16 : ui32,
+          config.num_kernel_iters = 0 : ui16
+        },
+        estimation = {
+          compute_cycles = 51 : ui64,
+          startup_cycles = 22 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x3x180x320xbf16> loc(#loc11)
+        xten_nn.output %465 : tensor<1x3x180x320xbf16> loc(#loc11)
+      } -> tensor<1x3x180x320xbf16> loc(#loc11)
+      xten_nn.output %464 : tensor<1x3x180x320xbf16> loc(#loc11)
+    } -> tensor<1x3x180x320xbf16> loc(#loc11)
+    %463 = xten_nn.subgraph (%arg5 = %462: tensor<1x3x180x320xbf16>)  attributes {
+      IfmOperands = [0 : index],
+      LayerName = "Clip_446",
+      Operands = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_fullbroadcast = dense<[1, 0]> : vector<2xindex>,
+          l1_tile_count = dense<[1, 3, 5, 40]> : vector<4xindex>,
+          l2_extend_end = dense<0> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 8, 20, 320]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+        }
+      ],
+      OutputName = "Clip_446",
+      Overlay = "4x4_1x4_vertBroadcastLeft_horizBroadcastRight",
+      Reason = "InCoreChain",
+      Results = [
+        {
+          CurrentDataFormat = "NCHW",
+          L3DataFormat = "HCWN",
+          L3Vectorization = "C:8",
+          l1_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l1_extend_start = dense<0> : vector<4xindex>,
+          l1_tile_count = dense<[1, 3, 5, 40]> : vector<4xindex>,
+          l2_extend_end = dense<[0, 24, 0, 0]> : vector<4xindex>,
+          l2_extend_start = dense<0> : vector<4xindex>,
+          l2_tile_count = dense<[1, 8, 20, 320]> : vector<4xindex>,
+          l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+          l3_extend_start = dense<0> : vector<4xindex>,
+          l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+        }
+      ],
+      estimation = {
+        buffer_cycles = {ifm = 231120 : ui64, ofm = 115920 : ui64},
+        computation_cycles = 18655 : ui64,
+        cycle_count = 2080080 : ui64
+      },
+      herd_size = dense<4> : vector<2xindex>,
+      l1_tile_permute = dense<[2, 1, 3]> : vector<3xindex>,
+      memory_configuration = {
+        L1 = {layout = "strict"},
+        L2 = {feature_maps_buffering = "double", layout = "flexible"}
+      }} {
+      %464 = xten_nn.subgraph (%arg6 = %arg5: tensor<1x3x180x320xbf16>)  attributes {
+        LayerName = "Clip_446",
+        Operands = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ifm",
+            l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+          }
+        ],
+        OutputName = "Clip_446",
+        Reason = "MllibKernel",
+        Results = [
+          {
+            CurrentDataFormat = "NCHW",
+            L3DataFormat = "HCWN",
+            L3Vectorization = "C:8",
+            Port = "data_io.ofm",
+            l3_extend_end = dense<[0, 5, 0, 0]> : vector<4xindex>,
+            l3_tile_count = dense<[1, 3, 180, 320]> : vector<4xindex>
+          }
+        ],
+        Specializes = "ClipBf16",
+        Traits = {
+          Elementwise = true,
+          NonNegativeOut = true,
+          Unary = true
+        },
+        With = {
+          config.aie_arch = "aie2p",
+          config.clamp_max = 1.000000e+00 : bf16,
+          config.clamp_min = 0.000000e+00 : bf16,
+          config.compiler = "chess",
+          config.ifm_shift = 0 : si8,
+          config.ifmsv_depth = 8 : ui32,
+          config.ifmsv_height = 5 : ui32,
+          config.ifmsv_width = 40 : ui32,
+          config.num_kernel_iters = 0 : ui16,
+          config.ofm_shift = 0 : si8
+        },
+        estimation = {
+          compute_cycles = 119 : ui64,
+          startup_cycles = 40 : ui64
+        }} {
+        %465 = tensor.empty() : tensor<1x3x180x320xbf16> loc(#loc306)
+        xten_nn.output %465 : tensor<1x3x180x320xbf16> loc(#loc306)
+      } -> tensor<1x3x180x320xbf16> loc(#loc306)
+      xten_nn.output %464 : tensor<1x3x180x320xbf16> loc(#loc306)
+    } -> tensor<1x3x180x320xbf16> loc(#loc306)
+    return %452, %433, %413, %390, %463, %460 : tensor<1x16x90x160xbf16>, tensor<1x20x45x80xbf16>, tensor<1x40x23x40xbf16>, tensor<1x64x12x20xbf16>, tensor<1x3x180x320xbf16>, tensor<1x1x180x320xbf16> loc(#loc308)
+  } loc(#loc308)
+} loc(#loc)
+#loc1 = loc("Div_2")
+#loc2 = loc("Sub_431")
+#loc3 = loc("Sub_411")
+#loc4 = loc("Sub_385")
+#loc5 = loc("Sub_359")
+#loc6 = loc("Div_16")
+#loc7 = loc("Sub_14")
+#loc8 = loc("Initializer_398")
+#loc9 = loc("Slice_7")
+#loc10 = loc("CompilerGeneratedLoc")
+#loc11 = loc("Add_445")
+#loc12 = loc("AveragePool_346")
+#loc13 = loc("Conv_17")
+#loc14 = loc("Add_19")
+#loc15 = loc("Clip_22")
+#loc16 = loc("Div_24")
+#loc17 = loc("Mul_25")
+#loc18 = loc("Conv_26")
+#loc19 = loc("Relu_27")
+#loc20 = loc("Conv_28")
+#loc21 = loc("Add_29")
+#loc22 = loc("Conv_30")
+#loc23 = loc("Relu_31")
+#loc24 = loc("Conv_32")
+#loc25 = loc("Relu_33")
+#loc26 = loc("Conv_34")
+#loc27 = loc("Conv_35")
+#loc28 = loc("Relu_36")
+#loc29 = loc("Conv_37")
+#loc30 = loc("Relu_38")
+#loc31 = loc("Conv_39")
+#loc32 = loc("Add_40")
+#loc33 = loc("Conv_41")
+#loc34 = loc("Relu_42")
+#loc35 = loc("Conv_43")
+#loc36 = loc("Relu_44")
+#loc37 = loc("GlobalAveragePool_45")
+#loc38 = loc("Conv_46")
+#loc39 = loc("Relu_47")
+#loc40 = loc("Conv_48")
+#loc41 = loc("Add_50")
+#loc42 = loc("Clip_53")
+#loc43 = loc("Div_55")
+#loc44 = loc("Mul_56")
+#loc45 = loc("Conv_57")
+#loc46 = loc("Conv_58")
+#loc47 = loc("Relu_59")
+#loc48 = loc("Conv_60")
+#loc49 = loc("Relu_61")
+#loc50 = loc("GlobalAveragePool_62")
+#loc51 = loc("Conv_63")
+#loc52 = loc("Relu_64")
+#loc53 = loc("Conv_65")
+#loc54 = loc("Add_67")
+#loc55 = loc("Clip_70")
+#loc56 = loc("Div_72")
+#loc57 = loc("Mul_73")
+#loc58 = loc("Conv_74")
+#loc59 = loc("Add_75")
+#loc60 = loc("Conv_76")
+#loc61 = loc("Relu_77")
+#loc62 = loc("Conv_78")
+#loc63 = loc("Relu_79")
+#loc64 = loc("GlobalAveragePool_80")
+#loc65 = loc("Conv_81")
+#loc66 = loc("Relu_82")
+#loc67 = loc("Conv_83")
+#loc68 = loc("Add_85")
+#loc69 = loc("Clip_88")
+#loc70 = loc("Div_90")
+#loc71 = loc("Mul_91")
+#loc72 = loc("Conv_92")
+#loc73 = loc("Add_93")
+#loc74 = loc("Conv_94")
+#loc75 = loc("Add_96")
+#loc76 = loc("Clip_99")
+#loc77 = loc("Div_101")
+#loc78 = loc("Mul_102")
+#loc79 = loc("Conv_103")
+#loc80 = loc("Add_105")
+#loc81 = loc("Clip_108")
+#loc82 = loc("Div_110")
+#loc83 = loc("Mul_111")
+#loc84 = loc("Conv_112")
+#loc85 = loc("Conv_113")
+#loc86 = loc("Add_115")
+#loc87 = loc("Clip_118")
+#loc88 = loc("Div_120")
+#loc89 = loc("Mul_121")
+#loc90 = loc("Conv_122")
+#loc91 = loc("Add_124")
+#loc92 = loc("Clip_127")
+#loc93 = loc("Div_129")
+#loc94 = loc("Mul_130")
+#loc95 = loc("Conv_131")
+#loc96 = loc("Add_132")
+#loc97 = loc("Conv_133")
+#loc98 = loc("Add_135")
+#loc99 = loc("Clip_138")
+#loc100 = loc("Div_140")
+#loc101 = loc("Mul_141")
+#loc102 = loc("Conv_142")
+#loc103 = loc("Add_144")
+#loc104 = loc("Clip_147")
+#loc105 = loc("Div_149")
+#loc106 = loc("Mul_150")
+#loc107 = loc("Conv_151")
+#loc108 = loc("Add_152")
+#loc109 = loc("Conv_153")
+#loc110 = loc("Add_155")
+#loc111 = loc("Clip_158")
+#loc112 = loc("Div_160")
+#loc113 = loc("Mul_161")
+#loc114 = loc("Conv_162")
+#loc115 = loc("Add_164")
+#loc116 = loc("Clip_167")
+#loc117 = loc("Div_169")
+#loc118 = loc("Mul_170")
+#loc119 = loc("Conv_171")
+#loc120 = loc("Add_172")
+#loc121 = loc("Conv_173")
+#loc122 = loc("Add_175")
+#loc123 = loc("Clip_178")
+#loc124 = loc("Div_180")
+#loc125 = loc("Mul_181")
+#loc126 = loc("Conv_182")
+#loc127 = loc("Add_184")
+#loc128 = loc("Clip_187")
+#loc129 = loc("Div_189")
+#loc130 = loc("Mul_190")
+#loc131 = loc("GlobalAveragePool_191")
+#loc132 = loc("Conv_192")
+#loc133 = loc("Relu_193")
+#loc134 = loc("Conv_194")
+#loc135 = loc("Add_196")
+#loc136 = loc("Clip_199")
+#loc137 = loc("Div_201")
+#loc138 = loc("Mul_202")
+#loc139 = loc("Conv_203")
+#loc140 = loc("Conv_204")
+#loc141 = loc("Add_206")
+#loc142 = loc("Clip_209")
+#loc143 = loc("Div_211")
+#loc144 = loc("Mul_212")
+#loc145 = loc("Conv_213")
+#loc146 = loc("Add_215")
+#loc147 = loc("Clip_218")
+#loc148 = loc("Div_220")
+#loc149 = loc("Mul_221")
+#loc150 = loc("GlobalAveragePool_222")
+#loc151 = loc("Conv_223")
+#loc152 = loc("Relu_224")
+#loc153 = loc("Conv_225")
+#loc154 = loc("Add_227")
+#loc155 = loc("Clip_230")
+#loc156 = loc("Div_232")
+#loc157 = loc("Mul_233")
+#loc158 = loc("Conv_234")
+#loc159 = loc("Add_235")
+#loc160 = loc("Conv_236")
+#loc161 = loc("Add_238")
+#loc162 = loc("Clip_241")
+#loc163 = loc("Div_243")
+#loc164 = loc("Mul_244")
+#loc165 = loc("Conv_245")
+#loc166 = loc("Add_247")
+#loc167 = loc("Clip_250")
+#loc168 = loc("Div_252")
+#loc169 = loc("Mul_253")
+#loc170 = loc("GlobalAveragePool_254")
+#loc171 = loc("Conv_255")
+#loc172 = loc("Relu_256")
+#loc173 = loc("Conv_257")
+#loc174 = loc("Add_259")
+#loc175 = loc("Clip_262")
+#loc176 = loc("Div_264")
+#loc177 = loc("Mul_265")
+#loc178 = loc("Conv_266")
+#loc179 = loc("Conv_267")
+#loc180 = loc("Add_269")
+#loc181 = loc("Clip_272")
+#loc182 = loc("Div_274")
+#loc183 = loc("Mul_275")
+#loc184 = loc("Conv_276")
+#loc185 = loc("Add_278")
+#loc186 = loc("Clip_281")
+#loc187 = loc("Div_283")
+#loc188 = loc("Mul_284")
+#loc189 = loc("GlobalAveragePool_285")
+#loc190 = loc("Conv_286")
+#loc191 = loc("Relu_287")
+#loc192 = loc("Conv_288")
+#loc193 = loc("Add_290")
+#loc194 = loc("Clip_293")
+#loc195 = loc("Div_295")
+#loc196 = loc("Mul_296")
+#loc197 = loc("Conv_297")
+#loc198 = loc("Add_298")
+#loc199 = loc("Conv_299")
+#loc200 = loc("Add_301")
+#loc201 = loc("Clip_304")
+#loc202 = loc("Div_306")
+#loc203 = loc("Mul_307")
+#loc204 = loc("Conv_308")
+#loc205 = loc("Add_310")
+#loc206 = loc("Clip_313")
+#loc207 = loc("Div_315")
+#loc208 = loc("Mul_316")
+#loc209 = loc("GlobalAveragePool_317")
+#loc210 = loc("Conv_318")
+#loc211 = loc("Relu_319")
+#loc212 = loc("Conv_320")
+#loc213 = loc("Add_322")
+#loc214 = loc("Clip_325")
+#loc215 = loc("Div_327")
+#loc216 = loc("Mul_328")
+#loc217 = loc("Conv_329")
+#loc218 = loc("Add_330")
+#loc219 = loc("Conv_331")
+#loc220 = loc("Add_333")
+#loc221 = loc("Clip_336")
+#loc222 = loc("Div_338")
+#loc223 = loc("Mul_339")
+#loc224 = loc("GlobalAveragePool_342")
+#loc225 = loc("Conv_343")
+#loc226 = loc("Sigmoid_344")
+#loc227 = loc("Mul_345")
+#loc228 = loc("Conv_340")
+#loc229 = loc("Relu_341")
+#loc230 = loc("Split_349")
+#loc231 = loc("Concat_350")
+#loc232 = loc("Conv_351")
+#loc233 = loc("Sigmoid_352")
+#loc234 = loc("Split_353")
+#loc235 = loc("Mul_354")
+#loc236 = loc("Concat_355")
+#loc237 = loc("Conv_356")
+#loc238 = loc("Tanh_357")
+#loc239 = loc("Mul_361")
+#loc240 = loc("Mul_360")
+#loc241 = loc("Add_362")
+#loc242 = loc("Concat_363")
+#loc243 = loc("Resize_365")
+#loc244 = loc("Slice_371")
+#loc245 = loc("AveragePool_347")
+#loc246 = loc("AveragePool_348")
+#loc247 = loc("Concat_372")
+#loc248 = loc("Conv_373")
+#loc249 = loc("Relu_374")
+#loc250 = loc("Split_375")
+#loc251 = loc("Concat_376")
+#loc252 = loc("Conv_377")
+#loc253 = loc("Sigmoid_378")
+#loc254 = loc("Split_379")
+#loc255 = loc("Mul_380")
+#loc256 = loc("Concat_381")
+#loc257 = loc("Conv_382")
+#loc258 = loc("Tanh_383")
+#loc259 = loc("Mul_387")
+#loc260 = loc("Mul_386")
+#loc261 = loc("Add_388")
+#loc262 = loc("Concat_389")
+#loc263 = loc("Resize_391")
+#loc264 = loc("Slice_397")
+#loc265 = loc("Concat_398")
+#loc266 = loc("Conv_399")
+#loc267 = loc("Relu_400")
+#loc268 = loc("Split_401")
+#loc269 = loc("Concat_402")
+#loc270 = loc("Conv_403")
+#loc271 = loc("Sigmoid_404")
+#loc272 = loc("Split_405")
+#loc273 = loc("Mul_406")
+#loc274 = loc("Concat_407")
+#loc275 = loc("Conv_408")
+#loc276 = loc("Tanh_409")
+#loc277 = loc("Mul_413")
+#loc278 = loc("Mul_412")
+#loc279 = loc("Add_414")
+#loc280 = loc("Concat_415")
+#loc281 = loc("Resize_417")
+#loc282 = loc("Concat_418")
+#loc283 = loc("Conv_419")
+#loc284 = loc("Relu_420")
+#loc285 = loc("Split_421")
+#loc286 = loc("Concat_422")
+#loc287 = loc("Conv_423")
+#loc288 = loc("Sigmoid_424")
+#loc289 = loc("Split_425")
+#loc290 = loc("Mul_426")
+#loc291 = loc("Concat_427")
+#loc292 = loc("Conv_428")
+#loc293 = loc("Tanh_429")
+#loc294 = loc("Mul_433")
+#loc295 = loc("Mul_432")
+#loc296 = loc("Add_434")
+#loc297 = loc("Concat_435")
+#loc298 = loc("Resize_437")
+#loc299 = loc("Concat_438")
+#loc300 = loc("Conv_439")
+#loc301 = loc("Relu_440")
+#loc302 = loc("Conv_441")
+#loc303 = loc("Relu_442")
+#loc304 = loc("Conv_443")
+#loc305 = loc("Split_444")
+#loc306 = loc("Clip_446")
+#loc307 = loc("Clip_447")
+#loc308 = loc(fused[#loc1, #loc2, #loc3, #loc4, #loc5, #loc6, #loc7, #loc8, #loc9, #loc10, #loc11, #loc12, #loc13, #loc14, #loc15, #loc16, #loc17, #loc18, #loc19, #loc20, #loc21, #loc22, #loc23, #loc24, #loc25, #loc26, #loc27, #loc28, #loc29, #loc30, #loc31, #loc32, #loc33, #loc34, #loc35, #loc36, #loc37, #loc38, #loc39, #loc40, #loc41, #loc42, #loc43, #loc44, #loc45, #loc46, #loc47, #loc48, #loc49, #loc50, #loc51, #loc52, #loc53, #loc54, #loc55, #loc56, #loc57, #loc58, #loc59, #loc60, #loc61, #loc62, #loc63, #loc64, #loc65, #loc66, #loc67, #loc68, #loc69, #loc70, #loc71, #loc72, #loc73, #loc74, #loc75, #loc76, #loc77, #loc78, #loc79, #loc80, #loc81, #loc82, #loc83, #loc84, #loc85, #loc86, #loc87, #loc88, #loc89, #loc90, #loc91, #loc92, #loc93, #loc94, #loc95, #loc96, #loc97, #loc98, #loc99, #loc100, #loc101, #loc102, #loc103, #loc104, #loc105, #loc106, #loc107, #loc108, #loc109, #loc110, #loc111, #loc112, #loc113, #loc114, #loc115, #loc116, #loc117, #loc118, #loc119, #loc120, #loc121, #loc122, #loc123, #loc124, #loc125, #loc126, #loc127, #loc128, #loc129, #loc130, #loc131, #loc132, #loc133, #loc134, #loc135, #loc136, #loc137, #loc138, #loc139, #loc140, #loc141, #loc142, #loc143, #loc144, #loc145, #loc146, #loc147, #loc148, #loc149, #loc150, #loc151, #loc152, #loc153, #loc154, #loc155, #loc156, #loc157, #loc158, #loc159, #loc160, #loc161, #loc162, #loc163, #loc164, #loc165, #loc166, #loc167, #loc168, #loc169, #loc170, #loc171, #loc172, #loc173, #loc174, #loc175, #loc176, #loc177, #loc178, #loc179, #loc180, #loc181, #loc182, #loc183, #loc184, #loc185, #loc186, #loc187, #loc188, #loc189, #loc190, #loc191, #loc192, #loc193, #loc194, #loc195, #loc196, #loc197, #loc198, #loc199, #loc200, #loc201, #loc202, #loc203, #loc204, #loc205, #loc206, #loc207, #loc208, #loc209, #loc210, #loc211, #loc212, #loc213, #loc214, #loc215, #loc216, #loc217, #loc218, #loc219, #loc220, #loc221, #loc222, #loc223, #loc224, #loc225, #loc226, #loc227, #loc228, #loc229, #loc230, #loc231, #loc232, #loc233, #loc234, #loc235, #loc236, #loc237, #loc238, #loc239, #loc240, #loc241, #loc242, #loc243, #loc244, #loc245, #loc246, #loc247, #loc248, #loc249, #loc250, #loc251, #loc252, #loc253, #loc254, #loc255, #loc256, #loc257, #loc258, #loc259, #loc260, #loc261, #loc262, #loc263, #loc264, #loc265, #loc266, #loc267, #loc268, #loc269, #loc270, #loc271, #loc272, #loc273, #loc274, #loc275, #loc276, #loc277, #loc278, #loc279, #loc280, #loc281, #loc282, #loc283, #loc284, #loc285, #loc286, #loc287, #loc288, #loc289, #loc290, #loc291, #loc292, #loc293, #loc294, #loc295, #loc296, #loc297, #loc298, #loc299, #loc300, #loc301, #loc302, #loc303, #loc304, #loc305, #loc306, #loc307])
+#loc309 = loc(fused[#loc7, #loc8])
+#loc310 = loc(fused[#loc11, #loc9, #loc12])
+#loc311 = loc(fused[#loc9, #loc12, #loc11])
+#loc312 = loc(fused[#loc18, #loc19])
+#loc313 = loc(fused[#loc20, #loc21])
+#loc314 = loc(fused[#loc22, #loc23])
+#loc315 = loc(fused[#loc24, #loc25])
+#loc316 = loc(fused[#loc27, #loc28])
+#loc317 = loc(fused[#loc29, #loc30])
+#loc318 = loc(fused[#loc31, #loc32])
+#loc319 = loc(fused[#loc33, #loc34])
+#loc320 = loc(fused[#loc35, #loc36])
+#loc321 = loc(fused[#loc38, #loc39])
+#loc322 = loc(fused[#loc46, #loc47])
+#loc323 = loc(fused[#loc48, #loc49])
+#loc324 = loc(fused[#loc51, #loc52])
+#loc325 = loc(fused[#loc58, #loc59])
+#loc326 = loc(fused[#loc60, #loc61])
+#loc327 = loc(fused[#loc62, #loc63])
+#loc328 = loc(fused[#loc65, #loc66])
+#loc329 = loc(fused[#loc72, #loc73])
+#loc330 = loc(fused[#loc95, #loc96])
+#loc331 = loc(fused[#loc107, #loc108])
+#loc332 = loc(fused[#loc119, #loc120])
+#loc333 = loc(fused[#loc130, #loc131])
+#loc334 = loc(fused[#loc132, #loc133])
+#loc335 = loc(fused[#loc149, #loc150])
+#loc336 = loc(fused[#loc151, #loc152])
+#loc337 = loc(fused[#loc158, #loc159])
+#loc338 = loc(fused[#loc169, #loc170])
+#loc339 = loc(fused[#loc171, #loc172])
+#loc340 = loc(fused[#loc188, #loc189])
+#loc341 = loc(fused[#loc190, #loc191])
+#loc342 = loc(fused[#loc197, #loc198])
+#loc343 = loc(fused[#loc208, #loc209])
+#loc344 = loc(fused[#loc210, #loc211])
+#loc345 = loc(fused[#loc217, #loc218])
+#loc346 = loc(fused[#loc223, #loc224])
+#loc347 = loc(fused[#loc228, #loc229, #loc227])
+#loc348 = loc(fused[#loc228, #loc229])
+#loc349 = loc(fused[#loc248, #loc249])
+#loc350 = loc(fused[#loc266, #loc267])
+#loc351 = loc(fused[#loc283, #loc284])
+#loc352 = loc(fused[#loc300, #loc301])
+#loc353 = loc(fused[#loc302, #loc303])
+
diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/flexmlrt-hsi.json b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/flexmlrt-hsi.json
new file mode 100644
index 0000000000000000000000000000000000000000..3f869465582054c5842c70d0707eded21657b0ac
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/flexmlrt-hsi.json
@@ -0,0 +1,1253 @@
+{
+    "inputs" : [
+        {
+            "name" : "compute_graph.ifm_ddr",
+            "scale_factor" : -1,
+            "cpu_shape" : [
+                1,
+                180,
+                320,
+                4
+            ],
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+}
diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/l2Placements.json b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/l2Placements.json
new file mode 100644
index 0000000000000000000000000000000000000000..7feb347eea2b2dbae9a740e46e75f26c1e3f49dd
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/l2Placements.json
@@ -0,0 +1,6143 @@
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diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/layer_runtime_params.h b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/layer_runtime_params.h
new file mode 100644
index 0000000000000000000000000000000000000000..7931a8fd4fb4d2cfc919e353041523f350ca33ef
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/layer_runtime_params.h
@@ -0,0 +1,480 @@
+#define LP_SIZE_SKGEN 16
+#define LP_SIZE_GEMM_SKGEN 7
+#define LP_SIZE_GEMM_ELTBINARY_SKGEN 16
+#define LP_SIZE_CONV_ELTBINARY_SKGEN 17
+#define LP_SIZE_ELTBINARY_SKGEN 20
+#define LP_SIZE_ELTUNARY_SKGEN 22
+// array values based on rtp index for layer_1
+const uint32_t layer_params_1[LP_SIZE_SKGEN] = {0x780, 0x0, 0x80000, 0x3b800001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_6
+const uint32_t layer_params_6[LP_SIZE_SKGEN] = {0x280, 0x0, 0xb40000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_7
+const uint32_t layer_params_7[LP_SIZE_SKGEN] = {0x280, 0x0, 0xb40000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_8
+const uint32_t layer_params_8[LP_SIZE_SKGEN] = {0x80a42, 0x3030008, 0x1021100, 0x3f80, 0x50040, 0x10006, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_9
+const uint32_t layer_params_9[LP_SIZE_SKGEN] = {0x5c0, 0x0, 0x140000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_10
+const uint32_t layer_params_10[LP_SIZE_SKGEN] = {0x780, 0x0, 0x10, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_11
+const uint32_t layer_params_11[LP_SIZE_SKGEN] = {0x5c0, 0x0, 0x140000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_12
+const uint32_t layer_params_12[LP_SIZE_SKGEN] = {0x400, 0x0, 0x1e0000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_13
+const uint32_t layer_params_13[LP_SIZE_SKGEN] = {0x1080812, 0x10303, 0x500, 0x28, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_14
+const uint32_t layer_params_14[LP_SIZE_CONV_ELTBINARY_SKGEN] = {0x400220, 0x1010008, 0x1020000, 0x3f80, 0x50040, 0x1000c, 0x0, 0x0, 0x200, 0x0, 0x3c0000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_15
+const uint32_t layer_params_15[LP_SIZE_SKGEN] = {0x400908, 0x1010010, 0x1010000, 0x1000000, 0x5000c, 0x1000a, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_16
+const uint32_t layer_params_16[LP_SIZE_SKGEN] = {0x208061a, 0x10303, 0x540, 0x54, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_18
+const uint32_t layer_params_18[LP_SIZE_SKGEN] = {0x400410, 0x1010010, 0x1010000, 0x3f80, 0x50000, 0x10003, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_19
+const uint32_t layer_params_19[LP_SIZE_SKGEN] = {0x400220, 0x1010018, 0x1020000, 0x1000000, 0x30040, 0x10006, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_20
+const uint32_t layer_params_20[LP_SIZE_SKGEN] = {0x1080812, 0x10303, 0x500, 0x1e, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_22
+const uint32_t layer_params_22[LP_SIZE_CONV_ELTBINARY_SKGEN] = {0x480410, 0x1010010, 0x1010000, 0x3f80, 0x50000, 0x10003, 0x0, 0x0, 0x400, 0x0, 0xf0000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_23
+const uint32_t layer_params_23[LP_SIZE_SKGEN] = {0x400220, 0x1010018, 0x1020000, 0x1000000, 0x30040, 0x10006, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_24
+const uint32_t layer_params_24[LP_SIZE_SKGEN] = {0x2080814, 0x10505, 0x500, 0x2d, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_26
+const uint32_t layer_params_26[LP_SIZE_SKGEN] = {0x1, 0x20, 0x40, 0x2, 0x1, 0x1, 0xf, 0x0, 0x3a8e, 0x0, 0xf, 0x398, 0x1, 0x48, 0x0, 0x0};
+// array values based on rtp index for layer_27
+const uint32_t layer_params_27[LP_SIZE_SKGEN] = {0x480110, 0x1010010, 0x1020000, 0x1000000, 0x1000c, 0x10001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_28
+const uint32_t layer_params_28[LP_SIZE_SKGEN] = {0x400108, 0x1010020, 0x1010000, 0x3f80, 0x1000c, 0x10001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_29
+const uint32_t layer_params_29[LP_SIZE_SKGEN] = {0x180, 0x0, 0x10000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_30
+const uint32_t layer_params_30[LP_SIZE_SKGEN] = {0x100, 0x0, 0x1, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_31
+const uint32_t layer_params_31[LP_SIZE_SKGEN] = {0x200, 0x0, 0x10000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_33
+const uint32_t layer_params_33[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x60000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_34
+const uint32_t layer_params_34[LP_SIZE_SKGEN] = {0x480608, 0x1010010, 0x1010000, 0x3f80, 0x5000c, 0x10001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_35
+const uint32_t layer_params_35[LP_SIZE_SKGEN] = {0x400220, 0x1010020, 0x1020000, 0x1000000, 0x20040, 0x10003, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_36
+const uint32_t layer_params_36[LP_SIZE_SKGEN] = {0x1080a0c, 0x10505, 0x3c0, 0x14, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_38
+const uint32_t layer_params_38[LP_SIZE_SKGEN] = {0x1, 0x20, 0x40, 0x2, 0x1, 0x1, 0xf, 0x0, 0x3a8e, 0x0, 0xf, 0x398, 0x1, 0x78, 0x0, 0x0};
+// array values based on rtp index for layer_39
+const uint32_t layer_params_39[LP_SIZE_SKGEN] = {0x780110, 0x1010010, 0x1020000, 0x1000000, 0x1000c, 0x10001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_40
+const uint32_t layer_params_40[LP_SIZE_SKGEN] = {0x400108, 0x1010020, 0x1010000, 0x3f80, 0x1000c, 0x10001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_41
+const uint32_t layer_params_41[LP_SIZE_SKGEN] = {0x180, 0x0, 0x10000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_42
+const uint32_t layer_params_42[LP_SIZE_SKGEN] = {0x100, 0x0, 0x1, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_43
+const uint32_t layer_params_43[LP_SIZE_SKGEN] = {0x200, 0x0, 0x10000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_45
+const uint32_t layer_params_45[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x80000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_46
+const uint32_t layer_params_46[LP_SIZE_CONV_ELTBINARY_SKGEN] = {0x400128, 0x1010010, 0x2050000, 0x3f80, 0x1000c, 0x10006, 0x0, 0x0, 0x280, 0x0, 0x60000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_47
+const uint32_t layer_params_47[LP_SIZE_SKGEN] = {0x400220, 0x1010020, 0x1020000, 0x1000000, 0x20040, 0x10003, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_48
+const uint32_t layer_params_48[LP_SIZE_SKGEN] = {0x1080a0c, 0x10505, 0x3c0, 0x14, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_50
+const uint32_t layer_params_50[LP_SIZE_SKGEN] = {0x1, 0x20, 0x40, 0x2, 0x1, 0x1, 0xf, 0x0, 0x3a8e, 0x0, 0xf, 0x398, 0x1, 0x78, 0x0, 0x0};
+// array values based on rtp index for layer_51
+const uint32_t layer_params_51[LP_SIZE_SKGEN] = {0x780110, 0x1010010, 0x1020000, 0x1000000, 0x1000c, 0x10001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_52
+const uint32_t layer_params_52[LP_SIZE_SKGEN] = {0x400108, 0x1010020, 0x1010000, 0x3f80, 0x1000c, 0x10001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_53
+const uint32_t layer_params_53[LP_SIZE_SKGEN] = {0x180, 0x0, 0x10000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_54
+const uint32_t layer_params_54[LP_SIZE_SKGEN] = {0x100, 0x0, 0x1, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_55
+const uint32_t layer_params_55[LP_SIZE_SKGEN] = {0x200, 0x0, 0x10000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_57
+const uint32_t layer_params_57[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x80000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_58
+const uint32_t layer_params_58[LP_SIZE_CONV_ELTBINARY_SKGEN] = {0x400128, 0x1010010, 0x2050000, 0x3f80, 0x1000c, 0x10006, 0x0, 0x0, 0x280, 0x0, 0x60000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_59
+const uint32_t layer_params_59[LP_SIZE_SKGEN] = {0x400220, 0x1010020, 0x1020000, 0x3f80, 0x20040, 0x20003, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_60
+const uint32_t layer_params_60[LP_SIZE_SKGEN] = {0x780, 0x0, 0x80000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_61
+const uint32_t layer_params_61[LP_SIZE_SKGEN] = {0x780, 0x0, 0x8, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_62
+const uint32_t layer_params_62[LP_SIZE_SKGEN] = {0x780, 0x0, 0x80000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_63
+const uint32_t layer_params_63[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x100000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_65
+const uint32_t layer_params_65[LP_SIZE_SKGEN] = {0x2080a0a, 0x303, 0x3c0, 0x28, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_66
+const uint32_t layer_params_66[LP_SIZE_SKGEN] = {0x780, 0x0, 0x20000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_67
+const uint32_t layer_params_67[LP_SIZE_SKGEN] = {0x780, 0x0, 0x2, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_68
+const uint32_t layer_params_68[LP_SIZE_SKGEN] = {0x780, 0x0, 0x20000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_69
+const uint32_t layer_params_69[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x40000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_70
+const uint32_t layer_params_70[LP_SIZE_SKGEN] = {0x500120, 0x1010018, 0x3020000, 0x3f80, 0x10040, 0x10003, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_71
+const uint32_t layer_params_71[LP_SIZE_SKGEN] = {0x500120, 0x1010020, 0x1020000, 0x3f80, 0x10040, 0x20003, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_72
+const uint32_t layer_params_72[LP_SIZE_SKGEN] = {0x780, 0x0, 0x20000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_73
+const uint32_t layer_params_73[LP_SIZE_SKGEN] = {0x780, 0x0, 0x2, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_74
+const uint32_t layer_params_74[LP_SIZE_SKGEN] = {0x780, 0x0, 0x20000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_75
+const uint32_t layer_params_75[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x40000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_76
+const uint32_t layer_params_76[LP_SIZE_SKGEN] = {0x108061a, 0x303, 0x540, 0x7, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_77
+const uint32_t layer_params_77[LP_SIZE_SKGEN] = {0x780, 0x0, 0x20000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_78
+const uint32_t layer_params_78[LP_SIZE_SKGEN] = {0x780, 0x0, 0x2, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_79
+const uint32_t layer_params_79[LP_SIZE_SKGEN] = {0x780, 0x0, 0x20000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_80
+const uint32_t layer_params_80[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x40000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_81
+const uint32_t layer_params_81[LP_SIZE_CONV_ELTBINARY_SKGEN] = {0x680120, 0x1010018, 0x2020000, 0x3f80, 0x10040, 0x10003, 0x0, 0x0, 0x300, 0x0, 0x30000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_82
+const uint32_t layer_params_82[LP_SIZE_SKGEN] = {0x500308, 0x1010030, 0x1010000, 0x3f80, 0x3000c, 0x10001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_83
+const uint32_t layer_params_83[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x30000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_84
+const uint32_t layer_params_84[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x3, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_85
+const uint32_t layer_params_85[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x30000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_86
+const uint32_t layer_params_86[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x30000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_87
+const uint32_t layer_params_87[LP_SIZE_SKGEN] = {0x108061a, 0x303, 0x540, 0x6, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_88
+const uint32_t layer_params_88[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x30000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_89
+const uint32_t layer_params_89[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x3, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_90
+const uint32_t layer_params_90[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x30000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_91
+const uint32_t layer_params_91[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x30000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_92
+const uint32_t layer_params_92[LP_SIZE_CONV_ELTBINARY_SKGEN] = {0x600120, 0x1010018, 0x2020000, 0x3f80, 0x10040, 0x10003, 0x0, 0x0, 0x300, 0x0, 0x30000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_93
+const uint32_t layer_params_93[LP_SIZE_SKGEN] = {0x500308, 0x1010030, 0x1010000, 0x3f80, 0x3000c, 0x10001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_94
+const uint32_t layer_params_94[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x30000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_95
+const uint32_t layer_params_95[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x3, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_96
+const uint32_t layer_params_96[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x30000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_97
+const uint32_t layer_params_97[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x30000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_98
+const uint32_t layer_params_98[LP_SIZE_SKGEN] = {0x108061a, 0x303, 0x540, 0x6, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_99
+const uint32_t layer_params_99[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x30000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_100
+const uint32_t layer_params_100[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x3, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_101
+const uint32_t layer_params_101[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x30000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_102
+const uint32_t layer_params_102[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x30000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_103
+const uint32_t layer_params_103[LP_SIZE_CONV_ELTBINARY_SKGEN] = {0x600120, 0x1010018, 0x2020000, 0x3f80, 0x10040, 0x10003, 0x0, 0x0, 0x300, 0x0, 0x30000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_104
+const uint32_t layer_params_104[LP_SIZE_SKGEN] = {0x500120, 0x1010028, 0x1020000, 0x3f80, 0x10040, 0x30003, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_105
+const uint32_t layer_params_105[LP_SIZE_SKGEN] = {0x780, 0x0, 0x40000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_106
+const uint32_t layer_params_106[LP_SIZE_SKGEN] = {0x780, 0x0, 0x4, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_107
+const uint32_t layer_params_107[LP_SIZE_SKGEN] = {0x780, 0x0, 0x40000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_108
+const uint32_t layer_params_108[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x80000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_109
+const uint32_t layer_params_109[LP_SIZE_SKGEN] = {0x108061a, 0x303, 0x540, 0xf, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_110
+const uint32_t layer_params_110[LP_SIZE_SKGEN] = {0x780, 0x0, 0x40000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_111
+const uint32_t layer_params_111[LP_SIZE_SKGEN] = {0x780, 0x0, 0x4, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_112
+const uint32_t layer_params_112[LP_SIZE_SKGEN] = {0x780, 0x0, 0x40000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_113
+const uint32_t layer_params_113[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x80000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_115
+const uint32_t layer_params_115[LP_SIZE_SKGEN] = {0x1, 0x28, 0x30, 0x2, 0x1, 0x3, 0x5, 0x0, 0x3b89, 0x0, 0xf, 0xf0, 0x1, 0x1e0, 0x0, 0x0};
+// array values based on rtp index for layer_116
+const uint32_t layer_params_116[LP_SIZE_SKGEN] = {0x780108, 0x1010020, 0x4010000, 0x1000000, 0x1000c, 0x10001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_117
+const uint32_t layer_params_117[LP_SIZE_SKGEN] = {0x780108, 0x1010020, 0x1010000, 0x3f80, 0x1000c, 0x40001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_118
+const uint32_t layer_params_118[LP_SIZE_SKGEN] = {0x180, 0x0, 0x10000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_119
+const uint32_t layer_params_119[LP_SIZE_SKGEN] = {0x100, 0x0, 0x1, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_120
+const uint32_t layer_params_120[LP_SIZE_SKGEN] = {0x200, 0x0, 0x10000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_122
+const uint32_t layer_params_122[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x80000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_123
+const uint32_t layer_params_123[LP_SIZE_SKGEN] = {0x600120, 0x1010020, 0x5020000, 0x3f80, 0x10000, 0x10003, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_124
+const uint32_t layer_params_124[LP_SIZE_SKGEN] = {0x400120, 0x1010038, 0x2020000, 0x3f80, 0x10040, 0x30003, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_125
+const uint32_t layer_params_125[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0xb0000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_126
+const uint32_t layer_params_126[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0xb, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_127
+const uint32_t layer_params_127[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0xb0000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_128
+const uint32_t layer_params_128[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0xb0000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_129
+const uint32_t layer_params_129[LP_SIZE_SKGEN] = {0x108061a, 0x303, 0x540, 0x15, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_130
+const uint32_t layer_params_130[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0xb0000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_131
+const uint32_t layer_params_131[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0xb, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_132
+const uint32_t layer_params_132[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0xb0000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_133
+const uint32_t layer_params_133[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0xb0000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_135
+const uint32_t layer_params_135[LP_SIZE_SKGEN] = {0x1, 0x38, 0x20, 0x2, 0x1, 0x3, 0x8, 0x0, 0x3b89, 0x0, 0x18, 0xf0, 0x1, 0x2a0, 0x0, 0x0};
+// array values based on rtp index for layer_136
+const uint32_t layer_params_136[LP_SIZE_SKGEN] = {0x600108, 0x1010030, 0x7010000, 0x1000000, 0x1000c, 0x10001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_137
+const uint32_t layer_params_137[LP_SIZE_SKGEN] = {0xa80110, 0x1010010, 0x1020000, 0x3f80, 0x1000c, 0xb0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_138
+const uint32_t layer_params_138[LP_SIZE_SKGEN] = {0x180, 0x0, 0x10000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_139
+const uint32_t layer_params_139[LP_SIZE_SKGEN] = {0x100, 0x0, 0x1, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_140
+const uint32_t layer_params_140[LP_SIZE_SKGEN] = {0x200, 0x0, 0x10000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_142
+const uint32_t layer_params_142[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0xb0000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_143
+const uint32_t layer_params_143[LP_SIZE_CONV_ELTBINARY_SKGEN] = {0x600120, 0x1010020, 0x7020000, 0x3f80, 0x10000, 0x10003, 0x0, 0x0, 0x400, 0x0, 0x30000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_144
+const uint32_t layer_params_144[LP_SIZE_SKGEN] = {0x400120, 0x1010038, 0x2020000, 0x3f80, 0x10040, 0x30003, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_145
+const uint32_t layer_params_145[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0xb0000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_146
+const uint32_t layer_params_146[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0xb, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_147
+const uint32_t layer_params_147[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0xb0000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_148
+const uint32_t layer_params_148[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0xb0000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_149
+const uint32_t layer_params_149[LP_SIZE_SKGEN] = {0x1080a10, 0x909, 0x500, 0x7e, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_150
+const uint32_t layer_params_150[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0xb0000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_151
+const uint32_t layer_params_151[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0xb, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_152
+const uint32_t layer_params_152[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0xb0000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_153
+const uint32_t layer_params_153[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0xb0000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_155
+const uint32_t layer_params_155[LP_SIZE_SKGEN] = {0x1, 0x38, 0x20, 0x2, 0x1, 0x3, 0x8, 0x0, 0x3b89, 0x0, 0x18, 0xf0, 0x1, 0x2a0, 0x0, 0x0};
+// array values based on rtp index for layer_156
+const uint32_t layer_params_156[LP_SIZE_SKGEN] = {0x600108, 0x1010030, 0x7010000, 0x1000000, 0x1000c, 0x10001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_157
+const uint32_t layer_params_157[LP_SIZE_SKGEN] = {0xa80110, 0x1010010, 0x1020000, 0x3f80, 0x1000c, 0xb0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_158
+const uint32_t layer_params_158[LP_SIZE_SKGEN] = {0x180, 0x0, 0x10000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_159
+const uint32_t layer_params_159[LP_SIZE_SKGEN] = {0x100, 0x0, 0x1, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_160
+const uint32_t layer_params_160[LP_SIZE_SKGEN] = {0x200, 0x0, 0x10000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_162
+const uint32_t layer_params_162[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0xb0000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_163
+const uint32_t layer_params_163[LP_SIZE_SKGEN] = {0x500120, 0x1010028, 0x9020000, 0x3f80, 0x10040, 0x10003, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_164
+const uint32_t layer_params_164[LP_SIZE_SKGEN] = {0x500120, 0x1010028, 0x2020000, 0x3f80, 0x10040, 0x60003, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_165
+const uint32_t layer_params_165[LP_SIZE_SKGEN] = {0x640, 0x0, 0x90000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_166
+const uint32_t layer_params_166[LP_SIZE_SKGEN] = {0x640, 0x0, 0x9, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_167
+const uint32_t layer_params_167[LP_SIZE_SKGEN] = {0x640, 0x0, 0x90000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_168
+const uint32_t layer_params_168[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x140000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_169
+const uint32_t layer_params_169[LP_SIZE_SKGEN] = {0x1080a10, 0x909, 0x500, 0xb4, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_170
+const uint32_t layer_params_170[LP_SIZE_SKGEN] = {0x640, 0x0, 0x90000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_171
+const uint32_t layer_params_171[LP_SIZE_SKGEN] = {0x640, 0x0, 0x9, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_172
+const uint32_t layer_params_172[LP_SIZE_SKGEN] = {0x640, 0x0, 0x90000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_173
+const uint32_t layer_params_173[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x140000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_175
+const uint32_t layer_params_175[LP_SIZE_SKGEN] = {0x1, 0x28, 0x30, 0x2, 0x1, 0x6, 0x5, 0x0, 0x3b89, 0x0, 0x1e, 0xf0, 0x1, 0x3c0, 0x0, 0x0};
+// array values based on rtp index for layer_176
+const uint32_t layer_params_176[LP_SIZE_SKGEN] = {0xc00110, 0x1010010, 0x5020000, 0x1000000, 0x1000c, 0x40001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_177
+const uint32_t layer_params_177[LP_SIZE_SKGEN] = {0x500108, 0x1010030, 0x3010000, 0x3f80, 0x1000c, 0x50001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_178
+const uint32_t layer_params_178[LP_SIZE_SKGEN] = {0x180, 0x0, 0x10000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_179
+const uint32_t layer_params_179[LP_SIZE_SKGEN] = {0x100, 0x0, 0x1, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_180
+const uint32_t layer_params_180[LP_SIZE_SKGEN] = {0x200, 0x0, 0x10000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_182
+const uint32_t layer_params_182[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0xf0000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_183
+const uint32_t layer_params_183[LP_SIZE_CONV_ELTBINARY_SKGEN] = {0x700120, 0x1010018, 0x9020000, 0x3f80, 0x10040, 0x20003, 0x0, 0x0, 0x300, 0x0, 0x60000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_184
+const uint32_t layer_params_184[LP_SIZE_SKGEN] = {0x500120, 0x1010028, 0x2020000, 0x3f80, 0x10040, 0x60003, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_185
+const uint32_t layer_params_185[LP_SIZE_SKGEN] = {0x640, 0x0, 0x90000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_186
+const uint32_t layer_params_186[LP_SIZE_SKGEN] = {0x640, 0x0, 0x9, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_187
+const uint32_t layer_params_187[LP_SIZE_SKGEN] = {0x640, 0x0, 0x90000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_188
+const uint32_t layer_params_188[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x140000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_189
+const uint32_t layer_params_189[LP_SIZE_SKGEN] = {0x1080a10, 0x909, 0x500, 0xb4, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_190
+const uint32_t layer_params_190[LP_SIZE_SKGEN] = {0x640, 0x0, 0x90000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_191
+const uint32_t layer_params_191[LP_SIZE_SKGEN] = {0x640, 0x0, 0x9, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_192
+const uint32_t layer_params_192[LP_SIZE_SKGEN] = {0x640, 0x0, 0x90000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_193
+const uint32_t layer_params_193[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x140000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_195
+const uint32_t layer_params_195[LP_SIZE_SKGEN] = {0x1, 0x28, 0x30, 0x2, 0x1, 0x6, 0x5, 0x0, 0x3b89, 0x0, 0x1e, 0xf0, 0x1, 0x3c0, 0x0, 0x0};
+// array values based on rtp index for layer_196
+const uint32_t layer_params_196[LP_SIZE_SKGEN] = {0xc00110, 0x1010010, 0x5020000, 0x1000000, 0x1000c, 0x40001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_197
+const uint32_t layer_params_197[LP_SIZE_SKGEN] = {0x500108, 0x1010030, 0x3010000, 0x3f80, 0x1000c, 0x50001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_198
+const uint32_t layer_params_198[LP_SIZE_SKGEN] = {0x180, 0x0, 0x10000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_199
+const uint32_t layer_params_199[LP_SIZE_SKGEN] = {0x100, 0x0, 0x1, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_200
+const uint32_t layer_params_200[LP_SIZE_SKGEN] = {0x200, 0x0, 0x10000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_202
+const uint32_t layer_params_202[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0xf0000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_203
+const uint32_t layer_params_203[LP_SIZE_CONV_ELTBINARY_SKGEN] = {0x700120, 0x1010018, 0x9020000, 0x3f80, 0x10040, 0x20003, 0x0, 0x0, 0x300, 0x0, 0x60000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_204
+const uint32_t layer_params_204[LP_SIZE_SKGEN] = {0x500120, 0x1010028, 0x2020000, 0x3f80, 0x10040, 0x60003, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_205
+const uint32_t layer_params_205[LP_SIZE_SKGEN] = {0x640, 0x0, 0x90000, 0x40400001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_206
+const uint32_t layer_params_206[LP_SIZE_SKGEN] = {0x640, 0x0, 0x9, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x40c0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_207
+const uint32_t layer_params_207[LP_SIZE_SKGEN] = {0x640, 0x0, 0x90000, 0x3e2a0001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_208
+const uint32_t layer_params_208[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x140000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_210
+const uint32_t layer_params_210[LP_SIZE_SKGEN] = {0x1, 0x28, 0x30, 0x2, 0x1, 0x6, 0x5, 0x0, 0x3b89, 0x0, 0x1e, 0xf0, 0x1, 0x3c0, 0x0, 0x0};
+// array values based on rtp index for layer_211
+const uint32_t layer_params_211[LP_SIZE_SKGEN] = {0xc00110, 0x1010010, 0x5020000, 0x3f80, 0x1000c, 0x20001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_212
+const uint32_t layer_params_212[LP_SIZE_SKGEN] = {0x200, 0x0, 0x1, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_214
+const uint32_t layer_params_214[LP_SIZE_CONV_ELTBINARY_SKGEN] = {0x600120, 0x1010020, 0xa020000, 0x1000000, 0x10000, 0x10003, 0x0, 0x0, 0x400, 0x0, 0x30000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x1};
+// array values based on rtp index for layer_218
+const uint32_t layer_params_218[LP_SIZE_SKGEN] = {0x100522, 0x3030010, 0x8020000, 0x3f80, 0x10000, 0x20001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_219
+const uint32_t layer_params_219[LP_SIZE_SKGEN] = {0x780, 0x0, 0x1, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_221
+const uint32_t layer_params_221[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x10000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_222
+const uint32_t layer_params_222[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x10000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_224
+const uint32_t layer_params_224[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x10000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_226
+const uint32_t layer_params_226[LP_SIZE_SKGEN] = {0x100522, 0x3030010, 0x8020000, 0x3f80, 0x10000, 0x10001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_227
+const uint32_t layer_params_227[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x1, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_228
+const uint32_t layer_params_228[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x10000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_229
+const uint32_t layer_params_229[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x10000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_233
+const uint32_t layer_params_233[LP_SIZE_SKGEN] = {0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x80250, 0x102, 0x0, 0x0, 0x5000000, 0x60, 0x3e800000, 0x0};
+// array values based on rtp index for layer_234
+const uint32_t layer_params_234[LP_SIZE_SKGEN] = {0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x80c10, 0x102, 0x0, 0x0, 0x6000000, 0x14, 0x3e800000, 0x0};
+// array values based on rtp index for layer_235
+const uint32_t layer_params_235[LP_SIZE_SKGEN] = {0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x80c10, 0x102, 0x0, 0x0, 0x6000000, 0x5, 0x3e800000, 0x0};
+// array values based on rtp index for layer_237
+const uint32_t layer_params_237[LP_SIZE_SKGEN] = {0x100532, 0x3030010, 0xb030000, 0x1000000, 0x10000, 0x20002, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_241
+const uint32_t layer_params_241[LP_SIZE_SKGEN] = {0x100532, 0x3030010, 0x5030000, 0x3f80, 0x10000, 0x20002, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_242
+const uint32_t layer_params_242[LP_SIZE_SKGEN] = {0x780, 0x0, 0x3, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_244
+const uint32_t layer_params_244[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x40000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_245
+const uint32_t layer_params_245[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x40000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_247
+const uint32_t layer_params_247[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x40000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_249
+const uint32_t layer_params_249[LP_SIZE_SKGEN] = {0x100532, 0x3030010, 0x5030000, 0x3f80, 0x10000, 0x10002, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_250
+const uint32_t layer_params_250[LP_SIZE_SKGEN] = {0x780, 0x0, 0x2, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_251
+const uint32_t layer_params_251[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x40000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_252
+const uint32_t layer_params_252[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x40000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_257
+const uint32_t layer_params_257[LP_SIZE_SKGEN] = {0x100e12, 0x3030010, 0x7010000, 0x1000000, 0x50000, 0x10001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_261
+const uint32_t layer_params_261[LP_SIZE_SKGEN] = {0x100e12, 0x3030010, 0x3010000, 0x3f80, 0x50000, 0x10001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_262
+const uint32_t layer_params_262[LP_SIZE_SKGEN] = {0x780, 0x0, 0x8, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_264
+const uint32_t layer_params_264[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x80000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_265
+const uint32_t layer_params_265[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x80000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_267
+const uint32_t layer_params_267[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x80000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_269
+const uint32_t layer_params_269[LP_SIZE_SKGEN] = {0x80e22, 0x3030008, 0x5020000, 0x3f80, 0x30040, 0x10001, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_270
+const uint32_t layer_params_270[LP_SIZE_SKGEN] = {0x780, 0x0, 0x4, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_271
+const uint32_t layer_params_271[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x80000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_272
+const uint32_t layer_params_272[LP_SIZE_SKGEN] = {0x3c0, 0x0, 0x80000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_276
+const uint32_t layer_params_276[LP_SIZE_SKGEN] = {0x100722, 0x3030008, 0x4020000, 0x1000000, 0x50040, 0x10005, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_280
+const uint32_t layer_params_280[LP_SIZE_SKGEN] = {0x100622, 0x3030008, 0x2020000, 0x3f80, 0x50040, 0x10006, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_281
+const uint32_t layer_params_281[LP_SIZE_SKGEN] = {0x800, 0x0, 0xf, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_283
+const uint32_t layer_params_283[LP_SIZE_SKGEN] = {0x400, 0x0, 0x1e0000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_284
+const uint32_t layer_params_284[LP_SIZE_SKGEN] = {0x400, 0x0, 0x1e0000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_286
+const uint32_t layer_params_286[LP_SIZE_SKGEN] = {0x400, 0x0, 0x1e0000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_288
+const uint32_t layer_params_288[LP_SIZE_SKGEN] = {0x100622, 0x3030008, 0x2020000, 0x3f80, 0x50040, 0x10006, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_289
+const uint32_t layer_params_289[LP_SIZE_SKGEN] = {0x5c0, 0x0, 0x14, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_290
+const uint32_t layer_params_290[LP_SIZE_SKGEN] = {0x400, 0x0, 0x1e0000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_291
+const uint32_t layer_params_291[LP_SIZE_SKGEN] = {0x400, 0x0, 0x1e0000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_295
+const uint32_t layer_params_295[LP_SIZE_SKGEN] = {0x80642, 0x3030008, 0x5040000, 0x1000000, 0x50040, 0x1000c, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_296
+const uint32_t layer_params_296[LP_SIZE_SKGEN] = {0x100722, 0x3030008, 0x1020000, 0x1000000, 0xa0040, 0x10009, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_297
+const uint32_t layer_params_297[LP_SIZE_SKGEN] = {0x400140, 0x1010008, 0x1040000, 0x3f80, 0x50040, 0x1002d, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_299
+const uint32_t layer_params_299[LP_SIZE_SKGEN] = {0x640, 0x0, 0x48, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x3f80, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_301
+const uint32_t layer_params_301[LP_SIZE_SKGEN] = {0x280, 0x0, 0xb40000, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
+// array values based on rtp index for layer_302
+const uint32_t layer_params_302[LP_SIZE_SKGEN] = {0x640, 0x0, 0x48, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0, 0x3f80, 0x0, 0x0, 0x0, 0x0, 0x0, 0x0};
diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/mllib_config.h b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/mllib_config.h
new file mode 100644
index 0000000000000000000000000000000000000000..ecd2760e4e97babe31292e0407d91da5ec4b5ad3
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/mllib_config.h
@@ -0,0 +1,41 @@
+#pragma once
+
+#include "mllib_const.h"
+#include <adf.h>
+using namespace adf;
+
+#define BATCH_SIZE         1
+#define ACT_TYPE           LINEAR
+#define DTYPE_IFM          bfloat16
+#define DTYPE_OFM          bfloat16
+#define DTYPE_WTS          bfloat16
+#define DTYPE_AVG_OFM      bfloat16
+#define DTYPE_ELTWISE_IFM      bfloat16
+#define BPCTYPE_IFM        adf::bpc_sync_0d
+#define BPCTYPE_WTS        adf::bpc_sync_0d
+#define BPCTYPE_OFM        adf::bpc_async_0d
+
+typedef enum {
+  CONV2D = 0,
+  CONV2D_LAYER_1,
+  CONV2D_ADD2D,
+  CONV2D_ADD2D_GAP,
+  FC,
+  CONV2D_GAP
+} op_mode;
+
+typedef enum {
+  ELTBINARY_ADD1D = 0,
+  ELTBINARY_MUL1D = 1
+} eltbinary_op_mode;
+
+#define PAD_TOP_EN   0
+#define PAD_BOT_EN   0
+#define PAD_LEFT_EN  0
+#define PAD_RIGHT_EN 0
+#define USE_OPMODE_1 0
+
+#define LAST_COL 3
+#define BPCTYPE_IFM2       adf::bpc_async_0d
+#define AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16 1
+#define PAD3D_FOR_REDUCEOP 0
diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/multi_layer_overlay.h b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/multi_layer_overlay.h
new file mode 100644
index 0000000000000000000000000000000000000000..fc96a3421decb5f0764442aa829fb2b2b81fedc9
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/multi_layer_overlay.h
@@ -0,0 +1,14213 @@
+#pragma once
+
+#include "tiling.h"
+#include "superkernels.h"
+#include "L2/include/ml_adf/multi_layer_overlay_slice_hcwc8.h"
+#include "L2/include/ml_adf/multi_layer_overlay_buffer_pad.h"
+#include "L2/include/ml_adf/multi_layer_overlay_transpose4d.h"
+#include "L2/include/ml_adf/multi_layer_overlay_buffer_unpad.h"
+#include "L2/include/ml_adf/multi_layer_overlay_tile.h"
+#include "L2/include/ml_adf/multi_layer_overlay_resize.h"
+#include "L2/include/ml_adf/multi_layer_overlay_concatc8.h"
+
+#define NUM_LAYERS (237)
+static constexpr unsigned NUM_COL = 4;
+class single_layer_overlay : public graph{
+public:
+kernel compute_node[4][4];
+
+pktorderedmerge<4> ofm_merge[4];
+
+single_layer_overlay(
+bool is_ofm_int8,
+shared_buffer<bfloat16>& wts,
+int wtsShimDMACount,
+shared_buffer<bfloat16>& ofm,
+shared_buffer<int8_t>& int8_ofm,
+int predecessor_idx,
+unsigned super_kernel_mode,
+int kernel_type,
+const uint32_t layer_params[],
+uint32_t wtsL2_size,
+uint32_t kernel_iter,
+uint32_t ofm_repetition,
+ml_adf_overlay_4x4::tiling_params_t &params)
+{
+bool has_wts = (wtsL2_size > 0);
+int ofm_offset = predecessor_idx * NUM_COL;
+
+for (int col = 0; col < 4; col++) {
+  ofm_merge[col] = pktorderedmerge<4>::create();
+  for (int row = 0; row < 4 ; row++) {
+    switch(super_kernel_mode){
+      case 0: { 
+        compute_node[col][row] = kernel::create(conv2d_maxpool);
+        initial_value(compute_node[col][row].in[2]) = {layer_params[0], layer_params[1], layer_params[2], layer_params[3], layer_params[4], layer_params[5], layer_params[6], layer_params[7], layer_params[8], layer_params[9], layer_params[10], layer_params[11], layer_params[12], layer_params[13], layer_params[14], layer_params[15]};
+        break;
+      }
+      case 5: { 
+        switch (kernel_type) {
+          case 2: {
+            compute_node[col][row] = kernel::create(superkernel_add1d_attribute_broadcasting);
+            break;
+          }
+          case 3: {
+            compute_node[col][row] = kernel::create(superkernel_clip1d);
+            break;
+          }
+          case 1: {
+            compute_node[col][row] = kernel::create(superkernel_mul1d_attribute_broadcasting);
+            break;
+          }
+          case 4: {
+            compute_node[col][row] = kernel::create(superkernel_sigmoid1d);
+            break;
+          }
+          case 5: {
+            compute_node[col][row] = kernel::create(superkernel_tanh1d);
+            break;
+          }
+          default:;
+        }
+        initial_value(compute_node[col][row].in[1]) = {layer_params[0], layer_params[1], layer_params[2], layer_params[3], layer_params[4], layer_params[5], layer_params[6], layer_params[7], layer_params[8], layer_params[9], layer_params[10], layer_params[11], layer_params[12], layer_params[13], layer_params[14], layer_params[15]};
+        break;
+      }
+      case 7: { 
+        compute_node[col][row] = kernel::create(superkernel_avgpool);
+        initial_value(compute_node[col][row].in[1]) = {layer_params[0], layer_params[1], layer_params[2], layer_params[3], layer_params[4], layer_params[5], layer_params[6], layer_params[7], layer_params[8], layer_params[9], layer_params[10], layer_params[11], layer_params[12], layer_params[13], layer_params[14], layer_params[15]};
+        break;
+      }
+      case 8: { 
+        switch (kernel_type) {
+          case 1: {
+            compute_node[col][row] = kernel::create(superkernel_add1d);
+            break;
+          }
+          case 2: {
+            compute_node[col][row] = kernel::create(superkernel_mul1d);
+            break;
+          }
+          case 3: {
+            compute_node[col][row] = kernel::create(superkernel_sub1d);
+            break;
+          }
+          default:;
+        }
+        async_repetition(compute_node[col][row].in[2]) = ofm_repetition;
+        initial_value(compute_node[col][row].in[1]) = {layer_params[0], layer_params[1], layer_params[2], layer_params[3], layer_params[4], layer_params[5], layer_params[6], layer_params[7], layer_params[8], layer_params[9], layer_params[10], layer_params[11], layer_params[12], layer_params[13], layer_params[14], layer_params[15]};
+        break;
+      }
+      case 10: { 
+        compute_node[col][row] = kernel::create(superkernel_conv2d_dwc);
+        initial_value(compute_node[col][row].in[2]) = {layer_params[0], layer_params[1], layer_params[2], layer_params[3], layer_params[4], layer_params[5], layer_params[6], layer_params[7], layer_params[8], layer_params[9], layer_params[10], layer_params[11], layer_params[12], layer_params[13], layer_params[14], layer_params[15]};
+        break;
+      }
+      case 13: { 
+        switch (kernel_type) {
+          case 1: {
+            compute_node[col][row] = kernel::create(superkernel_reduce_mean_c8);
+            break;
+          }
+          default:;
+        }
+        initial_value(compute_node[col][row].in[1]) = {layer_params[0], layer_params[1], layer_params[2], layer_params[3], layer_params[4], layer_params[5], layer_params[6], layer_params[7], layer_params[8], layer_params[9], layer_params[10], layer_params[11], layer_params[12], layer_params[13], layer_params[14], layer_params[15]};
+        break;
+      }
+      case 14: { 
+        compute_node[col][row] = kernel::create(superkernel_conv_eltbinary);
+        async_repetition(compute_node[col][row].in[2]) = ofm_repetition;
+        initial_value(compute_node[col][row].in[3]) = {layer_params[0], layer_params[1], layer_params[2], layer_params[3], layer_params[4], layer_params[5], layer_params[6], layer_params[7], layer_params[8], layer_params[9], layer_params[10], layer_params[11], layer_params[12], layer_params[13], layer_params[14], layer_params[15], layer_params[16]};
+        break;
+      }
+    }
+    source(compute_node[col][row]) = "superkernels.cpp";
+    repetition_count(compute_node[col][row]) = kernel_iter;
+    runtime<ratio>(compute_node[col][row]) = 0.8;
+    location<kernel>(compute_node[col][row]) = tile( col+0,row);
+  }
+}
+ml_adf_overlay_4x4::set_stack_heap(compute_node, 0xb280, 0x940, 0x8c0);
+if(has_wts) {
+  ml_adf_overlay_4x4::connect_wts<bfloat16>(compute_node, wts, params, 0, 1);
+  location_constraint wts_dma_loc[2] = {  dma_channel(memory_tile, 3, 0, 0),
+   dma_channel(memory_tile, 3, 0, 1)};
+
+  for (unsigned i = 0; i < wtsShimDMACount; i++) {
+      location<dma>(wts.in[i]) = wts_dma_loc[i];
+  }
+}
+if(is_ofm_int8)
+  ml_adf_overlay_4x4::connect_ofm<int8_t>(compute_node, int8_ofm, ofm_offset, ofm_merge, params);
+else
+  ml_adf_overlay_4x4::connect_ofm<bfloat16>(compute_node, ofm, ofm_offset, ofm_merge, params);
+} //end of ctor
+
+};
+
+static std::vector<access_pattern> get_l1_write_pattern(bool has_l1_write_pattern, std::vector<access_pattern>& l1_write_pattern) {
+  if(has_l1_write_pattern)
+    return l1_write_pattern;
+  else
+    return {};
+}
+
+static std::vector<access_pattern> get_l1_wts_write_pattern(bool has_l1_wts_write_pattern, std::vector<access_pattern>& l1_wts_write_pattern) {
+  if(has_l1_wts_write_pattern)
+    return l1_wts_write_pattern;
+  else
+    return {};
+}
+
+static std::vector<access_pattern> get_l1_read_pattern(bool has_l1_read_pattern, std::vector<access_pattern>& l1_read_pattern) {
+  if(has_l1_read_pattern)
+    return l1_read_pattern;
+  else
+    return {};
+}
+
+class FlexMLGraph : public graph {
+public:
+
+//WTS Location & L2 WTS Buffer Definition
+shared_buffer<bfloat16> Layer_l2_wts_dummy;
+std::vector<location_constraint> wts_loc_8 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_8_l2_wts = shared_buffer<bfloat16>::create({2432}, 2, 4);
+external_buffer<bfloat16> Layer_8_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_8, 0, 2);
+std::vector<location_constraint> wts_loc_13 = {address(3, 0, 523264)};
+shared_buffer<bfloat16> Layer_13_l2_wts = shared_buffer<bfloat16>::create({512}, 2, 4);
+external_buffer<bfloat16> Layer_13_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_13, 0, 2);
+std::vector<location_constraint> wts_loc_14 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_14_l2_wts = shared_buffer<bfloat16>::create({2176}, 2, 4);
+external_buffer<bfloat16> Layer_14_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_14, 0, 2);
+std::vector<location_constraint> wts_loc_15 = {address(3, 0, 515584)};
+shared_buffer<bfloat16> Layer_15_l2_wts = shared_buffer<bfloat16>::create({4352}, 2, 4);
+external_buffer<bfloat16> Layer_15_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_15, 0, 2);
+std::vector<location_constraint> wts_loc_16 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_16_l2_wts = shared_buffer<bfloat16>::create({1024}, 2, 4);
+external_buffer<bfloat16> Layer_16_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_16, 0, 2);
+std::vector<location_constraint> wts_loc_18 = {address(3, 0, 515584)};
+shared_buffer<bfloat16> Layer_18_l2_wts = shared_buffer<bfloat16>::create({4352}, 2, 4);
+external_buffer<bfloat16> Layer_18_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_18, 0, 2);
+std::vector<location_constraint> wts_loc_19 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_19_l2_wts = shared_buffer<bfloat16>::create({6528}, 2, 4);
+external_buffer<bfloat16> Layer_19_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_19, 0, 2);
+std::vector<location_constraint> wts_loc_20 = {address(3, 0, 521216)};
+shared_buffer<bfloat16> Layer_20_l2_wts = shared_buffer<bfloat16>::create({1536}, 2, 4);
+external_buffer<bfloat16> Layer_20_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_20, 0, 2);
+std::vector<location_constraint> wts_loc_22 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_22_l2_wts = shared_buffer<bfloat16>::create({4864}, 2, 4);
+external_buffer<bfloat16> Layer_22_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_22, 0, 2);
+std::vector<location_constraint> wts_loc_23 = {address(3, 0, 511232)};
+shared_buffer<bfloat16> Layer_23_l2_wts = shared_buffer<bfloat16>::create({6528}, 2, 4);
+external_buffer<bfloat16> Layer_23_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_23, 0, 2);
+std::vector<location_constraint> wts_loc_24 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_24_l2_wts = shared_buffer<bfloat16>::create({4224}, 2, 4);
+external_buffer<bfloat16> Layer_24_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_24, 0, 2);
+std::vector<location_constraint> wts_loc_27 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_27_l2_wts = shared_buffer<bfloat16>::create({4864}, 2, 4);
+external_buffer<bfloat16> Layer_27_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_27, 0, 2);
+std::vector<location_constraint> wts_loc_28 = {address(3, 0, 506880)};
+shared_buffer<bfloat16> Layer_28_l2_wts = shared_buffer<bfloat16>::create({8704}, 2, 4);
+external_buffer<bfloat16> Layer_28_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_28, 0, 2);
+std::vector<location_constraint> wts_loc_34 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_34_l2_wts = shared_buffer<bfloat16>::create({4864}, 2, 4);
+external_buffer<bfloat16> Layer_34_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_34, 0, 2);
+std::vector<location_constraint> wts_loc_35 = {address(3, 0, 506880)};
+shared_buffer<bfloat16> Layer_35_l2_wts = shared_buffer<bfloat16>::create({8704}, 2, 4);
+external_buffer<bfloat16> Layer_35_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_35, 0, 2);
+std::vector<location_constraint> wts_loc_36 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_36_l2_wts = shared_buffer<bfloat16>::create({5632}, 2, 4);
+external_buffer<bfloat16> Layer_36_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_36, 0, 2);
+std::vector<location_constraint> wts_loc_39 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_39_l2_wts = shared_buffer<bfloat16>::create({7936}, 2, 4);
+external_buffer<bfloat16> Layer_39_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_39, 0, 2);
+std::vector<location_constraint> wts_loc_40 = {address(3, 0, 506880)};
+shared_buffer<bfloat16> Layer_40_l2_wts = shared_buffer<bfloat16>::create({8704}, 2, 4);
+external_buffer<bfloat16> Layer_40_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_40, 0, 2);
+std::vector<location_constraint> wts_loc_46 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_46_l2_wts = shared_buffer<bfloat16>::create({8704}, 2, 4);
+external_buffer<bfloat16> Layer_46_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_46, 0, 2);
+std::vector<location_constraint> wts_loc_47 = {address(3, 0, 506880)};
+shared_buffer<bfloat16> Layer_47_l2_wts = shared_buffer<bfloat16>::create({8704}, 2, 4);
+external_buffer<bfloat16> Layer_47_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_47, 0, 2);
+std::vector<location_constraint> wts_loc_48 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_48_l2_wts = shared_buffer<bfloat16>::create({5632}, 2, 4);
+external_buffer<bfloat16> Layer_48_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_48, 0, 2);
+std::vector<location_constraint> wts_loc_51 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_51_l2_wts = shared_buffer<bfloat16>::create({7936}, 2, 4);
+external_buffer<bfloat16> Layer_51_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_51, 0, 2);
+std::vector<location_constraint> wts_loc_52 = {address(3, 0, 506880)};
+shared_buffer<bfloat16> Layer_52_l2_wts = shared_buffer<bfloat16>::create({8704}, 2, 4);
+external_buffer<bfloat16> Layer_52_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_52, 0, 2);
+std::vector<location_constraint> wts_loc_58 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_58_l2_wts = shared_buffer<bfloat16>::create({8704}, 2, 4);
+external_buffer<bfloat16> Layer_58_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_58, 0, 2);
+std::vector<location_constraint> wts_loc_59 = {address(3, 0, 489472)};
+shared_buffer<bfloat16> Layer_59_l2_wts = shared_buffer<bfloat16>::create({17408}, 2, 4);
+external_buffer<bfloat16> Layer_59_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_59, 0, 2);
+std::vector<location_constraint> wts_loc_65 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_65_l2_wts = shared_buffer<bfloat16>::create({4096}, 2, 4);
+external_buffer<bfloat16> Layer_65_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_65, 0, 2);
+std::vector<location_constraint> wts_loc_70 = {address(3, 0, 475904)};
+shared_buffer<bfloat16> Layer_70_l2_wts = shared_buffer<bfloat16>::create({24192}, 2, 4);
+external_buffer<bfloat16> Layer_70_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_70, 0, 2);
+std::vector<location_constraint> wts_loc_71 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_71_l2_wts = shared_buffer<bfloat16>::create({21504}, 2, 4);
+external_buffer<bfloat16> Layer_71_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_71, 0, 2);
+std::vector<location_constraint> wts_loc_76 = {address(3, 0, 517120)};
+shared_buffer<bfloat16> Layer_76_l2_wts = shared_buffer<bfloat16>::create({3584}, 2, 4);
+external_buffer<bfloat16> Layer_76_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_76, 0, 2);
+std::vector<location_constraint> wts_loc_81 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_81_l2_wts = shared_buffer<bfloat16>::create({20736}, 2, 4);
+external_buffer<bfloat16> Layer_81_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_81, 0, 2);
+std::vector<location_constraint> wts_loc_82 = {address(3, 0, 492032)};
+shared_buffer<bfloat16> Layer_82_l2_wts = shared_buffer<bfloat16>::create({16128}, 2, 4);
+external_buffer<bfloat16> Layer_82_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_82, 0, 2);
+std::vector<location_constraint> wts_loc_87 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_87_l2_wts = shared_buffer<bfloat16>::create({3072}, 2, 4);
+external_buffer<bfloat16> Layer_87_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_87, 0, 2);
+std::vector<location_constraint> wts_loc_92 = {address(3, 0, 485888)};
+shared_buffer<bfloat16> Layer_92_l2_wts = shared_buffer<bfloat16>::create({19200}, 2, 4);
+external_buffer<bfloat16> Layer_92_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_92, 0, 2);
+std::vector<location_constraint> wts_loc_93 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_93_l2_wts = shared_buffer<bfloat16>::create({16128}, 2, 4);
+external_buffer<bfloat16> Layer_93_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_93, 0, 2);
+std::vector<location_constraint> wts_loc_98 = {address(3, 0, 518144)};
+shared_buffer<bfloat16> Layer_98_l2_wts = shared_buffer<bfloat16>::create({3072}, 2, 4);
+external_buffer<bfloat16> Layer_98_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_98, 0, 2);
+std::vector<location_constraint> wts_loc_103 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_103_l2_wts = shared_buffer<bfloat16>::create({19200}, 2, 4);
+external_buffer<bfloat16> Layer_103_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_103, 0, 2);
+std::vector<location_constraint> wts_loc_104 = {address(3, 0, 443648)};
+shared_buffer<bfloat16> Layer_104_l2_wts = shared_buffer<bfloat16>::create({40320}, 2, 4);
+external_buffer<bfloat16> Layer_104_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_104, 0, 2);
+std::vector<location_constraint> wts_loc_109 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_109_l2_wts = shared_buffer<bfloat16>::create({7680}, 2, 4);
+external_buffer<bfloat16> Layer_109_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_109, 0, 2);
+std::vector<location_constraint> wts_loc_116 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_116_l2_wts = shared_buffer<bfloat16>::create({63488}, 2, 4);
+external_buffer<bfloat16> Layer_116_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_116, 0, 2);
+std::vector<location_constraint> wts_loc_117 = {address(3, 0, 397312)};
+shared_buffer<bfloat16> Layer_117_l2_wts = shared_buffer<bfloat16>::create({63488}, 2, 4);
+external_buffer<bfloat16> Layer_117_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_117, 0, 2);
+std::vector<location_constraint> wts_loc_123 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_123_l2_wts = shared_buffer<bfloat16>::create({64000}, 2, 4);
+external_buffer<bfloat16> Layer_123_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_123, 0, 2);
+std::vector<location_constraint> wts_loc_124 = {address(3, 0, 341504)};
+shared_buffer<bfloat16> Layer_124_l2_wts = shared_buffer<bfloat16>::create({91392}, 2, 4);
+external_buffer<bfloat16> Layer_124_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_124, 0, 2);
+std::vector<location_constraint> wts_loc_129 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_129_l2_wts = shared_buffer<bfloat16>::create({10752}, 2, 4);
+external_buffer<bfloat16> Layer_129_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_129, 0, 2);
+std::vector<location_constraint> wts_loc_136 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_136_l2_wts = shared_buffer<bfloat16>::create({134400}, 2, 4);
+external_buffer<bfloat16> Layer_136_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_136, 0, 2);
+std::vector<location_constraint> wts_loc_137 = {address(3, 0, 282112)};
+shared_buffer<bfloat16> Layer_137_l2_wts = shared_buffer<bfloat16>::create({121088}, 2, 4);
+external_buffer<bfloat16> Layer_137_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_137, 0, 2);
+std::vector<location_constraint> wts_loc_143 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_143_l2_wts = shared_buffer<bfloat16>::create({89600}, 2, 4);
+external_buffer<bfloat16> Layer_143_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_143, 0, 2);
+std::vector<location_constraint> wts_loc_144 = {address(3, 0, 341504)};
+shared_buffer<bfloat16> Layer_144_l2_wts = shared_buffer<bfloat16>::create({91392}, 2, 4);
+external_buffer<bfloat16> Layer_144_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_144, 0, 2);
+std::vector<location_constraint> wts_loc_149 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_149_l2_wts = shared_buffer<bfloat16>::create({75264}, 2, 4);
+external_buffer<bfloat16> Layer_149_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_149, 0, 2);
+std::vector<location_constraint> wts_loc_156 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_156_l2_wts = shared_buffer<bfloat16>::create({134400}, 2, 4);
+external_buffer<bfloat16> Layer_156_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_156, 0, 2);
+std::vector<location_constraint> wts_loc_157 = {address(3, 0, 282112)};
+shared_buffer<bfloat16> Layer_157_l2_wts = shared_buffer<bfloat16>::create({121088}, 2, 4);
+external_buffer<bfloat16> Layer_157_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_157, 0, 2);
+std::vector<location_constraint> wts_loc_163 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_163_l2_wts = shared_buffer<bfloat16>::create({120960}, 2, 4);
+external_buffer<bfloat16> Layer_163_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_163, 0, 2);
+std::vector<location_constraint> wts_loc_164 = {address(3, 0, 201728)};
+shared_buffer<bfloat16> Layer_164_l2_wts = shared_buffer<bfloat16>::create({161280}, 2, 4);
+external_buffer<bfloat16> Layer_164_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_164, 0, 2);
+std::vector<location_constraint> wts_loc_169 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_169_l2_wts = shared_buffer<bfloat16>::create({107520}, 2, 4);
+external_buffer<bfloat16> Layer_169_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_169, 0, 2);
+std::vector<location_constraint> wts_loc_176 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_176_l2_wts = shared_buffer<bfloat16>::create({250880}, 2, 4);
+external_buffer<bfloat16> Layer_176_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_176, 0, 2);
+std::vector<location_constraint> wts_loc_177 = {address(3, 0, 40448)};
+shared_buffer<bfloat16> Layer_177_l2_wts = shared_buffer<bfloat16>::create({241920}, 2, 4);
+external_buffer<bfloat16> Layer_177_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_177, 0, 2);
+std::vector<location_constraint> wts_loc_183 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_183_l2_wts = shared_buffer<bfloat16>::create({200448}, 2, 4);
+external_buffer<bfloat16> Layer_183_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_183, 0, 2);
+std::vector<location_constraint> wts_loc_184 = {address(3, 0, 201728)};
+shared_buffer<bfloat16> Layer_184_l2_wts = shared_buffer<bfloat16>::create({161280}, 2, 4);
+external_buffer<bfloat16> Layer_184_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_184, 0, 2);
+std::vector<location_constraint> wts_loc_189 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_189_l2_wts = shared_buffer<bfloat16>::create({107520}, 2, 4);
+external_buffer<bfloat16> Layer_189_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_189, 0, 2);
+std::vector<location_constraint> wts_loc_196 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_196_l2_wts = shared_buffer<bfloat16>::create({250880}, 2, 4);
+external_buffer<bfloat16> Layer_196_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_196, 0, 2);
+std::vector<location_constraint> wts_loc_197 = {address(3, 0, 40448)};
+shared_buffer<bfloat16> Layer_197_l2_wts = shared_buffer<bfloat16>::create({241920}, 2, 4);
+external_buffer<bfloat16> Layer_197_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_197, 0, 2);
+std::vector<location_constraint> wts_loc_203 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_203_l2_wts = shared_buffer<bfloat16>::create({200448}, 2, 4);
+external_buffer<bfloat16> Layer_203_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_203, 0, 2);
+std::vector<location_constraint> wts_loc_204 = {address(3, 0, 201728)};
+shared_buffer<bfloat16> Layer_204_l2_wts = shared_buffer<bfloat16>::create({161280}, 2, 4);
+external_buffer<bfloat16> Layer_204_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_204, 0, 2);
+std::vector<location_constraint> wts_loc_211 = {address(3, 0, 273408)};
+shared_buffer<bfloat16> Layer_211_l2_wts = shared_buffer<bfloat16>::create({125440}, 2, 4);
+external_buffer<bfloat16> Layer_211_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_211, 0, 2);
+std::vector<location_constraint> wts_loc_214 = {address(3, 0, 268288)};
+shared_buffer<bfloat16> Layer_214_l2_wts = shared_buffer<bfloat16>::create({128000}, 2, 4);
+external_buffer<bfloat16> Layer_214_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_214, 0, 2);
+std::vector<location_constraint> wts_loc_218 = {address(2, 0, 489472)};
+shared_buffer<bfloat16> Layer_218_l2_wts = shared_buffer<bfloat16>::create({151552}, 2, 4);
+external_buffer<bfloat16> Layer_218_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_218, 0, 2);
+std::vector<location_constraint> wts_loc_226 = {address(3, 0, 372736)};
+shared_buffer<bfloat16> Layer_226_l2_wts = shared_buffer<bfloat16>::create({75776}, 2, 4);
+external_buffer<bfloat16> Layer_226_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_226, 0, 2);
+std::vector<location_constraint> wts_loc_237 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_237_l2_wts = shared_buffer<bfloat16>::create({208384}, 2, 4);
+external_buffer<bfloat16> Layer_237_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_237, 0, 2);
+std::vector<location_constraint> wts_loc_241 = {address(3, 0, 334848)};
+shared_buffer<bfloat16> Layer_241_l2_wts = shared_buffer<bfloat16>::create({94720}, 2, 4);
+external_buffer<bfloat16> Layer_241_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_241, 0, 2);
+std::vector<location_constraint> wts_loc_249 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_249_l2_wts = shared_buffer<bfloat16>::create({47360}, 2, 4);
+external_buffer<bfloat16> Layer_249_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_249, 0, 2);
+std::vector<location_constraint> wts_loc_257 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_257_l2_wts = shared_buffer<bfloat16>::create({66304}, 2, 4);
+external_buffer<bfloat16> Layer_257_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_257, 0, 2);
+std::vector<location_constraint> wts_loc_261 = {address(3, 0, 467456)};
+shared_buffer<bfloat16> Layer_261_l2_wts = shared_buffer<bfloat16>::create({28416}, 2, 4);
+external_buffer<bfloat16> Layer_261_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_261, 0, 2);
+std::vector<location_constraint> wts_loc_269 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_269_l2_wts = shared_buffer<bfloat16>::create({12160}, 2, 4);
+external_buffer<bfloat16> Layer_269_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_269, 0, 2);
+std::vector<location_constraint> wts_loc_276 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_276_l2_wts = shared_buffer<bfloat16>::create({18944}, 2, 4);
+external_buffer<bfloat16> Layer_276_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_276, 0, 2);
+std::vector<location_constraint> wts_loc_280 = {address(3, 0, 505344)};
+shared_buffer<bfloat16> Layer_280_l2_wts = shared_buffer<bfloat16>::create({9472}, 2, 4);
+external_buffer<bfloat16> Layer_280_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_280, 0, 2);
+std::vector<location_constraint> wts_loc_288 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_288_l2_wts = shared_buffer<bfloat16>::create({9472}, 2, 4);
+external_buffer<bfloat16> Layer_288_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_288, 0, 2);
+std::vector<location_constraint> wts_loc_295 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_295_l2_wts = shared_buffer<bfloat16>::create({12160}, 2, 4);
+external_buffer<bfloat16> Layer_295_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_295, 0, 2);
+std::vector<location_constraint> wts_loc_296 = {address(3, 0, 514816)};
+shared_buffer<bfloat16> Layer_296_l2_wts = shared_buffer<bfloat16>::create({4736}, 2, 4);
+external_buffer<bfloat16> Layer_296_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_296, 0, 2);
+std::vector<location_constraint> wts_loc_297 = {address(3, 0, 0)};
+shared_buffer<bfloat16> Layer_297_l2_wts = shared_buffer<bfloat16>::create({2176}, 2, 4);
+external_buffer<bfloat16> Layer_297_wts_ddr = external_buffer<bfloat16>::create(wts_ddr_dim_297, 0, 2);
+
+//L2 Buffer definition
+shared_buffer<bfloat16> L2_IFM_Buffer_for_input0_0_port0 = shared_buffer<bfloat16>::create({8,4,23,320}, 2, 4);
+shared_buffer<bfloat16> l2_1 = shared_buffer<bfloat16>::create({8,4,24,320}, 4, 2);
+shared_buffer<bfloat16> L2_CONST_IFM_Buffer_for_input5_0_port1 = shared_buffer<bfloat16>::create({8,320,1,20}, 2, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_5_for_layer_6_port0 = shared_buffer<bfloat16>::create({8,320,1,20}, 2, 4);
+shared_buffer<bfloat16> l2_6 = shared_buffer<bfloat16>::create({8,320,4,20}, 4, 2);
+shared_buffer<bfloat16> L2_CONST_IFM_Buffer_for_input4_0_port1 = shared_buffer<bfloat16>::create({8,320,1,20}, 2, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_6_for_layer_7_port0 = shared_buffer<bfloat16>::create({8,320,1,20}, 2, 4);
+shared_buffer<bfloat16> l2_7 = shared_buffer<bfloat16>::create({8,320,4,20}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_7_for_layer_8_port0 = shared_buffer<bfloat16>::create({8,320,1,61}, 2, 4);
+shared_buffer<bfloat16> l2_8 = shared_buffer<bfloat16>::create({8,160,4,32}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_8_for_layer_9_port0 = shared_buffer<bfloat16>::create({8,160,2,90}, 2, 4);
+shared_buffer<bfloat16> l2_9 = shared_buffer<bfloat16>::create({8,160,4,92}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_9_for_layer_10_port0 = shared_buffer<bfloat16>::create({8,160,2,45}, 2, 4);
+shared_buffer<bfloat16> l2_10 = shared_buffer<bfloat16>::create({8,160,4,48}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_10_for_layer_11_port0 = shared_buffer<bfloat16>::create({8,160,2,90}, 2, 4);
+shared_buffer<bfloat16> l2_11 = shared_buffer<bfloat16>::create({8,160,4,92}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_8_for_layer_12_port0 = shared_buffer<bfloat16>::create({8,160,2,30}, 2, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_11_for_layer_12_port1 = shared_buffer<bfloat16>::create({8,160,2,30}, 2, 4);
+shared_buffer<bfloat16> l2_12 = shared_buffer<bfloat16>::create({8,160,4,32}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_12_for_layer_13_port0 = shared_buffer<bfloat16>::create({8,160,2,90}, 2, 4);
+shared_buffer<bfloat16> l2_13 = shared_buffer<bfloat16>::create({8,160,4,96}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_12_for_layer_14_port1 = shared_buffer<bfloat16>::create({8,160,4,48}, 2, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_13_for_layer_14_port0 = shared_buffer<bfloat16>::create({8,160,2,45}, 2, 4);
+shared_buffer<bfloat16> l2_14 = shared_buffer<bfloat16>::create({8,160,4,48}, 4, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_14_for_layer_15_port0 = shared_buffer<bfloat16>::create({8,160,2,18}, 2, 4);
+shared_buffer<bfloat16> l2_15 = shared_buffer<bfloat16>::create({8,160,8,18}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_15_for_layer_16_port0 = shared_buffer<bfloat16>::create({8,160,8,17}, 2, 4);
+shared_buffer<bfloat16> l2_16 = shared_buffer<bfloat16>::create({8,84,8,8}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_17_for_layer_18_port0 = shared_buffer<bfloat16>::create({8,80,8,45}, 2, 4);
+shared_buffer<bfloat16> l2_18 = shared_buffer<bfloat16>::create({8,80,8,48}, 4, 6);
+shared_buffer<bfloat16> l2_19 = shared_buffer<bfloat16>::create({8,96,12,48}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_19_for_layer_20_port0 = shared_buffer<bfloat16>::create({8,80,9,25}, 2, 4);
+shared_buffer<bfloat16> l2_20 = shared_buffer<bfloat16>::create({8,80,12,24}, 4, 2);
+shared_buffer<bfloat16> L2_OFM_Buffer_layer_TGSpilling_1818 = shared_buffer<bfloat16>::create({8,80,8,48}, 2, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_21_for_layer_22_port0 = shared_buffer<bfloat16>::create({8,80,9,45}, 2, 4);
+shared_buffer<bfloat16> l2_22 = shared_buffer<bfloat16>::create({8,80,8,48}, 4, 6);
+shared_buffer<bfloat16> l2_23 = shared_buffer<bfloat16>::create({8,96,12,48}, 4, 4);
+shared_buffer<bfloat16> l2_24 = shared_buffer<bfloat16>::create({8,40,12,24}, 4, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_25_for_layer_26_port0 = shared_buffer<bfloat16>::create({8,920,9,1}, 2, 4);
+shared_buffer<bfloat16> l2_26 = shared_buffer<bfloat16>::create({8,1,16,4}, 4, 4);
+shared_buffer<bfloat16> l2_27 = shared_buffer<bfloat16>::create({8,64,8,1}, 4, 4);
+shared_buffer<bfloat16> l2_28 = shared_buffer<bfloat16>::create({8,32,16,1}, 4, 4);
+shared_buffer<bfloat16> l2_29 = shared_buffer<bfloat16>::create({8,1,12,64}, 4, 4);
+shared_buffer<bfloat16> l2_30 = shared_buffer<bfloat16>::create({8,1,16,32}, 4, 4);
+shared_buffer<bfloat16> l2_31 = shared_buffer<bfloat16>::create({8,1,16,64}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_32_for_layer_33_port0 = shared_buffer<bfloat16>::create({8,40,9,23}, 2, 4);
+shared_buffer<bfloat16> L2_OFM_Buffer_layer_TGSpilling_2424 = shared_buffer<bfloat16>::create({8,40,12,24}, 2, 4);
+shared_buffer<bfloat16> l2_33 = shared_buffer<bfloat16>::create({8,40,12,24}, 4, 4);
+shared_buffer<bfloat16> l2_34 = shared_buffer<bfloat16>::create({8,40,8,24}, 4, 6);
+shared_buffer<bfloat16> l2_35 = shared_buffer<bfloat16>::create({8,64,16,24}, 4, 4);
+shared_buffer<bfloat16> l2_36 = shared_buffer<bfloat16>::create({8,40,16,24}, 4, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_37_for_layer_38_port0 = shared_buffer<bfloat16>::create({8,920,15,1}, 2, 4);
+shared_buffer<bfloat16> l2_38 = shared_buffer<bfloat16>::create({8,1,16,4}, 4, 4);
+shared_buffer<bfloat16> l2_39 = shared_buffer<bfloat16>::create({8,64,8,1}, 4, 4);
+shared_buffer<bfloat16> l2_40 = shared_buffer<bfloat16>::create({8,32,16,1}, 4, 4);
+shared_buffer<bfloat16> l2_41 = shared_buffer<bfloat16>::create({8,1,16,48}, 4, 4);
+shared_buffer<bfloat16> l2_42 = shared_buffer<bfloat16>::create({8,1,16,32}, 4, 4);
+shared_buffer<bfloat16> l2_43 = shared_buffer<bfloat16>::create({8,1,16,64}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_44_for_layer_45_port0 = shared_buffer<bfloat16>::create({8,40,15,23}, 2, 4);
+shared_buffer<bfloat16> L2_OFM_Buffer_layer_TGSpilling_3636 = shared_buffer<bfloat16>::create({8,40,16,24}, 2, 4);
+shared_buffer<bfloat16> l2_45 = shared_buffer<bfloat16>::create({8,40,16,24}, 4, 4);
+shared_buffer<bfloat16> L2_OFM_Buffer_layer_TGSpilling_3434 = shared_buffer<bfloat16>::create({8,40,8,24}, 2, 4);
+shared_buffer<bfloat16> l2_46 = shared_buffer<bfloat16>::create({8,40,8,24}, 4, 6);
+shared_buffer<bfloat16> l2_47 = shared_buffer<bfloat16>::create({8,64,16,24}, 4, 4);
+shared_buffer<bfloat16> l2_48 = shared_buffer<bfloat16>::create({8,40,16,24}, 4, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_49_for_layer_50_port0 = shared_buffer<bfloat16>::create({8,920,15,1}, 2, 4);
+shared_buffer<bfloat16> l2_50 = shared_buffer<bfloat16>::create({8,1,16,4}, 4, 4);
+shared_buffer<bfloat16> l2_51 = shared_buffer<bfloat16>::create({8,64,8,1}, 4, 4);
+shared_buffer<bfloat16> l2_52 = shared_buffer<bfloat16>::create({8,32,16,1}, 4, 4);
+shared_buffer<bfloat16> l2_53 = shared_buffer<bfloat16>::create({8,1,16,48}, 4, 4);
+shared_buffer<bfloat16> l2_54 = shared_buffer<bfloat16>::create({8,1,16,32}, 4, 4);
+shared_buffer<bfloat16> l2_55 = shared_buffer<bfloat16>::create({8,1,16,64}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_56_for_layer_57_port0 = shared_buffer<bfloat16>::create({8,40,15,23}, 2, 4);
+shared_buffer<bfloat16> L2_OFM_Buffer_layer_TGSpilling_4848 = shared_buffer<bfloat16>::create({8,40,16,24}, 2, 4);
+shared_buffer<bfloat16> l2_57 = shared_buffer<bfloat16>::create({8,40,16,24}, 4, 4);
+shared_buffer<bfloat16> L2_OFM_Buffer_layer_TGSpilling_4646 = shared_buffer<bfloat16>::create({8,40,8,24}, 2, 4);
+shared_buffer<bfloat16> l2_58 = shared_buffer<bfloat16>::create({8,40,8,24}, 4, 6);
+shared_buffer<bfloat16> l2_59 = shared_buffer<bfloat16>::create({8,64,32,24}, 4, 6);
+shared_buffer<bfloat16> l2_60 = shared_buffer<bfloat16>::create({8,40,32,24}, 4, 4);
+shared_buffer<bfloat16> l2_61 = shared_buffer<bfloat16>::create({8,40,32,24}, 4, 4);
+shared_buffer<bfloat16> l2_62 = shared_buffer<bfloat16>::create({8,40,32,24}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_59_for_layer_63_port0 = shared_buffer<bfloat16>::create({8,40,30,12}, 2, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_62_for_layer_63_port1 = shared_buffer<bfloat16>::create({8,40,30,12}, 2, 4);
+shared_buffer<bfloat16> l2_63 = shared_buffer<bfloat16>::create({8,40,32,12}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_64_for_layer_65_port0 = shared_buffer<bfloat16>::create({8,40,30,23}, 2, 4);
+shared_buffer<bfloat16> l2_65 = shared_buffer<bfloat16>::create({8,20,32,16}, 4, 8);
+shared_buffer<bfloat16> l2_66 = shared_buffer<bfloat16>::create({8,20,32,12}, 4, 4);
+shared_buffer<bfloat16> l2_67 = shared_buffer<bfloat16>::create({8,20,32,12}, 4, 4);
+shared_buffer<bfloat16> l2_68 = shared_buffer<bfloat16>::create({8,20,32,12}, 4, 4);
+shared_buffer<bfloat16> l2_69 = shared_buffer<bfloat16>::create({8,20,32,12}, 4, 4);
+shared_buffer<bfloat16> l2_70 = shared_buffer<bfloat16>::create({8,32,12,12}, 4, 8);
+shared_buffer<bfloat16> l2_71 = shared_buffer<bfloat16>::create({8,32,32,12}, 4, 8);
+shared_buffer<bfloat16> l2_72 = shared_buffer<bfloat16>::create({8,20,32,12}, 4, 4);
+shared_buffer<bfloat16> l2_73 = shared_buffer<bfloat16>::create({8,20,32,12}, 4, 4);
+shared_buffer<bfloat16> l2_74 = shared_buffer<bfloat16>::create({8,20,32,12}, 4, 4);
+shared_buffer<bfloat16> l2_75 = shared_buffer<bfloat16>::create({8,20,32,12}, 4, 4);
+shared_buffer<bfloat16> l2_76 = shared_buffer<bfloat16>::create({8,24,28,16}, 4, 8);
+shared_buffer<bfloat16> l2_77 = shared_buffer<bfloat16>::create({8,20,32,12}, 4, 4);
+shared_buffer<bfloat16> l2_78 = shared_buffer<bfloat16>::create({8,20,32,12}, 4, 4);
+shared_buffer<bfloat16> l2_79 = shared_buffer<bfloat16>::create({8,20,32,12}, 4, 4);
+shared_buffer<bfloat16> l2_80 = shared_buffer<bfloat16>::create({8,20,32,12}, 4, 4);
+shared_buffer<bfloat16> l2_81 = shared_buffer<bfloat16>::create({8,32,12,12}, 4, 8);
+shared_buffer<bfloat16> l2_82 = shared_buffer<bfloat16>::create({8,24,24,12}, 4, 8);
+shared_buffer<bfloat16> l2_83 = shared_buffer<bfloat16>::create({8,20,24,12}, 4, 4);
+shared_buffer<bfloat16> l2_84 = shared_buffer<bfloat16>::create({8,20,24,12}, 4, 4);
+shared_buffer<bfloat16> l2_85 = shared_buffer<bfloat16>::create({8,20,24,12}, 4, 4);
+shared_buffer<bfloat16> l2_86 = shared_buffer<bfloat16>::create({8,20,24,12}, 4, 4);
+shared_buffer<bfloat16> l2_87 = shared_buffer<bfloat16>::create({8,24,24,16}, 4, 8);
+shared_buffer<bfloat16> l2_88 = shared_buffer<bfloat16>::create({8,20,24,12}, 4, 4);
+shared_buffer<bfloat16> l2_89 = shared_buffer<bfloat16>::create({8,20,24,12}, 4, 4);
+shared_buffer<bfloat16> l2_90 = shared_buffer<bfloat16>::create({8,20,24,12}, 4, 4);
+shared_buffer<bfloat16> l2_91 = shared_buffer<bfloat16>::create({8,20,24,12}, 4, 4);
+shared_buffer<bfloat16> l2_92 = shared_buffer<bfloat16>::create({8,32,12,12}, 4, 8);
+shared_buffer<bfloat16> l2_93 = shared_buffer<bfloat16>::create({8,24,24,12}, 4, 8);
+shared_buffer<bfloat16> l2_94 = shared_buffer<bfloat16>::create({8,20,24,12}, 4, 4);
+shared_buffer<bfloat16> l2_95 = shared_buffer<bfloat16>::create({8,20,24,12}, 4, 4);
+shared_buffer<bfloat16> l2_96 = shared_buffer<bfloat16>::create({8,20,24,12}, 4, 4);
+shared_buffer<bfloat16> l2_97 = shared_buffer<bfloat16>::create({8,20,24,12}, 4, 4);
+shared_buffer<bfloat16> l2_98 = shared_buffer<bfloat16>::create({8,24,24,16}, 4, 8);
+shared_buffer<bfloat16> l2_99 = shared_buffer<bfloat16>::create({8,20,24,12}, 4, 4);
+shared_buffer<bfloat16> l2_100 = shared_buffer<bfloat16>::create({8,20,24,12}, 4, 4);
+shared_buffer<bfloat16> l2_101 = shared_buffer<bfloat16>::create({8,20,24,12}, 4, 4);
+shared_buffer<bfloat16> l2_102 = shared_buffer<bfloat16>::create({8,20,24,12}, 4, 4);
+shared_buffer<bfloat16> l2_103 = shared_buffer<bfloat16>::create({8,32,12,12}, 4, 4);
+shared_buffer<bfloat16> l2_104 = shared_buffer<bfloat16>::create({8,32,60,12}, 4, 8);
+shared_buffer<bfloat16> l2_105 = shared_buffer<bfloat16>::create({8,20,64,12}, 4, 4);
+shared_buffer<bfloat16> l2_106 = shared_buffer<bfloat16>::create({8,20,64,12}, 4, 4);
+shared_buffer<bfloat16> l2_107 = shared_buffer<bfloat16>::create({8,20,64,12}, 4, 4);
+shared_buffer<bfloat16> l2_108 = shared_buffer<bfloat16>::create({8,20,64,12}, 4, 4);
+shared_buffer<bfloat16> l2_109 = shared_buffer<bfloat16>::create({8,24,60,16}, 4, 8);
+shared_buffer<bfloat16> l2_110 = shared_buffer<bfloat16>::create({8,20,64,12}, 4, 4);
+shared_buffer<bfloat16> l2_111 = shared_buffer<bfloat16>::create({8,20,64,12}, 4, 4);
+shared_buffer<bfloat16> l2_112 = shared_buffer<bfloat16>::create({8,20,64,12}, 4, 4);
+shared_buffer<bfloat16> l2_113 = shared_buffer<bfloat16>::create({8,20,64,12}, 4, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_114_for_layer_115_port0 = shared_buffer<bfloat16>::create({8,240,60,1}, 2, 4);
+shared_buffer<bfloat16> l2_115 = shared_buffer<bfloat16>::create({8,1,60,4}, 4, 4);
+shared_buffer<bfloat16> l2_116 = shared_buffer<bfloat16>::create({8,32,16,1}, 4, 4);
+shared_buffer<bfloat16> l2_117 = shared_buffer<bfloat16>::create({8,32,64,1}, 4, 4);
+shared_buffer<bfloat16> l2_118 = shared_buffer<bfloat16>::create({8,1,64,12}, 4, 4);
+shared_buffer<bfloat16> l2_119 = shared_buffer<bfloat16>::create({8,1,64,8}, 4, 4);
+shared_buffer<bfloat16> l2_120 = shared_buffer<bfloat16>::create({8,1,64,16}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_121_for_layer_122_port0 = shared_buffer<bfloat16>::create({8,20,60,12}, 2, 4);
+shared_buffer<bfloat16> L2_OFM_Buffer_layer_TGSpilling_113113 = shared_buffer<bfloat16>::create({8,20,64,12}, 2, 4);
+shared_buffer<bfloat16> l2_122 = shared_buffer<bfloat16>::create({8,20,64,12}, 4, 4);
+shared_buffer<bfloat16> l2_123 = shared_buffer<bfloat16>::create({8,32,16,12}, 4, 6);
+shared_buffer<bfloat16> l2_124 = shared_buffer<bfloat16>::create({8,32,84,12}, 4, 8);
+shared_buffer<bfloat16> l2_125 = shared_buffer<bfloat16>::create({8,20,88,12}, 4, 4);
+shared_buffer<bfloat16> l2_126 = shared_buffer<bfloat16>::create({8,20,88,12}, 4, 4);
+shared_buffer<bfloat16> l2_127 = shared_buffer<bfloat16>::create({8,20,88,12}, 4, 4);
+shared_buffer<bfloat16> l2_128 = shared_buffer<bfloat16>::create({8,20,88,12}, 4, 4);
+shared_buffer<bfloat16> l2_129 = shared_buffer<bfloat16>::create({8,24,84,16}, 4, 8);
+shared_buffer<bfloat16> l2_130 = shared_buffer<bfloat16>::create({8,20,88,12}, 4, 4);
+shared_buffer<bfloat16> l2_131 = shared_buffer<bfloat16>::create({8,20,88,12}, 4, 4);
+shared_buffer<bfloat16> l2_132 = shared_buffer<bfloat16>::create({8,20,88,12}, 4, 4);
+shared_buffer<bfloat16> l2_133 = shared_buffer<bfloat16>::create({8,20,88,12}, 4, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_134_for_layer_135_port0 = shared_buffer<bfloat16>::create({8,240,84,1}, 2, 4);
+shared_buffer<bfloat16> l2_135 = shared_buffer<bfloat16>::create({8,1,84,4}, 4, 4);
+shared_buffer<bfloat16> l2_136 = shared_buffer<bfloat16>::create({8,32,24,1}, 4, 4);
+shared_buffer<bfloat16> l2_137 = shared_buffer<bfloat16>::create({8,64,88,1}, 4, 4);
+shared_buffer<bfloat16> l2_138 = shared_buffer<bfloat16>::create({8,1,96,8}, 4, 4);
+shared_buffer<bfloat16> l2_139 = shared_buffer<bfloat16>::create({8,1,128,4}, 4, 4);
+shared_buffer<bfloat16> l2_140 = shared_buffer<bfloat16>::create({8,1,128,8}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_141_for_layer_142_port0 = shared_buffer<bfloat16>::create({8,20,84,12}, 2, 4);
+shared_buffer<bfloat16> L2_OFM_Buffer_layer_TGSpilling_133133 = shared_buffer<bfloat16>::create({8,20,88,12}, 2, 4);
+shared_buffer<bfloat16> l2_142 = shared_buffer<bfloat16>::create({8,20,88,12}, 4, 4);
+shared_buffer<bfloat16> L2_OFM_Buffer_layer_TGSpilling_123123 = shared_buffer<bfloat16>::create({8,32,16,12}, 2, 4);
+shared_buffer<bfloat16> l2_143 = shared_buffer<bfloat16>::create({8,32,16,12}, 4, 4);
+shared_buffer<bfloat16> l2_144 = shared_buffer<bfloat16>::create({8,32,84,12}, 4, 8);
+shared_buffer<bfloat16> l2_145 = shared_buffer<bfloat16>::create({8,20,88,12}, 4, 4);
+shared_buffer<bfloat16> l2_146 = shared_buffer<bfloat16>::create({8,20,88,12}, 4, 4);
+shared_buffer<bfloat16> l2_147 = shared_buffer<bfloat16>::create({8,20,88,12}, 4, 4);
+shared_buffer<bfloat16> l2_148 = shared_buffer<bfloat16>::create({8,20,88,12}, 4, 4);
+shared_buffer<bfloat16> l2_149 = shared_buffer<bfloat16>::create({8,24,84,16}, 4, 8);
+shared_buffer<bfloat16> l2_150 = shared_buffer<bfloat16>::create({8,20,88,12}, 4, 4);
+shared_buffer<bfloat16> l2_151 = shared_buffer<bfloat16>::create({8,20,88,12}, 4, 4);
+shared_buffer<bfloat16> l2_152 = shared_buffer<bfloat16>::create({8,20,88,12}, 4, 4);
+shared_buffer<bfloat16> l2_153 = shared_buffer<bfloat16>::create({8,20,88,12}, 4, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_154_for_layer_155_port0 = shared_buffer<bfloat16>::create({8,240,84,1}, 2, 4);
+shared_buffer<bfloat16> l2_155 = shared_buffer<bfloat16>::create({8,1,84,4}, 4, 4);
+shared_buffer<bfloat16> l2_156 = shared_buffer<bfloat16>::create({8,32,24,1}, 4, 4);
+shared_buffer<bfloat16> l2_157 = shared_buffer<bfloat16>::create({8,64,88,1}, 4, 4);
+shared_buffer<bfloat16> l2_158 = shared_buffer<bfloat16>::create({8,1,96,8}, 4, 4);
+shared_buffer<bfloat16> l2_159 = shared_buffer<bfloat16>::create({8,1,128,4}, 4, 4);
+shared_buffer<bfloat16> l2_160 = shared_buffer<bfloat16>::create({8,1,128,8}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_161_for_layer_162_port0 = shared_buffer<bfloat16>::create({8,20,84,12}, 2, 4);
+shared_buffer<bfloat16> L2_OFM_Buffer_layer_TGSpilling_153153 = shared_buffer<bfloat16>::create({8,20,88,12}, 2, 4);
+shared_buffer<bfloat16> l2_162 = shared_buffer<bfloat16>::create({8,20,88,12}, 4, 4);
+shared_buffer<bfloat16> l2_163 = shared_buffer<bfloat16>::create({8,32,20,12}, 4, 6);
+shared_buffer<bfloat16> l2_164 = shared_buffer<bfloat16>::create({8,32,120,12}, 4, 6);
+shared_buffer<bfloat16> l2_165 = shared_buffer<bfloat16>::create({8,20,120,12}, 4, 4);
+shared_buffer<bfloat16> l2_166 = shared_buffer<bfloat16>::create({8,20,120,12}, 4, 4);
+shared_buffer<bfloat16> l2_167 = shared_buffer<bfloat16>::create({8,20,120,12}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_164_for_layer_168_port0 = shared_buffer<bfloat16>::create({8,20,120,6}, 2, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_167_for_layer_168_port1 = shared_buffer<bfloat16>::create({8,20,120,6}, 2, 4);
+shared_buffer<bfloat16> l2_168 = shared_buffer<bfloat16>::create({8,20,120,8}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_168_for_layer_169_port0 = shared_buffer<bfloat16>::create({8,20,120,12}, 2, 4);
+shared_buffer<bfloat16> l2_169 = shared_buffer<bfloat16>::create({8,24,120,16}, 4, 6);
+shared_buffer<bfloat16> l2_170 = shared_buffer<bfloat16>::create({8,20,120,12}, 4, 4);
+shared_buffer<bfloat16> l2_171 = shared_buffer<bfloat16>::create({8,20,120,12}, 4, 4);
+shared_buffer<bfloat16> l2_172 = shared_buffer<bfloat16>::create({8,20,120,12}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_169_for_layer_173_port0 = shared_buffer<bfloat16>::create({8,20,120,6}, 2, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_172_for_layer_173_port1 = shared_buffer<bfloat16>::create({8,20,120,6}, 2, 4);
+shared_buffer<bfloat16> l2_173 = shared_buffer<bfloat16>::create({8,20,120,8}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_174_for_layer_175_port0 = shared_buffer<bfloat16>::create({8,240,120,1}, 2, 4);
+shared_buffer<bfloat16> l2_175 = shared_buffer<bfloat16>::create({8,1,120,4}, 4, 4);
+shared_buffer<bfloat16> l2_176 = shared_buffer<bfloat16>::create({8,64,32,1}, 4, 4);
+shared_buffer<bfloat16> l2_177 = shared_buffer<bfloat16>::create({8,32,120,1}, 4, 4);
+shared_buffer<bfloat16> l2_178 = shared_buffer<bfloat16>::create({8,1,192,4}, 4, 4);
+shared_buffer<bfloat16> l2_179 = shared_buffer<bfloat16>::create({8,1,128,4}, 4, 4);
+shared_buffer<bfloat16> l2_180 = shared_buffer<bfloat16>::create({8,1,128,8}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_173_for_layer_182_port1 = shared_buffer<bfloat16>::create({8,20,120,12}, 2, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_181_for_layer_182_port0 = shared_buffer<bfloat16>::create({8,20,120,12}, 2, 4);
+shared_buffer<bfloat16> l2_182 = shared_buffer<bfloat16>::create({8,20,120,12}, 4, 4);
+shared_buffer<bfloat16> L2_OFM_Buffer_layer_TGSpilling_163163 = shared_buffer<bfloat16>::create({8,32,24,12}, 2, 4);
+shared_buffer<bfloat16> l2_183 = shared_buffer<bfloat16>::create({8,32,24,12}, 4, 6);
+shared_buffer<bfloat16> l2_184 = shared_buffer<bfloat16>::create({8,32,120,12}, 4, 6);
+shared_buffer<bfloat16> l2_185 = shared_buffer<bfloat16>::create({8,20,120,12}, 4, 4);
+shared_buffer<bfloat16> l2_186 = shared_buffer<bfloat16>::create({8,20,120,12}, 4, 4);
+shared_buffer<bfloat16> l2_187 = shared_buffer<bfloat16>::create({8,20,120,12}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_184_for_layer_188_port0 = shared_buffer<bfloat16>::create({8,20,120,6}, 2, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_187_for_layer_188_port1 = shared_buffer<bfloat16>::create({8,20,120,6}, 2, 4);
+shared_buffer<bfloat16> l2_188 = shared_buffer<bfloat16>::create({8,20,120,8}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_188_for_layer_189_port0 = shared_buffer<bfloat16>::create({8,20,120,12}, 2, 4);
+shared_buffer<bfloat16> l2_189 = shared_buffer<bfloat16>::create({8,24,120,16}, 4, 6);
+shared_buffer<bfloat16> l2_190 = shared_buffer<bfloat16>::create({8,20,120,12}, 4, 4);
+shared_buffer<bfloat16> l2_191 = shared_buffer<bfloat16>::create({8,20,120,12}, 4, 4);
+shared_buffer<bfloat16> l2_192 = shared_buffer<bfloat16>::create({8,20,120,12}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_189_for_layer_193_port0 = shared_buffer<bfloat16>::create({8,20,120,6}, 2, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_192_for_layer_193_port1 = shared_buffer<bfloat16>::create({8,20,120,6}, 2, 4);
+shared_buffer<bfloat16> l2_193 = shared_buffer<bfloat16>::create({8,20,120,8}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_194_for_layer_195_port0 = shared_buffer<bfloat16>::create({8,240,120,1}, 2, 4);
+shared_buffer<bfloat16> l2_195 = shared_buffer<bfloat16>::create({8,1,120,4}, 4, 4);
+shared_buffer<bfloat16> l2_196 = shared_buffer<bfloat16>::create({8,64,32,1}, 4, 4);
+shared_buffer<bfloat16> l2_197 = shared_buffer<bfloat16>::create({8,32,120,1}, 4, 4);
+shared_buffer<bfloat16> l2_198 = shared_buffer<bfloat16>::create({8,1,192,4}, 4, 4);
+shared_buffer<bfloat16> l2_199 = shared_buffer<bfloat16>::create({8,1,128,4}, 4, 4);
+shared_buffer<bfloat16> l2_200 = shared_buffer<bfloat16>::create({8,1,128,8}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_193_for_layer_202_port1 = shared_buffer<bfloat16>::create({8,20,120,12}, 2, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_201_for_layer_202_port0 = shared_buffer<bfloat16>::create({8,20,120,12}, 2, 4);
+shared_buffer<bfloat16> l2_202 = shared_buffer<bfloat16>::create({8,20,120,12}, 4, 4);
+shared_buffer<bfloat16> L2_OFM_Buffer_layer_TGSpilling_183183 = shared_buffer<bfloat16>::create({8,32,24,12}, 2, 4);
+shared_buffer<bfloat16> l2_203 = shared_buffer<bfloat16>::create({8,32,24,12}, 4, 4);
+shared_buffer<bfloat16> l2_204 = shared_buffer<bfloat16>::create({8,32,120,12}, 4, 6);
+shared_buffer<bfloat16> l2_205 = shared_buffer<bfloat16>::create({8,20,120,12}, 4, 4);
+shared_buffer<bfloat16> l2_206 = shared_buffer<bfloat16>::create({8,20,120,12}, 4, 4);
+shared_buffer<bfloat16> l2_207 = shared_buffer<bfloat16>::create({8,20,120,12}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_204_for_layer_208_port0 = shared_buffer<bfloat16>::create({8,20,120,6}, 2, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_207_for_layer_208_port1 = shared_buffer<bfloat16>::create({8,20,120,6}, 2, 4);
+shared_buffer<bfloat16> l2_208 = shared_buffer<bfloat16>::create({8,20,120,8}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_209_for_layer_210_port0 = shared_buffer<bfloat16>::create({8,240,120,1}, 2, 4);
+shared_buffer<bfloat16> l2_210 = shared_buffer<bfloat16>::create({8,1,120,4}, 4, 4);
+shared_buffer<bfloat16> l2_211 = shared_buffer<bfloat16>::create({8,64,16,1}, 4, 4);
+shared_buffer<bfloat16> l2_212 = shared_buffer<bfloat16>::create({8,1,16,64}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_208_for_layer_214_port0 = shared_buffer<bfloat16>::create({8,20,120,12}, 2, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_213_for_layer_214_port1 = shared_buffer<bfloat16>::create({8,32,16,12}, 2, 4);
+shared_buffer<bfloat16> l2_214 = shared_buffer<bfloat16>::create({8,32,16,12}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_216_for_layer_217_port0 = shared_buffer<bfloat16>::create({8,20,8,12}, 2, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_for_input4_0_port1 = shared_buffer<bfloat16>::create({8,20,8,12}, 2, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_217_for_layer_218_port0 = shared_buffer<bfloat16>::create({8,20,16,12}, 2, 4);
+shared_buffer<bfloat16> l2_218 = shared_buffer<bfloat16>::create({8,32,16,12}, 4, 4);
+shared_buffer<bfloat16> l2_219 = shared_buffer<bfloat16>::create({8,20,16,12}, 4, 2);
+shared_buffer<bfloat16> L2_CONST_IFM_Buffer_for_input3_0_port0 = shared_buffer<bfloat16>::create({8,20,8,12}, 2, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_220_for_layer_221_port1 = shared_buffer<bfloat16>::create({8,20,8,12}, 2, 4);
+shared_buffer<bfloat16> l2_221 = shared_buffer<bfloat16>::create({8,20,8,12}, 4, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_for_input4_1_port1 = shared_buffer<bfloat16>::create({8,20,8,12}, 2, 4);
+shared_buffer<bfloat16> l2_222 = shared_buffer<bfloat16>::create({8,20,8,12}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_for_input4_2_port1 = shared_buffer<bfloat16>::create({8,20,8,12}, 2, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_223_for_layer_224_port0 = shared_buffer<bfloat16>::create({8,20,8,12}, 2, 4);
+shared_buffer<bfloat16> l2_224 = shared_buffer<bfloat16>::create({8,20,8,12}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_216_for_layer_225_port0 = shared_buffer<bfloat16>::create({8,20,8,12}, 2, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_225_for_layer_226_port0 = shared_buffer<bfloat16>::create({8,20,16,12}, 2, 4);
+shared_buffer<bfloat16> l2_226 = shared_buffer<bfloat16>::create({8,32,8,12}, 4, 4);
+shared_buffer<bfloat16> l2_227 = shared_buffer<bfloat16>::create({8,20,8,12}, 4, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_220_for_layer_228_port0 = shared_buffer<bfloat16>::create({8,20,8,12}, 2, 4);
+shared_buffer<bfloat16> l2_228 = shared_buffer<bfloat16>::create({8,20,8,12}, 4, 4);
+shared_buffer<bfloat16> L2_OFM_Buffer_layer_TGSpilling_222222 = shared_buffer<bfloat16>::create({8,20,8,12}, 2, 4);
+shared_buffer<bfloat16> l2_229 = shared_buffer<bfloat16>::create({8,20,8,12}, 4, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_215_for_layer_230_port0 = shared_buffer<bfloat16>::create({8,20,8,12}, 2, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_232_for_layer_236_port0 = shared_buffer<bfloat16>::create({8,40,16,23}, 2, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_5_for_layer_233_port0 = shared_buffer<bfloat16>::create({8,320,1,60}, 2, 4);
+shared_buffer<bfloat16> l2_233 = shared_buffer<bfloat16>::create({8,160,4,32}, 4, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_233_for_layer_234_port0 = shared_buffer<bfloat16>::create({8,160,1,90}, 2, 4);
+shared_buffer<bfloat16> l2_234 = shared_buffer<bfloat16>::create({8,80,4,48}, 4, 6);
+shared_buffer<bfloat16> l2_235 = shared_buffer<bfloat16>::create({8,40,4,24}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_236_for_layer_237_port0 = shared_buffer<bfloat16>::create({8,40,22,23}, 2, 4);
+shared_buffer<bfloat16> l2_237 = shared_buffer<bfloat16>::create({8,48,16,24}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_239_for_layer_240_port0 = shared_buffer<bfloat16>::create({8,40,5,23}, 2, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_for_input3_0_port1 = shared_buffer<bfloat16>::create({8,40,5,23}, 2, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_240_for_layer_241_port0 = shared_buffer<bfloat16>::create({8,40,10,23}, 2, 4);
+shared_buffer<bfloat16> l2_241 = shared_buffer<bfloat16>::create({8,48,16,24}, 4, 4);
+shared_buffer<bfloat16> l2_242 = shared_buffer<bfloat16>::create({8,40,12,24}, 4, 2);
+shared_buffer<bfloat16> L2_CONST_IFM_Buffer_for_input2_0_port0 = shared_buffer<bfloat16>::create({8,40,5,23}, 2, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_243_for_layer_244_port1 = shared_buffer<bfloat16>::create({8,40,5,23}, 2, 4);
+shared_buffer<bfloat16> l2_244 = shared_buffer<bfloat16>::create({8,40,8,24}, 4, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_for_input3_1_port1 = shared_buffer<bfloat16>::create({8,40,5,23}, 2, 4);
+shared_buffer<bfloat16> l2_245 = shared_buffer<bfloat16>::create({8,40,8,24}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_for_input3_2_port1 = shared_buffer<bfloat16>::create({8,40,5,23}, 2, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_246_for_layer_247_port0 = shared_buffer<bfloat16>::create({8,40,5,23}, 2, 4);
+shared_buffer<bfloat16> l2_247 = shared_buffer<bfloat16>::create({8,40,8,24}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_239_for_layer_248_port0 = shared_buffer<bfloat16>::create({8,40,5,23}, 2, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_248_for_layer_249_port0 = shared_buffer<bfloat16>::create({8,40,10,23}, 2, 4);
+shared_buffer<bfloat16> l2_249 = shared_buffer<bfloat16>::create({8,48,8,24}, 4, 4);
+shared_buffer<bfloat16> l2_250 = shared_buffer<bfloat16>::create({8,40,8,24}, 4, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_243_for_layer_251_port0 = shared_buffer<bfloat16>::create({8,40,5,23}, 2, 4);
+shared_buffer<bfloat16> l2_251 = shared_buffer<bfloat16>::create({8,40,8,24}, 4, 4);
+shared_buffer<bfloat16> L2_OFM_Buffer_layer_TGSpilling_245245 = shared_buffer<bfloat16>::create({8,40,8,24}, 2, 4);
+shared_buffer<bfloat16> l2_252 = shared_buffer<bfloat16>::create({8,40,8,24}, 4, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_238_for_layer_253_port0 = shared_buffer<bfloat16>::create({8,40,5,23}, 2, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_255_for_layer_256_port0 = shared_buffer<bfloat16>::create({8,80,10,45}, 2, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_256_for_layer_257_port0 = shared_buffer<bfloat16>::create({8,80,14,45}, 2, 4);
+shared_buffer<bfloat16> l2_257 = shared_buffer<bfloat16>::create({8,80,8,48}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_260_for_layer_261_port0 = shared_buffer<bfloat16>::create({8,80,5,45}, 2, 4);
+shared_buffer<bfloat16> l2_261 = shared_buffer<bfloat16>::create({8,80,8,48}, 4, 4);
+shared_buffer<bfloat16> l2_262 = shared_buffer<bfloat16>::create({8,80,8,48}, 4, 2);
+shared_buffer<bfloat16> L2_CONST_IFM_Buffer_for_input1_0_port0 = shared_buffer<bfloat16>::create({8,80,3,45}, 2, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_263_for_layer_264_port1 = shared_buffer<bfloat16>::create({8,80,3,45}, 2, 4);
+shared_buffer<bfloat16> l2_264 = shared_buffer<bfloat16>::create({8,80,4,48}, 4, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_for_input2_1_port1 = shared_buffer<bfloat16>::create({8,80,3,45}, 2, 4);
+shared_buffer<bfloat16> l2_265 = shared_buffer<bfloat16>::create({8,80,4,48}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_for_input2_2_port1 = shared_buffer<bfloat16>::create({8,80,3,45}, 2, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_266_for_layer_267_port0 = shared_buffer<bfloat16>::create({8,80,3,45}, 2, 4);
+shared_buffer<bfloat16> l2_267 = shared_buffer<bfloat16>::create({8,80,4,48}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_268_for_layer_269_port0 = shared_buffer<bfloat16>::create({8,80,5,45}, 2, 4);
+shared_buffer<bfloat16> l2_269 = shared_buffer<bfloat16>::create({8,96,4,48}, 4, 4);
+shared_buffer<bfloat16> l2_270 = shared_buffer<bfloat16>::create({8,80,4,48}, 4, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_263_for_layer_271_port0 = shared_buffer<bfloat16>::create({8,80,3,45}, 2, 4);
+shared_buffer<bfloat16> l2_271 = shared_buffer<bfloat16>::create({8,80,4,48}, 4, 4);
+shared_buffer<bfloat16> L2_OFM_Buffer_layer_TGSpilling_265265 = shared_buffer<bfloat16>::create({8,80,4,48}, 2, 4);
+shared_buffer<bfloat16> l2_272 = shared_buffer<bfloat16>::create({8,80,4,48}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_275_for_layer_276_port0 = shared_buffer<bfloat16>::create({8,160,8,20}, 2, 4);
+shared_buffer<bfloat16> l2_276 = shared_buffer<bfloat16>::create({8,160,4,20}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_278_for_layer_279_port0 = shared_buffer<bfloat16>::create({8,160,2,90}, 2, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_for_input1_0_port1 = shared_buffer<bfloat16>::create({8,160,2,90}, 2, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_279_for_layer_280_port0 = shared_buffer<bfloat16>::create({8,160,4,32}, 2, 4);
+shared_buffer<bfloat16> l2_280 = shared_buffer<bfloat16>::create({8,160,4,32}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_280_for_layer_281_port0 = shared_buffer<bfloat16>::create({8,160,4,30}, 2, 4);
+shared_buffer<bfloat16> l2_281 = shared_buffer<bfloat16>::create({8,160,4,32}, 4, 2);
+shared_buffer<bfloat16> L2_CONST_IFM_Buffer_for_input0_0_port0 = shared_buffer<bfloat16>::create({8,160,2,30}, 2, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_282_for_layer_283_port1 = shared_buffer<bfloat16>::create({8,160,2,30}, 2, 4);
+shared_buffer<bfloat16> l2_283 = shared_buffer<bfloat16>::create({8,160,4,32}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_for_input1_1_port1 = shared_buffer<bfloat16>::create({8,160,2,30}, 2, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_283_for_layer_284_port0 = shared_buffer<bfloat16>::create({8,160,2,30}, 2, 4);
+shared_buffer<bfloat16> l2_284 = shared_buffer<bfloat16>::create({8,160,4,32}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_for_input1_2_port1 = shared_buffer<bfloat16>::create({8,160,2,30}, 2, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_285_for_layer_286_port0 = shared_buffer<bfloat16>::create({8,160,2,30}, 2, 4);
+shared_buffer<bfloat16> l2_286 = shared_buffer<bfloat16>::create({8,160,4,32}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_278_for_layer_287_port0 = shared_buffer<bfloat16>::create({8,160,2,90}, 2, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_287_for_layer_288_port0 = shared_buffer<bfloat16>::create({8,160,4,32}, 2, 4);
+shared_buffer<bfloat16> l2_288 = shared_buffer<bfloat16>::create({8,160,4,32}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_288_for_layer_289_port0 = shared_buffer<bfloat16>::create({8,160,2,90}, 2, 4);
+shared_buffer<bfloat16> l2_289 = shared_buffer<bfloat16>::create({8,160,4,92}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_282_for_layer_290_port0 = shared_buffer<bfloat16>::create({8,160,2,30}, 2, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_289_for_layer_290_port1 = shared_buffer<bfloat16>::create({8,160,2,30}, 2, 4);
+shared_buffer<bfloat16> l2_290 = shared_buffer<bfloat16>::create({8,160,4,32}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_284_for_layer_291_port0 = shared_buffer<bfloat16>::create({8,160,2,30}, 2, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_290_for_layer_291_port1 = shared_buffer<bfloat16>::create({8,160,2,30}, 2, 4);
+shared_buffer<bfloat16> l2_291 = shared_buffer<bfloat16>::create({8,160,4,32}, 4, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_277_for_layer_292_port0 = shared_buffer<bfloat16>::create({8,160,2,90}, 2, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_5_for_layer_294_port1 = shared_buffer<bfloat16>::create({8,320,1,180}, 2, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_294_for_layer_295_port0 = shared_buffer<bfloat16>::create({8,320,5,17}, 2, 4);
+shared_buffer<bfloat16> l2_295 = shared_buffer<bfloat16>::create({8,320,4,16}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_295_for_layer_296_port0 = shared_buffer<bfloat16>::create({8,320,2,22}, 2, 4);
+shared_buffer<bfloat16> l2_296 = shared_buffer<bfloat16>::create({8,320,4,20}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_296_for_layer_297_port0 = shared_buffer<bfloat16>::create({8,320,2,20}, 2, 4);
+shared_buffer<bfloat16> l2_297 = shared_buffer<bfloat16>::create({8,320,4,20}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_298_for_layer_299_port0 = shared_buffer<bfloat16>::create({8,320,1,20}, 2, 4);
+shared_buffer<bfloat16> L2_OFM_Buffer_layer_299 = shared_buffer<bfloat16>::create({8,320,4,20}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_5_for_layer_301_port1 = shared_buffer<bfloat16>::create({8,320,1,20}, 2, 4);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_300_for_layer_301_port0 = shared_buffer<bfloat16>::create({8,320,1,20}, 2, 4);
+shared_buffer<bfloat16> l2_301 = shared_buffer<bfloat16>::create({8,320,4,20}, 4, 2);
+shared_buffer<bfloat16> L2_IFM_Buffer_from_layer_301_for_layer_302_port0 = shared_buffer<bfloat16>::create({8,320,1,20}, 2, 4);
+shared_buffer<bfloat16> L2_OFM_Buffer_layer_302 = shared_buffer<bfloat16>::create({8,320,4,20}, 4, 2);
+
+//L3 Buffer creation
+external_buffer<bfloat16> ifm_ddr = external_buffer<bfloat16>::create({8,4,23,320}, 0, 2);
+external_buffer<bfloat16> l2l3_1_spill = external_buffer<bfloat16>::create({8,4,23,320}, 2, 2);
+external_buffer<bfloat16> l2l3_2_spill = external_buffer<bfloat16>::create({8,3,23,320}, 2, 1);
+external_buffer<bfloat16> l2l3_scratch_0_3_spill = external_buffer<bfloat16>::create({471040}, 1, 1);
+external_buffer<bfloat16> l2l3_3_spill = external_buffer<bfloat16>::create({8,8,23,320}, 1, 1);
+external_buffer<bfloat16> l2l3_4_spill = external_buffer<bfloat16>::create({8,320,1,184}, 1, 1);
+external_buffer<bfloat16> l2l3_scratch_0_5_spill = external_buffer<bfloat16>::create({460800}, 1, 1);
+external_buffer<bfloat16> l2l3_5_spill = external_buffer<bfloat16>::create({8,320,1,180}, 1, 8);
+external_buffer<bfloat16> const_ifm_ddr_5 = external_buffer<bfloat16>::create({8,320,1,180}, 0, 2);
+external_buffer<bfloat16> l2l3_6_spill = external_buffer<bfloat16>::create({8,320,1,180}, 2, 2);
+external_buffer<bfloat16> const_ifm_ddr_4 = external_buffer<bfloat16>::create({8,320,1,180}, 0, 2);
+external_buffer<bfloat16> l2l3_7_spill = external_buffer<bfloat16>::create({8,320,1,180}, 2, 2);
+external_buffer<bfloat16> l2l3_8_spill = external_buffer<bfloat16>::create({8,160,2,90}, 2, 4);
+external_buffer<bfloat16> l2l3_9_spill = external_buffer<bfloat16>::create({8,160,2,90}, 2, 2);
+external_buffer<bfloat16> l2l3_10_spill = external_buffer<bfloat16>::create({8,160,2,90}, 2, 2);
+external_buffer<bfloat16> l2l3_11_spill = external_buffer<bfloat16>::create({8,160,2,90}, 2, 2);
+external_buffer<bfloat16> l2l3_12_spill = external_buffer<bfloat16>::create({8,160,2,90}, 2, 4);
+external_buffer<bfloat16> l2l3_13_spill = external_buffer<bfloat16>::create({8,160,2,90}, 2, 2);
+external_buffer<bfloat16> l2l3_14_spill = external_buffer<bfloat16>::create({8,160,2,90}, 2, 2);
+external_buffer<bfloat16> l2l3_15_spill = external_buffer<bfloat16>::create({8,160,8,90}, 2, 2);
+external_buffer<bfloat16> l2l3_16_spill = external_buffer<bfloat16>::create({8,80,8,48}, 2, 1);
+external_buffer<bfloat16> l2l3_scratch_0_17_spill = external_buffer<bfloat16>::create({230400}, 1, 1);
+external_buffer<bfloat16> l2l3_17_spill = external_buffer<bfloat16>::create({8,80,8,45}, 1, 2);
+external_buffer<bfloat16> L3_OFM_Buffer_layer_TGSpilling_1818 = external_buffer<bfloat16>::create({8,80,3,45}, 2, 2);
+external_buffer<bfloat16> l2l3_19_spill = external_buffer<bfloat16>::create({8,80,9,45}, 2, 2);
+external_buffer<bfloat16> l2l3_20_spill = external_buffer<bfloat16>::create({8,80,9,46}, 2, 1);
+external_buffer<bfloat16> l2l3_scratch_0_21_spill = external_buffer<bfloat16>::create({259200}, 1, 1);
+external_buffer<bfloat16> l2l3_21_spill = external_buffer<bfloat16>::create({8,80,9,45}, 1, 2);
+external_buffer<bfloat16> L3_OFM_Buffer_layer_TGSpilling_2424 = external_buffer<bfloat16>::create({8,40,9,23}, 2, 2);
+external_buffer<bfloat16> l2l3_24_spill = external_buffer<bfloat16>::create({8,40,9,23}, 2, 1);
+external_buffer<bfloat16> l2l3_25_spill = external_buffer<bfloat16>::create({8,920,9,1}, 1, 2);
+external_buffer<bfloat16> l2l3_31_spill = external_buffer<bfloat16>::create({8,1,9,1}, 2, 1);
+external_buffer<bfloat16> l2l3_scratch_0_32_spill = external_buffer<bfloat16>::create({66240}, 1, 1);
+external_buffer<bfloat16> l2l3_scratch_1_32_spill = external_buffer<bfloat16>::create({66240}, 1, 1);
+external_buffer<bfloat16> l2l3_32_spill = external_buffer<bfloat16>::create({8,40,9,23}, 1, 2);
+external_buffer<bfloat16> L3_OFM_Buffer_layer_TGSpilling_3434 = external_buffer<bfloat16>::create({8,40,5,23}, 2, 2);
+external_buffer<bfloat16> L3_OFM_Buffer_layer_TGSpilling_3636 = external_buffer<bfloat16>::create({8,40,15,23}, 2, 2);
+external_buffer<bfloat16> l2l3_36_spill = external_buffer<bfloat16>::create({8,40,15,23}, 2, 1);
+external_buffer<bfloat16> l2l3_37_spill = external_buffer<bfloat16>::create({8,920,15,1}, 1, 2);
+external_buffer<bfloat16> l2l3_43_spill = external_buffer<bfloat16>::create({8,1,15,1}, 2, 1);
+external_buffer<bfloat16> l2l3_scratch_0_44_spill = external_buffer<bfloat16>::create({110400}, 1, 1);
+external_buffer<bfloat16> l2l3_scratch_1_44_spill = external_buffer<bfloat16>::create({110400}, 1, 1);
+external_buffer<bfloat16> l2l3_44_spill = external_buffer<bfloat16>::create({8,40,15,23}, 1, 2);
+external_buffer<bfloat16> L3_OFM_Buffer_layer_TGSpilling_4646 = external_buffer<bfloat16>::create({8,40,5,23}, 2, 2);
+external_buffer<bfloat16> L3_OFM_Buffer_layer_TGSpilling_4848 = external_buffer<bfloat16>::create({8,40,15,23}, 2, 2);
+external_buffer<bfloat16> l2l3_48_spill = external_buffer<bfloat16>::create({8,40,15,23}, 2, 1);
+external_buffer<bfloat16> l2l3_49_spill = external_buffer<bfloat16>::create({8,920,15,1}, 1, 2);
+external_buffer<bfloat16> l2l3_55_spill = external_buffer<bfloat16>::create({8,1,15,1}, 2, 1);
+external_buffer<bfloat16> l2l3_scratch_0_56_spill = external_buffer<bfloat16>::create({110400}, 1, 1);
+external_buffer<bfloat16> l2l3_scratch_1_56_spill = external_buffer<bfloat16>::create({110400}, 1, 1);
+external_buffer<bfloat16> l2l3_56_spill = external_buffer<bfloat16>::create({8,40,15,23}, 1, 2);
+external_buffer<bfloat16> l2l3_59_spill = external_buffer<bfloat16>::create({8,40,30,23}, 2, 2);
+external_buffer<bfloat16> l2l3_62_spill = external_buffer<bfloat16>::create({8,40,30,23}, 2, 2);
+external_buffer<bfloat16> l2l3_63_spill = external_buffer<bfloat16>::create({8,40,30,24}, 2, 1);
+external_buffer<bfloat16> l2l3_scratch_0_64_spill = external_buffer<bfloat16>::create({220800}, 1, 1);
+external_buffer<bfloat16> l2l3_64_spill = external_buffer<bfloat16>::create({8,40,30,23}, 1, 2);
+external_buffer<bfloat16> L3_OFM_Buffer_layer_TGSpilling_113113 = external_buffer<bfloat16>::create({8,20,60,12}, 2, 2);
+external_buffer<bfloat16> l2l3_113_spill = external_buffer<bfloat16>::create({8,20,60,12}, 2, 1);
+external_buffer<bfloat16> l2l3_114_spill = external_buffer<bfloat16>::create({8,240,60,1}, 1, 2);
+external_buffer<bfloat16> l2l3_120_spill = external_buffer<bfloat16>::create({8,1,60,1}, 2, 1);
+external_buffer<bfloat16> l2l3_scratch_0_121_spill = external_buffer<bfloat16>::create({115200}, 1, 1);
+external_buffer<bfloat16> l2l3_scratch_1_121_spill = external_buffer<bfloat16>::create({115200}, 1, 1);
+external_buffer<bfloat16> l2l3_121_spill = external_buffer<bfloat16>::create({8,20,60,12}, 1, 2);
+external_buffer<bfloat16> L3_OFM_Buffer_layer_TGSpilling_123123 = external_buffer<bfloat16>::create({8,20,14,12}, 2, 2);
+external_buffer<bfloat16> L3_OFM_Buffer_layer_TGSpilling_133133 = external_buffer<bfloat16>::create({8,20,84,12}, 2, 2);
+external_buffer<bfloat16> l2l3_133_spill = external_buffer<bfloat16>::create({8,20,84,12}, 2, 1);
+external_buffer<bfloat16> l2l3_134_spill = external_buffer<bfloat16>::create({8,240,84,1}, 1, 2);
+external_buffer<bfloat16> l2l3_140_spill = external_buffer<bfloat16>::create({8,1,84,1}, 2, 1);
+external_buffer<bfloat16> l2l3_scratch_0_141_spill = external_buffer<bfloat16>::create({161280}, 1, 1);
+external_buffer<bfloat16> l2l3_scratch_1_141_spill = external_buffer<bfloat16>::create({161280}, 1, 1);
+external_buffer<bfloat16> l2l3_141_spill = external_buffer<bfloat16>::create({8,20,84,12}, 1, 2);
+external_buffer<bfloat16> L3_OFM_Buffer_layer_TGSpilling_153153 = external_buffer<bfloat16>::create({8,20,84,12}, 2, 2);
+external_buffer<bfloat16> l2l3_153_spill = external_buffer<bfloat16>::create({8,20,84,12}, 2, 1);
+external_buffer<bfloat16> l2l3_154_spill = external_buffer<bfloat16>::create({8,240,84,1}, 1, 2);
+external_buffer<bfloat16> l2l3_160_spill = external_buffer<bfloat16>::create({8,1,84,1}, 2, 1);
+external_buffer<bfloat16> l2l3_scratch_1_161_spill = external_buffer<bfloat16>::create({161280}, 1, 1);
+external_buffer<bfloat16> l2l3_scratch_0_161_spill = external_buffer<bfloat16>::create({161280}, 1, 1);
+external_buffer<bfloat16> l2l3_161_spill = external_buffer<bfloat16>::create({8,20,84,12}, 1, 2);
+external_buffer<bfloat16> L3_OFM_Buffer_layer_TGSpilling_163163 = external_buffer<bfloat16>::create({8,20,20,12}, 2, 2);
+external_buffer<bfloat16> l2l3_164_spill = external_buffer<bfloat16>::create({8,20,120,12}, 2, 2);
+external_buffer<bfloat16> l2l3_167_spill = external_buffer<bfloat16>::create({8,20,120,12}, 2, 2);
+external_buffer<bfloat16> l2l3_168_spill = external_buffer<bfloat16>::create({8,20,120,12}, 2, 2);
+external_buffer<bfloat16> l2l3_169_spill = external_buffer<bfloat16>::create({8,20,120,12}, 2, 2);
+external_buffer<bfloat16> l2l3_172_spill = external_buffer<bfloat16>::create({8,20,120,12}, 2, 2);
+external_buffer<bfloat16> l2l3_173_spill = external_buffer<bfloat16>::create({8,20,120,12}, 2, 3);
+external_buffer<bfloat16> l2l3_174_spill = external_buffer<bfloat16>::create({8,240,120,1}, 1, 2);
+external_buffer<bfloat16> l2l3_180_spill = external_buffer<bfloat16>::create({8,1,120,1}, 2, 1);
+external_buffer<bfloat16> l2l3_scratch_0_181_spill = external_buffer<bfloat16>::create({230400}, 1, 1);
+external_buffer<bfloat16> l2l3_scratch_1_181_spill = external_buffer<bfloat16>::create({230400}, 1, 1);
+external_buffer<bfloat16> l2l3_181_spill = external_buffer<bfloat16>::create({8,20,120,12}, 1, 2);
+external_buffer<bfloat16> L3_OFM_Buffer_layer_TGSpilling_183183 = external_buffer<bfloat16>::create({8,20,20,12}, 2, 2);
+external_buffer<bfloat16> l2l3_184_spill = external_buffer<bfloat16>::create({8,20,120,12}, 2, 2);
+external_buffer<bfloat16> l2l3_187_spill = external_buffer<bfloat16>::create({8,20,120,12}, 2, 2);
+external_buffer<bfloat16> l2l3_188_spill = external_buffer<bfloat16>::create({8,20,120,12}, 2, 2);
+external_buffer<bfloat16> l2l3_189_spill = external_buffer<bfloat16>::create({8,20,120,12}, 2, 2);
+external_buffer<bfloat16> l2l3_192_spill = external_buffer<bfloat16>::create({8,20,120,12}, 2, 2);
+external_buffer<bfloat16> l2l3_193_spill = external_buffer<bfloat16>::create({8,20,120,12}, 2, 3);
+external_buffer<bfloat16> l2l3_194_spill = external_buffer<bfloat16>::create({8,240,120,1}, 1, 2);
+external_buffer<bfloat16> l2l3_200_spill = external_buffer<bfloat16>::create({8,1,120,1}, 2, 1);
+external_buffer<bfloat16> l2l3_scratch_0_201_spill = external_buffer<bfloat16>::create({230400}, 1, 1);
+external_buffer<bfloat16> l2l3_scratch_1_201_spill = external_buffer<bfloat16>::create({230400}, 1, 1);
+external_buffer<bfloat16> l2l3_201_spill = external_buffer<bfloat16>::create({8,20,120,12}, 1, 2);
+external_buffer<bfloat16> l2l3_204_spill = external_buffer<bfloat16>::create({8,20,120,12}, 2, 2);
+external_buffer<bfloat16> l2l3_207_spill = external_buffer<bfloat16>::create({8,20,120,12}, 2, 2);
+external_buffer<bfloat16> l2l3_208_spill = external_buffer<bfloat16>::create({8,20,120,12}, 2, 3);
+external_buffer<bfloat16> l2l3_209_spill = external_buffer<bfloat16>::create({8,240,120,1}, 1, 2);
+external_buffer<bfloat16> l2l3_212_spill = external_buffer<bfloat16>::create({8,1,16,1}, 2, 1);
+external_buffer<bfloat16> l2l3_scratch_0_213_spill = external_buffer<bfloat16>::create({30720}, 1, 1);
+external_buffer<bfloat16> l2l3_scratch_1_213_spill = external_buffer<bfloat16>::create({30720}, 1, 1);
+external_buffer<bfloat16> l2l3_213_spill = external_buffer<bfloat16>::create({8,20,16,12}, 1, 2);
+external_buffer<bfloat16> l2l3_214_spill = external_buffer<bfloat16>::create({8,20,16,12}, 2, 4);
+external_buffer<bfloat16> l2l3_215_spill = external_buffer<bfloat16>::create({8,20,8,12}, 2, 2);
+external_buffer<bfloat16> l2l3_216_spill = external_buffer<bfloat16>::create({8,20,8,12}, 2, 4);
+external_buffer<bfloat16> ifm_ddr_4 = external_buffer<bfloat16>::create({8,20,8,12}, 0, 6);
+external_buffer<bfloat16> spill_L3_Concat_Buffer_layer_217 = external_buffer<bfloat16>::create({8,20,16,12}, 4, 2);
+external_buffer<bfloat16> l2l3_219_spill = external_buffer<bfloat16>::create({8,20,16,12}, 2, 4);
+external_buffer<bfloat16> l2l3_220_spill = external_buffer<bfloat16>::create({8,20,8,12}, 2, 4);
+external_buffer<bfloat16> const_ifm_ddr_3 = external_buffer<bfloat16>::create({8,20,8,12}, 0, 2);
+external_buffer<bfloat16> L3_OFM_Buffer_layer_TGSpilling_222222 = external_buffer<bfloat16>::create({8,20,8,12}, 2, 2);
+external_buffer<bfloat16> l2l3_223_spill = external_buffer<bfloat16>::create({8,20,8,12}, 2, 2);
+external_buffer<bfloat16> spill_L3_Concat_Buffer_layer_225 = external_buffer<bfloat16>::create({8,20,16,12}, 4, 2);
+external_buffer<bfloat16> ofm_ddr_0_l2l3_229_spill = external_buffer<bfloat16>::create({8,20,8,12}, 2, 0);
+external_buffer<bfloat16> spill_L3_Concat_Buffer_layer_230 = external_buffer<bfloat16>::create({8,20,16,12}, 4, 2);
+external_buffer<bfloat16> l2l3_231_spill = external_buffer<bfloat16>::create({8,40,16,24}, 2, 2);
+external_buffer<bfloat16> l2l3_232_spill = external_buffer<bfloat16>::create({8,40,16,23}, 2, 2);
+external_buffer<bfloat16> l2l3_233_spill = external_buffer<bfloat16>::create({8,160,1,90}, 2, 2);
+external_buffer<bfloat16> spill_L3_Concat_Buffer_layer_236 = external_buffer<bfloat16>::create({8,40,22,23}, 6, 2);
+external_buffer<bfloat16> l2l3_237_spill = external_buffer<bfloat16>::create({8,40,10,23}, 2, 4);
+external_buffer<bfloat16> l2l3_238_spill = external_buffer<bfloat16>::create({8,40,5,23}, 2, 2);
+external_buffer<bfloat16> l2l3_239_spill = external_buffer<bfloat16>::create({8,40,5,23}, 2, 4);
+external_buffer<bfloat16> ifm_ddr_3 = external_buffer<bfloat16>::create({8,40,5,23}, 0, 6);
+external_buffer<bfloat16> spill_L3_Concat_Buffer_layer_240 = external_buffer<bfloat16>::create({8,40,10,23}, 4, 2);
+external_buffer<bfloat16> l2l3_242_spill = external_buffer<bfloat16>::create({8,40,10,23}, 2, 4);
+external_buffer<bfloat16> l2l3_243_spill = external_buffer<bfloat16>::create({8,40,5,23}, 2, 4);
+external_buffer<bfloat16> const_ifm_ddr_2 = external_buffer<bfloat16>::create({8,40,5,23}, 0, 2);
+external_buffer<bfloat16> L3_OFM_Buffer_layer_TGSpilling_245245 = external_buffer<bfloat16>::create({8,40,5,23}, 2, 2);
+external_buffer<bfloat16> l2l3_246_spill = external_buffer<bfloat16>::create({8,40,5,23}, 2, 2);
+external_buffer<bfloat16> spill_L3_Concat_Buffer_layer_248 = external_buffer<bfloat16>::create({8,40,10,23}, 4, 2);
+external_buffer<bfloat16> ofm_ddr_1_l2l3_252_spill = external_buffer<bfloat16>::create({8,40,5,23}, 2, 0);
+external_buffer<bfloat16> spill_L3_Concat_Buffer_layer_253 = external_buffer<bfloat16>::create({8,40,10,23}, 4, 2);
+external_buffer<bfloat16> l2l3_254_spill = external_buffer<bfloat16>::create({8,80,10,46}, 2, 2);
+external_buffer<bfloat16> l2l3_255_spill = external_buffer<bfloat16>::create({8,80,10,45}, 2, 2);
+external_buffer<bfloat16> spill_L3_Concat_Buffer_layer_256 = external_buffer<bfloat16>::create({8,80,14,45}, 6, 2);
+external_buffer<bfloat16> l2l3_257_spill = external_buffer<bfloat16>::create({8,80,5,45}, 2, 4);
+external_buffer<bfloat16> l2l3_258_spill = external_buffer<bfloat16>::create({8,80,3,45}, 2, 1);
+external_buffer<bfloat16> l2l3_259_spill = external_buffer<bfloat16>::create({8,80,3,45}, 2, 2);
+external_buffer<bfloat16> ifm_ddr_2 = external_buffer<bfloat16>::create({8,80,3,45}, 0, 5);
+external_buffer<bfloat16> l2l3_260_spill = external_buffer<bfloat16>::create({8,80,5,45}, 1, 2);
+external_buffer<bfloat16> l2l3_262_spill = external_buffer<bfloat16>::create({8,80,5,45}, 2, 4);
+external_buffer<bfloat16> l2l3_263_spill = external_buffer<bfloat16>::create({8,80,3,45}, 2, 4);
+external_buffer<bfloat16> const_ifm_ddr_1 = external_buffer<bfloat16>::create({8,80,3,45}, 0, 2);
+external_buffer<bfloat16> L3_OFM_Buffer_layer_TGSpilling_265265 = external_buffer<bfloat16>::create({8,80,3,45}, 2, 2);
+external_buffer<bfloat16> l2l3_266_spill = external_buffer<bfloat16>::create({8,80,3,45}, 2, 2);
+external_buffer<bfloat16> l2l3_267_spill = external_buffer<bfloat16>::create({8,80,3,45}, 2, 1);
+external_buffer<bfloat16> l2l3_268_spill = external_buffer<bfloat16>::create({8,80,5,45}, 1, 2);
+external_buffer<bfloat16> ofm_ddr_2_l2l3_272_spill = external_buffer<bfloat16>::create({8,80,3,45}, 2, 1);
+external_buffer<bfloat16> l2l3_273_spill = external_buffer<bfloat16>::create({8,80,5,45}, 1, 2);
+external_buffer<bfloat16> spill_L3_Concat_Buffer_layer_275 = external_buffer<bfloat16>::create({8,160,8,90}, 6, 2);
+external_buffer<bfloat16> l2l3_276_spill = external_buffer<bfloat16>::create({8,160,4,90}, 2, 4);
+external_buffer<bfloat16> l2l3_277_spill = external_buffer<bfloat16>::create({8,160,2,90}, 2, 2);
+external_buffer<bfloat16> l2l3_278_spill = external_buffer<bfloat16>::create({8,160,2,90}, 2, 4);
+external_buffer<bfloat16> ifm_ddr_1 = external_buffer<bfloat16>::create({8,160,2,90}, 0, 6);
+external_buffer<bfloat16> spill_L3_Concat_Buffer_layer_279 = external_buffer<bfloat16>::create({8,160,4,90}, 4, 2);
+external_buffer<bfloat16> l2l3_280_spill = external_buffer<bfloat16>::create({8,160,4,90}, 2, 2);
+external_buffer<bfloat16> l2l3_281_spill = external_buffer<bfloat16>::create({8,160,4,90}, 2, 4);
+external_buffer<bfloat16> l2l3_282_spill = external_buffer<bfloat16>::create({8,160,2,90}, 2, 4);
+external_buffer<bfloat16> const_ifm_ddr = external_buffer<bfloat16>::create({8,160,2,90}, 0, 2);
+external_buffer<bfloat16> l2l3_283_spill = external_buffer<bfloat16>::create({8,160,2,90}, 2, 2);
+external_buffer<bfloat16> l2l3_284_spill = external_buffer<bfloat16>::create({8,160,2,90}, 2, 2);
+external_buffer<bfloat16> l2l3_285_spill = external_buffer<bfloat16>::create({8,160,2,90}, 2, 2);
+external_buffer<bfloat16> spill_L3_Concat_Buffer_layer_287 = external_buffer<bfloat16>::create({8,160,4,90}, 4, 2);
+external_buffer<bfloat16> l2l3_288_spill = external_buffer<bfloat16>::create({8,160,2,90}, 2, 2);
+external_buffer<bfloat16> l2l3_289_spill = external_buffer<bfloat16>::create({8,160,2,90}, 2, 2);
+external_buffer<bfloat16> l2l3_290_spill = external_buffer<bfloat16>::create({8,160,2,90}, 2, 2);
+external_buffer<bfloat16> ofm_ddr_3_l2l3_291_spill = external_buffer<bfloat16>::create({8,160,2,90}, 2, 0);
+external_buffer<bfloat16> spill_L3_Concat_Buffer_layer_292 = external_buffer<bfloat16>::create({8,160,4,90}, 4, 2);
+external_buffer<bfloat16> spill_L3_Concat_Buffer_layer_294 = external_buffer<bfloat16>::create({8,320,5,180}, 4, 2);
+external_buffer<bfloat16> l2l3_295_spill = external_buffer<bfloat16>::create({8,320,2,180}, 2, 2);
+external_buffer<bfloat16> l2l3_296_spill = external_buffer<bfloat16>::create({8,320,2,180}, 2, 2);
+external_buffer<bfloat16> l2l3_297_spill = external_buffer<bfloat16>::create({8,320,1,180}, 2, 4);
+external_buffer<bfloat16> l2l3_298_spill = external_buffer<bfloat16>::create({8,320,1,180}, 2, 2);
+external_buffer<bfloat16> ofm_ddr_4 = external_buffer<bfloat16>::create({8,320,1,180}, 2, 0);
+external_buffer<bfloat16> l2l3_300_spill = external_buffer<bfloat16>::create({8,320,1,180}, 2, 2);
+external_buffer<bfloat16> l2l3_301_spill = external_buffer<bfloat16>::create({8,320,1,180}, 2, 2);
+external_buffer<bfloat16> ofm_ddr_5 = external_buffer<bfloat16>::create({8,320,1,180}, 2, 0);
+
+
+// TG Declarations
+typename mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/3, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>::slice_hcwc8_adf_params params_graph_2 = {
+    .dim_n = 1,
+    .dim_c = 184,
+    .dim_h = 320,
+    .dim_w = 4,
+    .start = 0,
+    .end = 3,
+    .step = 1
+};
+
+mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/3, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>templated_graph_2;
+
+typename mllib_graphs::multi_layer_overlay_buffer_pad</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/524288, /*config.overlay_col_offset*/0>::buffer_pad_param params_graph_3 = {
+    .dim_0 = 320,
+    .dim_1 = 23,
+    .dim_2 = 3,
+    .dim_3 = 8,
+    .dim_0_padded = 320,
+    .dim_1_padded = 23,
+    .dim_2_padded = 8,
+    .dim_3_padded = 8
+};
+
+mllib_graphs::multi_layer_overlay_buffer_pad</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/524288, /*config.overlay_col_offset*/0>templated_graph_3;
+
+typename mllib_graphs::multi_layer_overlay_transpose4d</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>::transpose4d_param params_graph_4 = {
+    .dim_0 = 320,
+    .dim_1 = 23,
+    .dim_2 = 8,
+    .dim_3 = 8,
+    .perm = 10
+};
+
+mllib_graphs::multi_layer_overlay_transpose4d</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>templated_graph_4;
+
+typename mllib_graphs::multi_layer_overlay_buffer_unpad</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>::buffer_unpad_param params_graph_5 = {
+    .dim_0 = 184,
+    .dim_1 = 1,
+    .dim_2 = 320,
+    .dim_3 = 8,
+    .dim_0_unpadded = 180,
+    .dim_1_unpadded = 1,
+    .dim_2_unpadded = 320,
+    .dim_3_unpadded = 8
+};
+
+mllib_graphs::multi_layer_overlay_buffer_unpad</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>templated_graph_5;
+
+typename mllib_graphs::multi_layer_overlay_buffer_unpad</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>::buffer_unpad_param params_graph_17 = {
+    .dim_0 = 48,
+    .dim_1 = 8,
+    .dim_2 = 80,
+    .dim_3 = 8,
+    .dim_0_unpadded = 45,
+    .dim_1_unpadded = 8,
+    .dim_2_unpadded = 80,
+    .dim_3_unpadded = 8
+};
+
+mllib_graphs::multi_layer_overlay_buffer_unpad</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>templated_graph_17;
+
+typename mllib_graphs::multi_layer_overlay_buffer_unpad</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>::buffer_unpad_param params_graph_21 = {
+    .dim_0 = 46,
+    .dim_1 = 9,
+    .dim_2 = 80,
+    .dim_3 = 8,
+    .dim_0_unpadded = 45,
+    .dim_1_unpadded = 9,
+    .dim_2_unpadded = 80,
+    .dim_3_unpadded = 8
+};
+
+mllib_graphs::multi_layer_overlay_buffer_unpad</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>templated_graph_21;
+
+typename mllib_graphs::multi_layer_overlay_transpose4d</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>::transpose4d_param params_graph_25 = {
+    .dim_0 = 23,
+    .dim_1 = 9,
+    .dim_2 = 40,
+    .dim_3 = 8,
+    .perm = 6
+};
+
+mllib_graphs::multi_layer_overlay_transpose4d</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>templated_graph_25;
+
+typename mllib_graphs::multi_layer_overlay_tile</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>::tile_adf_param params_graph_32 = {
+    .i_dim_n = 1,
+    .i_dim_c = 72,
+    .i_dim_h = 1,
+    .i_dim_w = 1,
+    .rep_dim_c = 1,
+    .rep_dim_h = 23,
+    .rep_dim_w = 40
+};
+
+mllib_graphs::multi_layer_overlay_tile</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>templated_graph_32;
+
+typename mllib_graphs::multi_layer_overlay_transpose4d</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>::transpose4d_param params_graph_37 = {
+    .dim_0 = 23,
+    .dim_1 = 15,
+    .dim_2 = 40,
+    .dim_3 = 8,
+    .perm = 6
+};
+
+mllib_graphs::multi_layer_overlay_transpose4d</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>templated_graph_37;
+
+typename mllib_graphs::multi_layer_overlay_tile</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>::tile_adf_param params_graph_44 = {
+    .i_dim_n = 1,
+    .i_dim_c = 120,
+    .i_dim_h = 1,
+    .i_dim_w = 1,
+    .rep_dim_c = 1,
+    .rep_dim_h = 23,
+    .rep_dim_w = 40
+};
+
+mllib_graphs::multi_layer_overlay_tile</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>templated_graph_44;
+
+typename mllib_graphs::multi_layer_overlay_transpose4d</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>::transpose4d_param params_graph_49 = {
+    .dim_0 = 23,
+    .dim_1 = 15,
+    .dim_2 = 40,
+    .dim_3 = 8,
+    .perm = 6
+};
+
+mllib_graphs::multi_layer_overlay_transpose4d</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>templated_graph_49;
+
+typename mllib_graphs::multi_layer_overlay_tile</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>::tile_adf_param params_graph_56 = {
+    .i_dim_n = 1,
+    .i_dim_c = 120,
+    .i_dim_h = 1,
+    .i_dim_w = 1,
+    .rep_dim_c = 1,
+    .rep_dim_h = 23,
+    .rep_dim_w = 40
+};
+
+mllib_graphs::multi_layer_overlay_tile</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>templated_graph_56;
+
+typename mllib_graphs::multi_layer_overlay_buffer_unpad</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>::buffer_unpad_param params_graph_64 = {
+    .dim_0 = 24,
+    .dim_1 = 30,
+    .dim_2 = 40,
+    .dim_3 = 8,
+    .dim_0_unpadded = 23,
+    .dim_1_unpadded = 30,
+    .dim_2_unpadded = 40,
+    .dim_3_unpadded = 8
+};
+
+mllib_graphs::multi_layer_overlay_buffer_unpad</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>templated_graph_64;
+
+typename mllib_graphs::multi_layer_overlay_transpose4d</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>::transpose4d_param params_graph_114 = {
+    .dim_0 = 12,
+    .dim_1 = 60,
+    .dim_2 = 20,
+    .dim_3 = 8,
+    .perm = 6
+};
+
+mllib_graphs::multi_layer_overlay_transpose4d</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>templated_graph_114;
+
+typename mllib_graphs::multi_layer_overlay_tile</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>::tile_adf_param params_graph_121 = {
+    .i_dim_n = 1,
+    .i_dim_c = 480,
+    .i_dim_h = 1,
+    .i_dim_w = 1,
+    .rep_dim_c = 1,
+    .rep_dim_h = 12,
+    .rep_dim_w = 20
+};
+
+mllib_graphs::multi_layer_overlay_tile</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>templated_graph_121;
+
+typename mllib_graphs::multi_layer_overlay_transpose4d</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>::transpose4d_param params_graph_134 = {
+    .dim_0 = 12,
+    .dim_1 = 84,
+    .dim_2 = 20,
+    .dim_3 = 8,
+    .perm = 6
+};
+
+mllib_graphs::multi_layer_overlay_transpose4d</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>templated_graph_134;
+
+typename mllib_graphs::multi_layer_overlay_tile</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>::tile_adf_param params_graph_141 = {
+    .i_dim_n = 1,
+    .i_dim_c = 672,
+    .i_dim_h = 1,
+    .i_dim_w = 1,
+    .rep_dim_c = 1,
+    .rep_dim_h = 12,
+    .rep_dim_w = 20
+};
+
+mllib_graphs::multi_layer_overlay_tile</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>templated_graph_141;
+
+typename mllib_graphs::multi_layer_overlay_transpose4d</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>::transpose4d_param params_graph_154 = {
+    .dim_0 = 12,
+    .dim_1 = 84,
+    .dim_2 = 20,
+    .dim_3 = 8,
+    .perm = 6
+};
+
+mllib_graphs::multi_layer_overlay_transpose4d</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>templated_graph_154;
+
+typename mllib_graphs::multi_layer_overlay_tile</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>::tile_adf_param params_graph_161 = {
+    .i_dim_n = 1,
+    .i_dim_c = 672,
+    .i_dim_h = 1,
+    .i_dim_w = 1,
+    .rep_dim_c = 1,
+    .rep_dim_h = 12,
+    .rep_dim_w = 20
+};
+
+mllib_graphs::multi_layer_overlay_tile</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>templated_graph_161;
+
+typename mllib_graphs::multi_layer_overlay_transpose4d</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>::transpose4d_param params_graph_174 = {
+    .dim_0 = 12,
+    .dim_1 = 120,
+    .dim_2 = 20,
+    .dim_3 = 8,
+    .perm = 6
+};
+
+mllib_graphs::multi_layer_overlay_transpose4d</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>templated_graph_174;
+
+typename mllib_graphs::multi_layer_overlay_tile</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>::tile_adf_param params_graph_181 = {
+    .i_dim_n = 1,
+    .i_dim_c = 960,
+    .i_dim_h = 1,
+    .i_dim_w = 1,
+    .rep_dim_c = 1,
+    .rep_dim_h = 12,
+    .rep_dim_w = 20
+};
+
+mllib_graphs::multi_layer_overlay_tile</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>templated_graph_181;
+
+typename mllib_graphs::multi_layer_overlay_transpose4d</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>::transpose4d_param params_graph_194 = {
+    .dim_0 = 12,
+    .dim_1 = 120,
+    .dim_2 = 20,
+    .dim_3 = 8,
+    .perm = 6
+};
+
+mllib_graphs::multi_layer_overlay_transpose4d</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>templated_graph_194;
+
+typename mllib_graphs::multi_layer_overlay_tile</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>::tile_adf_param params_graph_201 = {
+    .i_dim_n = 1,
+    .i_dim_c = 960,
+    .i_dim_h = 1,
+    .i_dim_w = 1,
+    .rep_dim_c = 1,
+    .rep_dim_h = 12,
+    .rep_dim_w = 20
+};
+
+mllib_graphs::multi_layer_overlay_tile</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>templated_graph_201;
+
+typename mllib_graphs::multi_layer_overlay_transpose4d</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>::transpose4d_param params_graph_209 = {
+    .dim_0 = 12,
+    .dim_1 = 120,
+    .dim_2 = 20,
+    .dim_3 = 8,
+    .perm = 6
+};
+
+mllib_graphs::multi_layer_overlay_transpose4d</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>templated_graph_209;
+
+typename mllib_graphs::multi_layer_overlay_tile</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>::tile_adf_param params_graph_213 = {
+    .i_dim_n = 1,
+    .i_dim_c = 128,
+    .i_dim_h = 1,
+    .i_dim_w = 1,
+    .rep_dim_c = 1,
+    .rep_dim_h = 12,
+    .rep_dim_w = 20
+};
+
+mllib_graphs::multi_layer_overlay_tile</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.overlay_col_offset*/0>templated_graph_213;
+
+typename mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>::slice_hcwc8_adf_params params_graph_215 = {
+    .dim_n = 1,
+    .dim_c = 128,
+    .dim_h = 12,
+    .dim_w = 20,
+    .start = 0,
+    .end = 64,
+    .step = 1
+};
+
+mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>templated_graph_215;
+
+typename mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/2, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>::slice_hcwc8_adf_params params_graph_216 = {
+    .dim_n = 1,
+    .dim_c = 128,
+    .dim_h = 12,
+    .dim_w = 20,
+    .start = 64,
+    .end = 128,
+    .step = 1
+};
+
+mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/2, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>templated_graph_216;
+
+typename mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>::slice_hcwc8_adf_params params_graph_220 = {
+    .dim_n = 1,
+    .dim_c = 128,
+    .dim_h = 12,
+    .dim_w = 20,
+    .start = 64,
+    .end = 128,
+    .step = 1
+};
+
+mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>templated_graph_220;
+
+typename mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/2, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>::slice_hcwc8_adf_params params_graph_223 = {
+    .dim_n = 1,
+    .dim_c = 128,
+    .dim_h = 12,
+    .dim_w = 20,
+    .start = 0,
+    .end = 64,
+    .step = 1
+};
+
+mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/2, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>templated_graph_223;
+
+typename mllib_graphs::multi_layer_overlay_resize</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.opt_mode*/0, /*config.ofm_ddr_dim0*/8, /*config.ofm_ddr_dim1*/40, /*config.ofm_ddr_dim2*/16, /*config.ofm_ddr_dim3*/24, /*config.ofm_ddr_dim2_offset*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>::resize_param params_graph_231 = {
+    .dim_0 = 1,
+    .dim_1 = 128,
+    .dim_2 = 12,
+    .dim_3 = 20,
+    .mode = 1,
+    .nearest_mode = 0,
+    .co_trans_mode = 1,
+    .output_H = 24,
+    .output_W = 40
+};
+
+mllib_graphs::multi_layer_overlay_resize</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.opt_mode*/0, /*config.ofm_ddr_dim0*/8, /*config.ofm_ddr_dim1*/40, /*config.ofm_ddr_dim2*/16, /*config.ofm_ddr_dim3*/24, /*config.ofm_ddr_dim2_offset*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>templated_graph_231;
+
+typename mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/2, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>::slice_hcwc8_adf_params params_graph_232 = {
+    .dim_n = 1,
+    .dim_c = 128,
+    .dim_h = 24,
+    .dim_w = 40,
+    .start = 0,
+    .end = 23,
+    .step = 1
+};
+
+mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/2, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>templated_graph_232;
+
+typename mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>::slice_hcwc8_adf_params params_graph_238 = {
+    .dim_n = 1,
+    .dim_c = 80,
+    .dim_h = 23,
+    .dim_w = 40,
+    .start = 0,
+    .end = 40,
+    .step = 1
+};
+
+mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>templated_graph_238;
+
+typename mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/2, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>::slice_hcwc8_adf_params params_graph_239 = {
+    .dim_n = 1,
+    .dim_c = 80,
+    .dim_h = 23,
+    .dim_w = 40,
+    .start = 40,
+    .end = 80,
+    .step = 1
+};
+
+mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/2, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>templated_graph_239;
+
+typename mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>::slice_hcwc8_adf_params params_graph_243 = {
+    .dim_n = 1,
+    .dim_c = 80,
+    .dim_h = 23,
+    .dim_w = 40,
+    .start = 40,
+    .end = 80,
+    .step = 1
+};
+
+mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>templated_graph_243;
+
+typename mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/2, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>::slice_hcwc8_adf_params params_graph_246 = {
+    .dim_n = 1,
+    .dim_c = 80,
+    .dim_h = 23,
+    .dim_w = 40,
+    .start = 0,
+    .end = 40,
+    .step = 1
+};
+
+mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/2, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>templated_graph_246;
+
+typename mllib_graphs::multi_layer_overlay_resize</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.opt_mode*/0, /*config.ofm_ddr_dim0*/8, /*config.ofm_ddr_dim1*/80, /*config.ofm_ddr_dim2*/10, /*config.ofm_ddr_dim3*/46, /*config.ofm_ddr_dim2_offset*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>::resize_param params_graph_254 = {
+    .dim_0 = 1,
+    .dim_1 = 80,
+    .dim_2 = 23,
+    .dim_3 = 40,
+    .mode = 1,
+    .nearest_mode = 0,
+    .co_trans_mode = 1,
+    .output_H = 46,
+    .output_W = 80
+};
+
+mllib_graphs::multi_layer_overlay_resize</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.opt_mode*/0, /*config.ofm_ddr_dim0*/8, /*config.ofm_ddr_dim1*/80, /*config.ofm_ddr_dim2*/10, /*config.ofm_ddr_dim3*/46, /*config.ofm_ddr_dim2_offset*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>templated_graph_254;
+
+typename mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/2, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>::slice_hcwc8_adf_params params_graph_255 = {
+    .dim_n = 1,
+    .dim_c = 80,
+    .dim_h = 46,
+    .dim_w = 80,
+    .start = 0,
+    .end = 45,
+    .step = 1
+};
+
+mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/2, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>templated_graph_255;
+
+typename mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>::slice_hcwc8_adf_params params_graph_258 = {
+    .dim_n = 1,
+    .dim_c = 40,
+    .dim_h = 45,
+    .dim_w = 80,
+    .start = 0,
+    .end = 20,
+    .step = 1
+};
+
+mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>templated_graph_258;
+
+typename mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/2, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>::slice_hcwc8_adf_params params_graph_259 = {
+    .dim_n = 1,
+    .dim_c = 40,
+    .dim_h = 45,
+    .dim_w = 80,
+    .start = 20,
+    .end = 40,
+    .step = 1
+};
+
+mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/2, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>templated_graph_259;
+
+typename mllib_graphs::multi_layer_overlay_concatc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.wts_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0>::concatc8_param params_graph_260 = {
+    .in1_dim_h = 45,
+    .in1_dim_c = 24,
+    .in1_dim_w = 80,
+    .in2_dim_h = 45,
+    .in2_dim_c = 24,
+    .in2_dim_w = 80,
+    .concat_axis = 1,
+    .num_eff_concat_input0_size = 20,
+    .num_eff_concat_input1_size = 20,
+    .num_eff_concat_input0_start = 0,
+    .num_eff_concat_input1_start = 0
+};
+
+mllib_graphs::multi_layer_overlay_concatc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.wts_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0>templated_graph_260;
+
+typename mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>::slice_hcwc8_adf_params params_graph_263 = {
+    .dim_n = 1,
+    .dim_c = 40,
+    .dim_h = 45,
+    .dim_w = 80,
+    .start = 20,
+    .end = 40,
+    .step = 1
+};
+
+mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>templated_graph_263;
+
+typename mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/2, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>::slice_hcwc8_adf_params params_graph_266 = {
+    .dim_n = 1,
+    .dim_c = 40,
+    .dim_h = 45,
+    .dim_w = 80,
+    .start = 0,
+    .end = 20,
+    .step = 1
+};
+
+mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/2, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>templated_graph_266;
+
+typename mllib_graphs::multi_layer_overlay_concatc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/1, /*config.wts_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0>::concatc8_param params_graph_268 = {
+    .in1_dim_h = 45,
+    .in1_dim_c = 24,
+    .in1_dim_w = 80,
+    .in2_dim_h = 45,
+    .in2_dim_c = 24,
+    .in2_dim_w = 80,
+    .concat_axis = 1,
+    .num_eff_concat_input0_size = 20,
+    .num_eff_concat_input1_size = 20,
+    .num_eff_concat_input0_start = 0,
+    .num_eff_concat_input1_start = 0
+};
+
+mllib_graphs::multi_layer_overlay_concatc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/1, /*config.wts_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0>templated_graph_268;
+
+typename mllib_graphs::multi_layer_overlay_concatc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.wts_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0>::concatc8_param params_graph_273 = {
+    .in1_dim_h = 45,
+    .in1_dim_c = 24,
+    .in1_dim_w = 80,
+    .in2_dim_h = 45,
+    .in2_dim_c = 24,
+    .in2_dim_w = 80,
+    .concat_axis = 1,
+    .num_eff_concat_input0_size = 20,
+    .num_eff_concat_input1_size = 20,
+    .num_eff_concat_input0_start = 0,
+    .num_eff_concat_input1_start = 0
+};
+
+mllib_graphs::multi_layer_overlay_concatc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.wts_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0>templated_graph_273;
+
+typename mllib_graphs::multi_layer_overlay_resize</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.opt_mode*/2, /*config.ofm_ddr_dim0*/8, /*config.ofm_ddr_dim1*/160, /*config.ofm_ddr_dim2*/8, /*config.ofm_ddr_dim3*/90, /*config.ofm_ddr_dim2_offset*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>::resize_param params_graph_274 = {
+    .dim_0 = 1,
+    .dim_1 = 40,
+    .dim_2 = 45,
+    .dim_3 = 80,
+    .mode = 1,
+    .nearest_mode = 0,
+    .co_trans_mode = 1,
+    .output_H = 90,
+    .output_W = 160
+};
+
+mllib_graphs::multi_layer_overlay_resize</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.opt_mode*/2, /*config.ofm_ddr_dim0*/8, /*config.ofm_ddr_dim1*/160, /*config.ofm_ddr_dim2*/8, /*config.ofm_ddr_dim3*/90, /*config.ofm_ddr_dim2_offset*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>templated_graph_274;
+
+typename mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>::slice_hcwc8_adf_params params_graph_277 = {
+    .dim_n = 1,
+    .dim_c = 32,
+    .dim_h = 90,
+    .dim_w = 160,
+    .start = 0,
+    .end = 16,
+    .step = 1
+};
+
+mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>templated_graph_277;
+
+typename mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/2, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>::slice_hcwc8_adf_params params_graph_278 = {
+    .dim_n = 1,
+    .dim_c = 32,
+    .dim_h = 90,
+    .dim_w = 160,
+    .start = 16,
+    .end = 32,
+    .step = 1
+};
+
+mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/2, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>templated_graph_278;
+
+typename mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>::slice_hcwc8_adf_params params_graph_282 = {
+    .dim_n = 1,
+    .dim_c = 32,
+    .dim_h = 90,
+    .dim_w = 160,
+    .start = 16,
+    .end = 32,
+    .step = 1
+};
+
+mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>templated_graph_282;
+
+typename mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/2, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>::slice_hcwc8_adf_params params_graph_285 = {
+    .dim_n = 1,
+    .dim_c = 32,
+    .dim_h = 90,
+    .dim_w = 160,
+    .start = 0,
+    .end = 16,
+    .step = 1
+};
+
+mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/2, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>templated_graph_285;
+
+typename mllib_graphs::multi_layer_overlay_resize</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.opt_mode*/2, /*config.ofm_ddr_dim0*/8, /*config.ofm_ddr_dim1*/320, /*config.ofm_ddr_dim2*/5, /*config.ofm_ddr_dim3*/180, /*config.ofm_ddr_dim2_offset*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>::resize_param params_graph_293 = {
+    .dim_0 = 1,
+    .dim_1 = 32,
+    .dim_2 = 90,
+    .dim_3 = 160,
+    .mode = 1,
+    .nearest_mode = 0,
+    .co_trans_mode = 1,
+    .output_H = 180,
+    .output_W = 320
+};
+
+mllib_graphs::multi_layer_overlay_resize</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.opt_mode*/2, /*config.ofm_ddr_dim0*/8, /*config.ofm_ddr_dim1*/320, /*config.ofm_ddr_dim2*/5, /*config.ofm_ddr_dim3*/180, /*config.ofm_ddr_dim2_offset*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>templated_graph_293;
+
+typename mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>::slice_hcwc8_adf_params params_graph_298 = {
+    .dim_n = 1,
+    .dim_c = 8,
+    .dim_h = 180,
+    .dim_w = 320,
+    .start = 3,
+    .end = 4,
+    .step = 1
+};
+
+mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/0, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>templated_graph_298;
+
+typename mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/2, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>::slice_hcwc8_adf_params params_graph_300 = {
+    .dim_n = 1,
+    .dim_c = 8,
+    .dim_h = 180,
+    .dim_w = 320,
+    .start = 0,
+    .end = 3,
+    .step = 1
+};
+
+mllib_graphs::multi_layer_overlay_slice_hcwc8</*config.dtype*/bfloat16, /*config.kernel_cols*/4, /*config.kernel_rows*/4, /*config.axis*/1, /*config.stack_location*/45696, /*config.tg_stack_size*/2368, /*config.tg_heap_size*/2240, /*config.ifm_ddr_port_logical_index*/2, /*config.ofm_ddr_port_logical_index*/0, /*config.ifm_ofm_buffer_addr*/0, /*config.num_ifm_shim_ch*/2, /*config.num_ofm_shim_ch*/2>templated_graph_300;
+
+shared_buffer<int8_t> ofm_dummy_compareop;
+shared_buffer<bfloat16> ofm_dummy_bf16compareop;
+// Tiling Params Structures
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_1 = {
+  .mk_in0_size = ifmsv_size_1,
+  .mk_in1_size = wtssv_size_1,
+  .mk_out0_size = ofmsv_size_1,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa380, 0xcd80},
+  .read_ifm_mem = ifm_pattern_1,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_1, l1_write_pattern_1),
+  .read_wts_mem = wts_pattern_1,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_1, l1_wts_write_pattern_1),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_1, l1_read_pattern_1),
+  .write_ofm_mem = ofm_pattern_1,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_1,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_6 = {
+  .mk_in0_size = ifmsv_size_6,
+  .mk_in1_size = wtssv_size_6,
+  .mk_out0_size = ofmsv_size_6,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xad80, 0xcd80},
+  .read_ifm_mem = ifm_pattern_6,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_6, l1_write_pattern_6),
+  .read_wts_mem = wts_pattern_6,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_6, l1_wts_write_pattern_6),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_6, l1_read_pattern_6),
+  .write_ofm_mem = ofm_pattern_6,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_6,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_6_1 = {
+  .mk_in0_size = ifm2sv_size_6,
+  .mk_in0_addr = {0x5400, 0x1400},
+  .read_ifm_mem = ifm2_pattern_6,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_7 = {
+  .mk_in0_size = ifmsv_size_7,
+  .mk_in1_size = wtssv_size_7,
+  .mk_out0_size = ofmsv_size_7,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xad80, 0xcd80},
+  .read_ifm_mem = ifm_pattern_7,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_7, l1_write_pattern_7),
+  .read_wts_mem = wts_pattern_7,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_7, l1_wts_write_pattern_7),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_7, l1_read_pattern_7),
+  .write_ofm_mem = ofm_pattern_7,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_7,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_7_1 = {
+  .mk_in0_size = ifm2sv_size_7,
+  .mk_in0_addr = {0x5400, 0x1400},
+  .read_ifm_mem = ifm2_pattern_7,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_8 = {
+  .mk_in0_size = ifmsv_size_8,
+  .mk_in1_size = wtssv_size_8,
+  .mk_out0_size = ofmsv_size_8,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xf6c0, 0xa940},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_8,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_8, l1_write_pattern_8),
+  .read_wts_mem = wts_pattern_8,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_8, l1_wts_write_pattern_8),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_8, l1_read_pattern_8),
+  .write_ofm_mem = ofm_pattern_8,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_8,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_9 = {
+  .mk_in0_size = ifmsv_size_9,
+  .mk_in1_size = wtssv_size_9,
+  .mk_out0_size = ofmsv_size_9,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa700, 0xcd80},
+  .read_ifm_mem = ifm_pattern_9,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_9, l1_write_pattern_9),
+  .read_wts_mem = wts_pattern_9,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_9, l1_wts_write_pattern_9),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_9, l1_read_pattern_9),
+  .write_ofm_mem = ofm_pattern_9,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_9,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_10 = {
+  .mk_in0_size = ifmsv_size_10,
+  .mk_in1_size = wtssv_size_10,
+  .mk_out0_size = ofmsv_size_10,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa380, 0xcd80},
+  .read_ifm_mem = ifm_pattern_10,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_10, l1_write_pattern_10),
+  .read_wts_mem = wts_pattern_10,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_10, l1_wts_write_pattern_10),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_10, l1_read_pattern_10),
+  .write_ofm_mem = ofm_pattern_10,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_10,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_11 = {
+  .mk_in0_size = ifmsv_size_11,
+  .mk_in1_size = wtssv_size_11,
+  .mk_out0_size = ofmsv_size_11,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa700, 0xcd80},
+  .read_ifm_mem = ifm_pattern_11,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_11, l1_write_pattern_11),
+  .read_wts_mem = wts_pattern_11,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_11, l1_wts_write_pattern_11),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_11, l1_read_pattern_11),
+  .write_ofm_mem = ofm_pattern_11,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_11,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_12 = {
+  .mk_in0_size = ifmsv_size_12,
+  .mk_in1_size = wtssv_size_12,
+  .mk_out0_size = ofmsv_size_12,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xaa80, 0xcd80},
+  .read_ifm_mem = ifm_pattern_12,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_12, l1_write_pattern_12),
+  .read_wts_mem = wts_pattern_12,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_12, l1_wts_write_pattern_12),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_12, l1_read_pattern_12),
+  .write_ofm_mem = ofm_pattern_12,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_12,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_12_1 = {
+  .mk_in0_size = ifm2sv_size_12,
+  .mk_in0_addr = {0x6000, 0x2000},
+  .read_ifm_mem = ifm2_pattern_12,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_13 = {
+  .mk_in0_size = ifmsv_size_13,
+  .mk_in1_size = wtssv_size_13,
+  .mk_out0_size = ofmsv_size_13,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xf580, 0xa800},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_13,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_13, l1_write_pattern_13),
+  .read_wts_mem = wts_pattern_13,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_13, l1_wts_write_pattern_13),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_13, l1_read_pattern_13),
+  .write_ofm_mem = ofm_pattern_13,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_13,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_14 = {
+  .mk_in0_size = ifmsv_size_14,
+  .mk_in1_size = wtssv_size_14,
+  .mk_out0_size = ofmsv_size_14,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xed80, 0xa000},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_14,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_14, l1_write_pattern_14),
+  .read_wts_mem = wts_pattern_14,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_14, l1_wts_write_pattern_14),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_14, l1_read_pattern_14),
+  .write_ofm_mem = ofm_pattern_14,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_14,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_14_1 = {
+  .mk_in0_size = ifm2sv_size_14,
+  .mk_in0_addr = {0x2000, 0x6000},
+  .read_ifm_mem = ifm2_pattern_14,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_15 = {
+  .mk_in0_size = ifmsv_size_15,
+  .mk_in1_size = wtssv_size_15,
+  .mk_out0_size = ofmsv_size_15,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xf180, 0xa400},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_15,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_15, l1_write_pattern_15),
+  .read_wts_mem = wts_pattern_15,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_15, l1_wts_write_pattern_15),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_15, l1_read_pattern_15),
+  .write_ofm_mem = ofm_pattern_15,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_15,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_16 = {
+  .mk_in0_size = ifmsv_size_16,
+  .mk_in1_size = wtssv_size_16,
+  .mk_out0_size = ofmsv_size_16,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xf780, 0xaa00},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_16,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_16, l1_write_pattern_16),
+  .read_wts_mem = wts_pattern_16,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_16, l1_wts_write_pattern_16),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_16, l1_read_pattern_16),
+  .write_ofm_mem = ofm_pattern_16,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_16,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_18 = {
+  .mk_in0_size = ifmsv_size_18,
+  .mk_in1_size = wtssv_size_18,
+  .mk_out0_size = ofmsv_size_18,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xed80, 0xa000},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_18,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_18, l1_write_pattern_18),
+  .read_wts_mem = wts_pattern_18,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_18, l1_wts_write_pattern_18),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_18, l1_read_pattern_18),
+  .write_ofm_mem = ofm_pattern_18,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_18,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_19 = {
+  .mk_in0_size = ifmsv_size_19,
+  .mk_in1_size = wtssv_size_19,
+  .mk_out0_size = ofmsv_size_19,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xed80, 0xa000},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_19,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_19, l1_write_pattern_19),
+  .read_wts_mem = wts_pattern_19,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_19, l1_wts_write_pattern_19),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_19, l1_read_pattern_19),
+  .write_ofm_mem = ofm_pattern_19,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_19,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_20 = {
+  .mk_in0_size = ifmsv_size_20,
+  .mk_in1_size = wtssv_size_20,
+  .mk_out0_size = ofmsv_size_20,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xf580, 0xa800},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_20,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_20, l1_write_pattern_20),
+  .read_wts_mem = wts_pattern_20,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_20, l1_wts_write_pattern_20),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_20, l1_read_pattern_20),
+  .write_ofm_mem = ofm_pattern_20,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_20,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_22 = {
+  .mk_in0_size = ifmsv_size_22,
+  .mk_in1_size = wtssv_size_22,
+  .mk_out0_size = ofmsv_size_22,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xf180, 0xa400},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_22,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_22, l1_write_pattern_22),
+  .read_wts_mem = wts_pattern_22,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_22, l1_wts_write_pattern_22),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_22, l1_read_pattern_22),
+  .write_ofm_mem = ofm_pattern_22,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_22,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_22_1 = {
+  .mk_in0_size = ifm2sv_size_22,
+  .mk_in0_addr = {0x2000, 0x6000},
+  .read_ifm_mem = ifm2_pattern_22,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_23 = {
+  .mk_in0_size = ifmsv_size_23,
+  .mk_in1_size = wtssv_size_23,
+  .mk_out0_size = ofmsv_size_23,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xed80, 0xa000},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_23,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_23, l1_write_pattern_23),
+  .read_wts_mem = wts_pattern_23,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_23, l1_wts_write_pattern_23),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_23, l1_read_pattern_23),
+  .write_ofm_mem = ofm_pattern_23,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_23,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_24 = {
+  .mk_in0_size = ifmsv_size_24,
+  .mk_in1_size = wtssv_size_24,
+  .mk_out0_size = ofmsv_size_24,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xf580, 0xa800},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_24,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_24, l1_write_pattern_24),
+  .read_wts_mem = wts_pattern_24,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_24, l1_wts_write_pattern_24),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_24, l1_read_pattern_24),
+  .write_ofm_mem = ofm_pattern_24,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_24,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_26 = {
+  .mk_in0_size = ifmsv_size_26,
+  .mk_in1_size = wtssv_size_26,
+  .mk_out0_size = ofmsv_size_26,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xb080, 0xcd80},
+  .read_ifm_mem = ifm_pattern_26,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_26, l1_write_pattern_26),
+  .read_wts_mem = wts_pattern_26,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_26, l1_wts_write_pattern_26),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_26, l1_read_pattern_26),
+  .write_ofm_mem = ofm_pattern_26,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_26,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_27 = {
+  .mk_in0_size = ifmsv_size_27,
+  .mk_in1_size = wtssv_size_27,
+  .mk_out0_size = ofmsv_size_27,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xd680, 0x8900},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_27,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_27, l1_write_pattern_27),
+  .read_wts_mem = wts_pattern_27,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_27, l1_wts_write_pattern_27),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_27, l1_read_pattern_27),
+  .write_ofm_mem = ofm_pattern_27,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_27,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_28 = {
+  .mk_in0_size = ifmsv_size_28,
+  .mk_in1_size = wtssv_size_28,
+  .mk_out0_size = ofmsv_size_28,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xd180, 0x8400},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_28,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_28, l1_write_pattern_28),
+  .read_wts_mem = wts_pattern_28,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_28, l1_wts_write_pattern_28),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_28, l1_read_pattern_28),
+  .write_ofm_mem = ofm_pattern_28,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_28,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_29 = {
+  .mk_in0_size = ifmsv_size_29,
+  .mk_in1_size = wtssv_size_29,
+  .mk_out0_size = ofmsv_size_29,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xaf80, 0xcd80},
+  .read_ifm_mem = ifm_pattern_29,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_29, l1_write_pattern_29),
+  .read_wts_mem = wts_pattern_29,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_29, l1_wts_write_pattern_29),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_29, l1_read_pattern_29),
+  .write_ofm_mem = ofm_pattern_29,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_29,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_30 = {
+  .mk_in0_size = ifmsv_size_30,
+  .mk_in1_size = wtssv_size_30,
+  .mk_out0_size = ofmsv_size_30,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xb080, 0xcd80},
+  .read_ifm_mem = ifm_pattern_30,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_30, l1_write_pattern_30),
+  .read_wts_mem = wts_pattern_30,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_30, l1_wts_write_pattern_30),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_30, l1_read_pattern_30),
+  .write_ofm_mem = ofm_pattern_30,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_30,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_31 = {
+  .mk_in0_size = ifmsv_size_31,
+  .mk_in1_size = wtssv_size_31,
+  .mk_out0_size = ofmsv_size_31,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xae80, 0xcd80},
+  .read_ifm_mem = ifm_pattern_31,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_31, l1_write_pattern_31),
+  .read_wts_mem = wts_pattern_31,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_31, l1_wts_write_pattern_31),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_31, l1_read_pattern_31),
+  .write_ofm_mem = ofm_pattern_31,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_31,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_33 = {
+  .mk_in0_size = ifmsv_size_33,
+  .mk_in1_size = wtssv_size_33,
+  .mk_out0_size = ofmsv_size_33,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_33,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_33, l1_write_pattern_33),
+  .read_wts_mem = wts_pattern_33,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_33, l1_wts_write_pattern_33),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_33, l1_read_pattern_33),
+  .write_ofm_mem = ofm_pattern_33,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_33,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_33_1 = {
+  .mk_in0_size = ifm2sv_size_33,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_33,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_34 = {
+  .mk_in0_size = ifmsv_size_34,
+  .mk_in1_size = wtssv_size_34,
+  .mk_out0_size = ofmsv_size_34,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe880, 0x9b00},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_34,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_34, l1_write_pattern_34),
+  .read_wts_mem = wts_pattern_34,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_34, l1_wts_write_pattern_34),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_34, l1_read_pattern_34),
+  .write_ofm_mem = ofm_pattern_34,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_34,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_35 = {
+  .mk_in0_size = ifmsv_size_35,
+  .mk_in1_size = wtssv_size_35,
+  .mk_out0_size = ofmsv_size_35,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xed80, 0xa000},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_35,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_35, l1_write_pattern_35),
+  .read_wts_mem = wts_pattern_35,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_35, l1_wts_write_pattern_35),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_35, l1_read_pattern_35),
+  .write_ofm_mem = ofm_pattern_35,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_35,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_36 = {
+  .mk_in0_size = ifmsv_size_36,
+  .mk_in1_size = wtssv_size_36,
+  .mk_out0_size = ofmsv_size_36,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xeb80, 0x9e00},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_36,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_36, l1_write_pattern_36),
+  .read_wts_mem = wts_pattern_36,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_36, l1_wts_write_pattern_36),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_36, l1_read_pattern_36),
+  .write_ofm_mem = ofm_pattern_36,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_36,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_38 = {
+  .mk_in0_size = ifmsv_size_38,
+  .mk_in1_size = wtssv_size_38,
+  .mk_out0_size = ofmsv_size_38,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xb080, 0xcd80},
+  .read_ifm_mem = ifm_pattern_38,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_38, l1_write_pattern_38),
+  .read_wts_mem = wts_pattern_38,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_38, l1_wts_write_pattern_38),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_38, l1_read_pattern_38),
+  .write_ofm_mem = ofm_pattern_38,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_38,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_39 = {
+  .mk_in0_size = ifmsv_size_39,
+  .mk_in1_size = wtssv_size_39,
+  .mk_out0_size = ofmsv_size_39,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xdc80, 0x8f00},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_39,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_39, l1_write_pattern_39),
+  .read_wts_mem = wts_pattern_39,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_39, l1_wts_write_pattern_39),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_39, l1_read_pattern_39),
+  .write_ofm_mem = ofm_pattern_39,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_39,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_40 = {
+  .mk_in0_size = ifmsv_size_40,
+  .mk_in1_size = wtssv_size_40,
+  .mk_out0_size = ofmsv_size_40,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xd180, 0x8400},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_40,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_40, l1_write_pattern_40),
+  .read_wts_mem = wts_pattern_40,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_40, l1_wts_write_pattern_40),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_40, l1_read_pattern_40),
+  .write_ofm_mem = ofm_pattern_40,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_40,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_41 = {
+  .mk_in0_size = ifmsv_size_41,
+  .mk_in1_size = wtssv_size_41,
+  .mk_out0_size = ofmsv_size_41,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xaf80, 0xcd80},
+  .read_ifm_mem = ifm_pattern_41,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_41, l1_write_pattern_41),
+  .read_wts_mem = wts_pattern_41,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_41, l1_wts_write_pattern_41),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_41, l1_read_pattern_41),
+  .write_ofm_mem = ofm_pattern_41,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_41,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_42 = {
+  .mk_in0_size = ifmsv_size_42,
+  .mk_in1_size = wtssv_size_42,
+  .mk_out0_size = ofmsv_size_42,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xb080, 0xcd80},
+  .read_ifm_mem = ifm_pattern_42,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_42, l1_write_pattern_42),
+  .read_wts_mem = wts_pattern_42,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_42, l1_wts_write_pattern_42),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_42, l1_read_pattern_42),
+  .write_ofm_mem = ofm_pattern_42,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_42,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_43 = {
+  .mk_in0_size = ifmsv_size_43,
+  .mk_in1_size = wtssv_size_43,
+  .mk_out0_size = ofmsv_size_43,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xae80, 0xcd80},
+  .read_ifm_mem = ifm_pattern_43,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_43, l1_write_pattern_43),
+  .read_wts_mem = wts_pattern_43,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_43, l1_wts_write_pattern_43),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_43, l1_read_pattern_43),
+  .write_ofm_mem = ofm_pattern_43,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_43,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_45 = {
+  .mk_in0_size = ifmsv_size_45,
+  .mk_in1_size = wtssv_size_45,
+  .mk_out0_size = ofmsv_size_45,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_45,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_45, l1_write_pattern_45),
+  .read_wts_mem = wts_pattern_45,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_45, l1_wts_write_pattern_45),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_45, l1_read_pattern_45),
+  .write_ofm_mem = ofm_pattern_45,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_45,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_45_1 = {
+  .mk_in0_size = ifm2sv_size_45,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_45,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_46 = {
+  .mk_in0_size = ifmsv_size_46,
+  .mk_in1_size = wtssv_size_46,
+  .mk_out0_size = ofmsv_size_46,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe180, 0x9400},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_46,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_46, l1_write_pattern_46),
+  .read_wts_mem = wts_pattern_46,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_46, l1_wts_write_pattern_46),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_46, l1_read_pattern_46),
+  .write_ofm_mem = ofm_pattern_46,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_46,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_46_1 = {
+  .mk_in0_size = ifm2sv_size_46,
+  .mk_in0_addr = {0x2000, 0x6000},
+  .read_ifm_mem = ifm2_pattern_46,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_47 = {
+  .mk_in0_size = ifmsv_size_47,
+  .mk_in1_size = wtssv_size_47,
+  .mk_out0_size = ofmsv_size_47,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xed80, 0xa000},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_47,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_47, l1_write_pattern_47),
+  .read_wts_mem = wts_pattern_47,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_47, l1_wts_write_pattern_47),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_47, l1_read_pattern_47),
+  .write_ofm_mem = ofm_pattern_47,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_47,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_48 = {
+  .mk_in0_size = ifmsv_size_48,
+  .mk_in1_size = wtssv_size_48,
+  .mk_out0_size = ofmsv_size_48,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xeb80, 0x9e00},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_48,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_48, l1_write_pattern_48),
+  .read_wts_mem = wts_pattern_48,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_48, l1_wts_write_pattern_48),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_48, l1_read_pattern_48),
+  .write_ofm_mem = ofm_pattern_48,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_48,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_50 = {
+  .mk_in0_size = ifmsv_size_50,
+  .mk_in1_size = wtssv_size_50,
+  .mk_out0_size = ofmsv_size_50,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xb080, 0xcd80},
+  .read_ifm_mem = ifm_pattern_50,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_50, l1_write_pattern_50),
+  .read_wts_mem = wts_pattern_50,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_50, l1_wts_write_pattern_50),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_50, l1_read_pattern_50),
+  .write_ofm_mem = ofm_pattern_50,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_50,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_51 = {
+  .mk_in0_size = ifmsv_size_51,
+  .mk_in1_size = wtssv_size_51,
+  .mk_out0_size = ofmsv_size_51,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xdc80, 0x8f00},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_51,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_51, l1_write_pattern_51),
+  .read_wts_mem = wts_pattern_51,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_51, l1_wts_write_pattern_51),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_51, l1_read_pattern_51),
+  .write_ofm_mem = ofm_pattern_51,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_51,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_52 = {
+  .mk_in0_size = ifmsv_size_52,
+  .mk_in1_size = wtssv_size_52,
+  .mk_out0_size = ofmsv_size_52,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xd180, 0x8400},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_52,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_52, l1_write_pattern_52),
+  .read_wts_mem = wts_pattern_52,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_52, l1_wts_write_pattern_52),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_52, l1_read_pattern_52),
+  .write_ofm_mem = ofm_pattern_52,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_52,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_53 = {
+  .mk_in0_size = ifmsv_size_53,
+  .mk_in1_size = wtssv_size_53,
+  .mk_out0_size = ofmsv_size_53,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xaf80, 0xcd80},
+  .read_ifm_mem = ifm_pattern_53,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_53, l1_write_pattern_53),
+  .read_wts_mem = wts_pattern_53,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_53, l1_wts_write_pattern_53),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_53, l1_read_pattern_53),
+  .write_ofm_mem = ofm_pattern_53,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_53,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_54 = {
+  .mk_in0_size = ifmsv_size_54,
+  .mk_in1_size = wtssv_size_54,
+  .mk_out0_size = ofmsv_size_54,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xb080, 0xcd80},
+  .read_ifm_mem = ifm_pattern_54,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_54, l1_write_pattern_54),
+  .read_wts_mem = wts_pattern_54,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_54, l1_wts_write_pattern_54),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_54, l1_read_pattern_54),
+  .write_ofm_mem = ofm_pattern_54,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_54,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_55 = {
+  .mk_in0_size = ifmsv_size_55,
+  .mk_in1_size = wtssv_size_55,
+  .mk_out0_size = ofmsv_size_55,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xae80, 0xcd80},
+  .read_ifm_mem = ifm_pattern_55,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_55, l1_write_pattern_55),
+  .read_wts_mem = wts_pattern_55,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_55, l1_wts_write_pattern_55),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_55, l1_read_pattern_55),
+  .write_ofm_mem = ofm_pattern_55,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_55,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_57 = {
+  .mk_in0_size = ifmsv_size_57,
+  .mk_in1_size = wtssv_size_57,
+  .mk_out0_size = ofmsv_size_57,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_57,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_57, l1_write_pattern_57),
+  .read_wts_mem = wts_pattern_57,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_57, l1_wts_write_pattern_57),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_57, l1_read_pattern_57),
+  .write_ofm_mem = ofm_pattern_57,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_57,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_57_1 = {
+  .mk_in0_size = ifm2sv_size_57,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_57,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_58 = {
+  .mk_in0_size = ifmsv_size_58,
+  .mk_in1_size = wtssv_size_58,
+  .mk_out0_size = ofmsv_size_58,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe180, 0x9400},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_58,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_58, l1_write_pattern_58),
+  .read_wts_mem = wts_pattern_58,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_58, l1_wts_write_pattern_58),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_58, l1_read_pattern_58),
+  .write_ofm_mem = ofm_pattern_58,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_58,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_58_1 = {
+  .mk_in0_size = ifm2sv_size_58,
+  .mk_in0_addr = {0x2000, 0x6000},
+  .read_ifm_mem = ifm2_pattern_58,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_59 = {
+  .mk_in0_size = ifmsv_size_59,
+  .mk_in1_size = wtssv_size_59,
+  .mk_out0_size = ofmsv_size_59,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xed80, 0xa000},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_59,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_59, l1_write_pattern_59),
+  .read_wts_mem = wts_pattern_59,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_59, l1_wts_write_pattern_59),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_59, l1_read_pattern_59),
+  .write_ofm_mem = ofm_pattern_59,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_59,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_60 = {
+  .mk_in0_size = ifmsv_size_60,
+  .mk_in1_size = wtssv_size_60,
+  .mk_out0_size = ofmsv_size_60,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa380, 0xcd80},
+  .read_ifm_mem = ifm_pattern_60,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_60, l1_write_pattern_60),
+  .read_wts_mem = wts_pattern_60,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_60, l1_wts_write_pattern_60),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_60, l1_read_pattern_60),
+  .write_ofm_mem = ofm_pattern_60,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_60,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_61 = {
+  .mk_in0_size = ifmsv_size_61,
+  .mk_in1_size = wtssv_size_61,
+  .mk_out0_size = ofmsv_size_61,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa380, 0xcd80},
+  .read_ifm_mem = ifm_pattern_61,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_61, l1_write_pattern_61),
+  .read_wts_mem = wts_pattern_61,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_61, l1_wts_write_pattern_61),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_61, l1_read_pattern_61),
+  .write_ofm_mem = ofm_pattern_61,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_61,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_62 = {
+  .mk_in0_size = ifmsv_size_62,
+  .mk_in1_size = wtssv_size_62,
+  .mk_out0_size = ofmsv_size_62,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa380, 0xcd80},
+  .read_ifm_mem = ifm_pattern_62,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_62, l1_write_pattern_62),
+  .read_wts_mem = wts_pattern_62,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_62, l1_wts_write_pattern_62),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_62, l1_read_pattern_62),
+  .write_ofm_mem = ofm_pattern_62,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_62,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_63 = {
+  .mk_in0_size = ifmsv_size_63,
+  .mk_in1_size = wtssv_size_63,
+  .mk_out0_size = ofmsv_size_63,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_63,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_63, l1_write_pattern_63),
+  .read_wts_mem = wts_pattern_63,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_63, l1_wts_write_pattern_63),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_63, l1_read_pattern_63),
+  .write_ofm_mem = ofm_pattern_63,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_63,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_63_1 = {
+  .mk_in0_size = ifm2sv_size_63,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_63,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_65 = {
+  .mk_in0_size = ifmsv_size_65,
+  .mk_in1_size = wtssv_size_65,
+  .mk_out0_size = ofmsv_size_65,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xeb80, 0x9e00},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_65,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_65, l1_write_pattern_65),
+  .read_wts_mem = wts_pattern_65,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_65, l1_wts_write_pattern_65),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_65, l1_read_pattern_65),
+  .write_ofm_mem = ofm_pattern_65,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_65,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_66 = {
+  .mk_in0_size = ifmsv_size_66,
+  .mk_in1_size = wtssv_size_66,
+  .mk_out0_size = ofmsv_size_66,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa380, 0xcd80},
+  .read_ifm_mem = ifm_pattern_66,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_66, l1_write_pattern_66),
+  .read_wts_mem = wts_pattern_66,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_66, l1_wts_write_pattern_66),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_66, l1_read_pattern_66),
+  .write_ofm_mem = ofm_pattern_66,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_66,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_67 = {
+  .mk_in0_size = ifmsv_size_67,
+  .mk_in1_size = wtssv_size_67,
+  .mk_out0_size = ofmsv_size_67,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa380, 0xcd80},
+  .read_ifm_mem = ifm_pattern_67,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_67, l1_write_pattern_67),
+  .read_wts_mem = wts_pattern_67,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_67, l1_wts_write_pattern_67),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_67, l1_read_pattern_67),
+  .write_ofm_mem = ofm_pattern_67,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_67,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_68 = {
+  .mk_in0_size = ifmsv_size_68,
+  .mk_in1_size = wtssv_size_68,
+  .mk_out0_size = ofmsv_size_68,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa380, 0xcd80},
+  .read_ifm_mem = ifm_pattern_68,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_68, l1_write_pattern_68),
+  .read_wts_mem = wts_pattern_68,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_68, l1_wts_write_pattern_68),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_68, l1_read_pattern_68),
+  .write_ofm_mem = ofm_pattern_68,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_68,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_69 = {
+  .mk_in0_size = ifmsv_size_69,
+  .mk_in1_size = wtssv_size_69,
+  .mk_out0_size = ofmsv_size_69,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_69,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_69, l1_write_pattern_69),
+  .read_wts_mem = wts_pattern_69,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_69, l1_wts_write_pattern_69),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_69, l1_read_pattern_69),
+  .write_ofm_mem = ofm_pattern_69,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_69,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_69_1 = {
+  .mk_in0_size = ifm2sv_size_69,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_69,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_70 = {
+  .mk_in0_size = ifmsv_size_70,
+  .mk_in1_size = wtssv_size_70,
+  .mk_out0_size = ofmsv_size_70,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe180, 0x9400},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_70,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_70, l1_write_pattern_70),
+  .read_wts_mem = wts_pattern_70,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_70, l1_wts_write_pattern_70),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_70, l1_read_pattern_70),
+  .write_ofm_mem = ofm_pattern_70,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_70,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_71 = {
+  .mk_in0_size = ifmsv_size_71,
+  .mk_in1_size = wtssv_size_71,
+  .mk_out0_size = ofmsv_size_71,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe180, 0x9400},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_71,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_71, l1_write_pattern_71),
+  .read_wts_mem = wts_pattern_71,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_71, l1_wts_write_pattern_71),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_71, l1_read_pattern_71),
+  .write_ofm_mem = ofm_pattern_71,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_71,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_72 = {
+  .mk_in0_size = ifmsv_size_72,
+  .mk_in1_size = wtssv_size_72,
+  .mk_out0_size = ofmsv_size_72,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa380, 0xcd80},
+  .read_ifm_mem = ifm_pattern_72,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_72, l1_write_pattern_72),
+  .read_wts_mem = wts_pattern_72,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_72, l1_wts_write_pattern_72),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_72, l1_read_pattern_72),
+  .write_ofm_mem = ofm_pattern_72,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_72,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_73 = {
+  .mk_in0_size = ifmsv_size_73,
+  .mk_in1_size = wtssv_size_73,
+  .mk_out0_size = ofmsv_size_73,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa380, 0xcd80},
+  .read_ifm_mem = ifm_pattern_73,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_73, l1_write_pattern_73),
+  .read_wts_mem = wts_pattern_73,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_73, l1_wts_write_pattern_73),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_73, l1_read_pattern_73),
+  .write_ofm_mem = ofm_pattern_73,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_73,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_74 = {
+  .mk_in0_size = ifmsv_size_74,
+  .mk_in1_size = wtssv_size_74,
+  .mk_out0_size = ofmsv_size_74,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa380, 0xcd80},
+  .read_ifm_mem = ifm_pattern_74,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_74, l1_write_pattern_74),
+  .read_wts_mem = wts_pattern_74,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_74, l1_wts_write_pattern_74),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_74, l1_read_pattern_74),
+  .write_ofm_mem = ofm_pattern_74,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_74,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_75 = {
+  .mk_in0_size = ifmsv_size_75,
+  .mk_in1_size = wtssv_size_75,
+  .mk_out0_size = ofmsv_size_75,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_75,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_75, l1_write_pattern_75),
+  .read_wts_mem = wts_pattern_75,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_75, l1_wts_write_pattern_75),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_75, l1_read_pattern_75),
+  .write_ofm_mem = ofm_pattern_75,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_75,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_75_1 = {
+  .mk_in0_size = ifm2sv_size_75,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_75,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_76 = {
+  .mk_in0_size = ifmsv_size_76,
+  .mk_in1_size = wtssv_size_76,
+  .mk_out0_size = ofmsv_size_76,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xf780, 0xaa00},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_76,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_76, l1_write_pattern_76),
+  .read_wts_mem = wts_pattern_76,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_76, l1_wts_write_pattern_76),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_76, l1_read_pattern_76),
+  .write_ofm_mem = ofm_pattern_76,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_76,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_77 = {
+  .mk_in0_size = ifmsv_size_77,
+  .mk_in1_size = wtssv_size_77,
+  .mk_out0_size = ofmsv_size_77,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa380, 0xcd80},
+  .read_ifm_mem = ifm_pattern_77,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_77, l1_write_pattern_77),
+  .read_wts_mem = wts_pattern_77,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_77, l1_wts_write_pattern_77),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_77, l1_read_pattern_77),
+  .write_ofm_mem = ofm_pattern_77,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_77,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_78 = {
+  .mk_in0_size = ifmsv_size_78,
+  .mk_in1_size = wtssv_size_78,
+  .mk_out0_size = ofmsv_size_78,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa380, 0xcd80},
+  .read_ifm_mem = ifm_pattern_78,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_78, l1_write_pattern_78),
+  .read_wts_mem = wts_pattern_78,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_78, l1_wts_write_pattern_78),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_78, l1_read_pattern_78),
+  .write_ofm_mem = ofm_pattern_78,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_78,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_79 = {
+  .mk_in0_size = ifmsv_size_79,
+  .mk_in1_size = wtssv_size_79,
+  .mk_out0_size = ofmsv_size_79,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa380, 0xcd80},
+  .read_ifm_mem = ifm_pattern_79,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_79, l1_write_pattern_79),
+  .read_wts_mem = wts_pattern_79,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_79, l1_wts_write_pattern_79),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_79, l1_read_pattern_79),
+  .write_ofm_mem = ofm_pattern_79,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_79,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_80 = {
+  .mk_in0_size = ifmsv_size_80,
+  .mk_in1_size = wtssv_size_80,
+  .mk_out0_size = ofmsv_size_80,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_80,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_80, l1_write_pattern_80),
+  .read_wts_mem = wts_pattern_80,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_80, l1_wts_write_pattern_80),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_80, l1_read_pattern_80),
+  .write_ofm_mem = ofm_pattern_80,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_80,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_80_1 = {
+  .mk_in0_size = ifm2sv_size_80,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_80,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_81 = {
+  .mk_in0_size = ifmsv_size_81,
+  .mk_in1_size = wtssv_size_81,
+  .mk_out0_size = ofmsv_size_81,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe780, 0x9a00},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_81,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_81, l1_write_pattern_81),
+  .read_wts_mem = wts_pattern_81,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_81, l1_wts_write_pattern_81),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_81, l1_read_pattern_81),
+  .write_ofm_mem = ofm_pattern_81,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_81,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_81_1 = {
+  .mk_in0_size = ifm2sv_size_81,
+  .mk_in0_addr = {0x2000, 0x6000},
+  .read_ifm_mem = ifm2_pattern_81,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_82 = {
+  .mk_in0_size = ifmsv_size_82,
+  .mk_in1_size = wtssv_size_82,
+  .mk_out0_size = ofmsv_size_82,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xdc80, 0x8f00},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_82,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_82, l1_write_pattern_82),
+  .read_wts_mem = wts_pattern_82,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_82, l1_wts_write_pattern_82),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_82, l1_read_pattern_82),
+  .write_ofm_mem = ofm_pattern_82,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_82,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_83 = {
+  .mk_in0_size = ifmsv_size_83,
+  .mk_in1_size = wtssv_size_83,
+  .mk_out0_size = ofmsv_size_83,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_83,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_83, l1_write_pattern_83),
+  .read_wts_mem = wts_pattern_83,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_83, l1_wts_write_pattern_83),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_83, l1_read_pattern_83),
+  .write_ofm_mem = ofm_pattern_83,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_83,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_84 = {
+  .mk_in0_size = ifmsv_size_84,
+  .mk_in1_size = wtssv_size_84,
+  .mk_out0_size = ofmsv_size_84,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_84,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_84, l1_write_pattern_84),
+  .read_wts_mem = wts_pattern_84,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_84, l1_wts_write_pattern_84),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_84, l1_read_pattern_84),
+  .write_ofm_mem = ofm_pattern_84,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_84,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_85 = {
+  .mk_in0_size = ifmsv_size_85,
+  .mk_in1_size = wtssv_size_85,
+  .mk_out0_size = ofmsv_size_85,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_85,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_85, l1_write_pattern_85),
+  .read_wts_mem = wts_pattern_85,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_85, l1_wts_write_pattern_85),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_85, l1_read_pattern_85),
+  .write_ofm_mem = ofm_pattern_85,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_85,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_86 = {
+  .mk_in0_size = ifmsv_size_86,
+  .mk_in1_size = wtssv_size_86,
+  .mk_out0_size = ofmsv_size_86,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_86,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_86, l1_write_pattern_86),
+  .read_wts_mem = wts_pattern_86,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_86, l1_wts_write_pattern_86),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_86, l1_read_pattern_86),
+  .write_ofm_mem = ofm_pattern_86,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_86,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_86_1 = {
+  .mk_in0_size = ifm2sv_size_86,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_86,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_87 = {
+  .mk_in0_size = ifmsv_size_87,
+  .mk_in1_size = wtssv_size_87,
+  .mk_out0_size = ofmsv_size_87,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xf780, 0xaa00},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_87,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_87, l1_write_pattern_87),
+  .read_wts_mem = wts_pattern_87,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_87, l1_wts_write_pattern_87),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_87, l1_read_pattern_87),
+  .write_ofm_mem = ofm_pattern_87,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_87,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_88 = {
+  .mk_in0_size = ifmsv_size_88,
+  .mk_in1_size = wtssv_size_88,
+  .mk_out0_size = ofmsv_size_88,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_88,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_88, l1_write_pattern_88),
+  .read_wts_mem = wts_pattern_88,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_88, l1_wts_write_pattern_88),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_88, l1_read_pattern_88),
+  .write_ofm_mem = ofm_pattern_88,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_88,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_89 = {
+  .mk_in0_size = ifmsv_size_89,
+  .mk_in1_size = wtssv_size_89,
+  .mk_out0_size = ofmsv_size_89,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_89,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_89, l1_write_pattern_89),
+  .read_wts_mem = wts_pattern_89,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_89, l1_wts_write_pattern_89),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_89, l1_read_pattern_89),
+  .write_ofm_mem = ofm_pattern_89,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_89,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_90 = {
+  .mk_in0_size = ifmsv_size_90,
+  .mk_in1_size = wtssv_size_90,
+  .mk_out0_size = ofmsv_size_90,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_90,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_90, l1_write_pattern_90),
+  .read_wts_mem = wts_pattern_90,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_90, l1_wts_write_pattern_90),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_90, l1_read_pattern_90),
+  .write_ofm_mem = ofm_pattern_90,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_90,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_91 = {
+  .mk_in0_size = ifmsv_size_91,
+  .mk_in1_size = wtssv_size_91,
+  .mk_out0_size = ofmsv_size_91,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_91,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_91, l1_write_pattern_91),
+  .read_wts_mem = wts_pattern_91,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_91, l1_wts_write_pattern_91),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_91, l1_read_pattern_91),
+  .write_ofm_mem = ofm_pattern_91,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_91,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_91_1 = {
+  .mk_in0_size = ifm2sv_size_91,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_91,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_92 = {
+  .mk_in0_size = ifmsv_size_92,
+  .mk_in1_size = wtssv_size_92,
+  .mk_out0_size = ofmsv_size_92,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe580, 0x9800},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_92,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_92, l1_write_pattern_92),
+  .read_wts_mem = wts_pattern_92,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_92, l1_wts_write_pattern_92),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_92, l1_read_pattern_92),
+  .write_ofm_mem = ofm_pattern_92,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_92,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_92_1 = {
+  .mk_in0_size = ifm2sv_size_92,
+  .mk_in0_addr = {0x2000, 0x6000},
+  .read_ifm_mem = ifm2_pattern_92,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_93 = {
+  .mk_in0_size = ifmsv_size_93,
+  .mk_in1_size = wtssv_size_93,
+  .mk_out0_size = ofmsv_size_93,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xdc80, 0x8f00},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_93,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_93, l1_write_pattern_93),
+  .read_wts_mem = wts_pattern_93,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_93, l1_wts_write_pattern_93),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_93, l1_read_pattern_93),
+  .write_ofm_mem = ofm_pattern_93,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_93,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_94 = {
+  .mk_in0_size = ifmsv_size_94,
+  .mk_in1_size = wtssv_size_94,
+  .mk_out0_size = ofmsv_size_94,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_94,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_94, l1_write_pattern_94),
+  .read_wts_mem = wts_pattern_94,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_94, l1_wts_write_pattern_94),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_94, l1_read_pattern_94),
+  .write_ofm_mem = ofm_pattern_94,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_94,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_95 = {
+  .mk_in0_size = ifmsv_size_95,
+  .mk_in1_size = wtssv_size_95,
+  .mk_out0_size = ofmsv_size_95,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_95,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_95, l1_write_pattern_95),
+  .read_wts_mem = wts_pattern_95,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_95, l1_wts_write_pattern_95),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_95, l1_read_pattern_95),
+  .write_ofm_mem = ofm_pattern_95,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_95,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_96 = {
+  .mk_in0_size = ifmsv_size_96,
+  .mk_in1_size = wtssv_size_96,
+  .mk_out0_size = ofmsv_size_96,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_96,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_96, l1_write_pattern_96),
+  .read_wts_mem = wts_pattern_96,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_96, l1_wts_write_pattern_96),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_96, l1_read_pattern_96),
+  .write_ofm_mem = ofm_pattern_96,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_96,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_97 = {
+  .mk_in0_size = ifmsv_size_97,
+  .mk_in1_size = wtssv_size_97,
+  .mk_out0_size = ofmsv_size_97,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_97,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_97, l1_write_pattern_97),
+  .read_wts_mem = wts_pattern_97,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_97, l1_wts_write_pattern_97),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_97, l1_read_pattern_97),
+  .write_ofm_mem = ofm_pattern_97,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_97,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_97_1 = {
+  .mk_in0_size = ifm2sv_size_97,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_97,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_98 = {
+  .mk_in0_size = ifmsv_size_98,
+  .mk_in1_size = wtssv_size_98,
+  .mk_out0_size = ofmsv_size_98,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xf780, 0xaa00},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_98,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_98, l1_write_pattern_98),
+  .read_wts_mem = wts_pattern_98,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_98, l1_wts_write_pattern_98),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_98, l1_read_pattern_98),
+  .write_ofm_mem = ofm_pattern_98,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_98,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_99 = {
+  .mk_in0_size = ifmsv_size_99,
+  .mk_in1_size = wtssv_size_99,
+  .mk_out0_size = ofmsv_size_99,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_99,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_99, l1_write_pattern_99),
+  .read_wts_mem = wts_pattern_99,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_99, l1_wts_write_pattern_99),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_99, l1_read_pattern_99),
+  .write_ofm_mem = ofm_pattern_99,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_99,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_100 = {
+  .mk_in0_size = ifmsv_size_100,
+  .mk_in1_size = wtssv_size_100,
+  .mk_out0_size = ofmsv_size_100,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_100,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_100, l1_write_pattern_100),
+  .read_wts_mem = wts_pattern_100,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_100, l1_wts_write_pattern_100),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_100, l1_read_pattern_100),
+  .write_ofm_mem = ofm_pattern_100,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_100,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_101 = {
+  .mk_in0_size = ifmsv_size_101,
+  .mk_in1_size = wtssv_size_101,
+  .mk_out0_size = ofmsv_size_101,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_101,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_101, l1_write_pattern_101),
+  .read_wts_mem = wts_pattern_101,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_101, l1_wts_write_pattern_101),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_101, l1_read_pattern_101),
+  .write_ofm_mem = ofm_pattern_101,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_101,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_102 = {
+  .mk_in0_size = ifmsv_size_102,
+  .mk_in1_size = wtssv_size_102,
+  .mk_out0_size = ofmsv_size_102,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_102,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_102, l1_write_pattern_102),
+  .read_wts_mem = wts_pattern_102,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_102, l1_wts_write_pattern_102),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_102, l1_read_pattern_102),
+  .write_ofm_mem = ofm_pattern_102,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_102,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_102_1 = {
+  .mk_in0_size = ifm2sv_size_102,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_102,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_103 = {
+  .mk_in0_size = ifmsv_size_103,
+  .mk_in1_size = wtssv_size_103,
+  .mk_out0_size = ofmsv_size_103,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe580, 0x9800},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_103,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_103, l1_write_pattern_103),
+  .read_wts_mem = wts_pattern_103,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_103, l1_wts_write_pattern_103),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_103, l1_read_pattern_103),
+  .write_ofm_mem = ofm_pattern_103,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_103,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_103_1 = {
+  .mk_in0_size = ifm2sv_size_103,
+  .mk_in0_addr = {0x2000, 0x6000},
+  .read_ifm_mem = ifm2_pattern_103,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_104 = {
+  .mk_in0_size = ifmsv_size_104,
+  .mk_in1_size = wtssv_size_104,
+  .mk_out0_size = ofmsv_size_104,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe180, 0x9400},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_104,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_104, l1_write_pattern_104),
+  .read_wts_mem = wts_pattern_104,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_104, l1_wts_write_pattern_104),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_104, l1_read_pattern_104),
+  .write_ofm_mem = ofm_pattern_104,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_104,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_105 = {
+  .mk_in0_size = ifmsv_size_105,
+  .mk_in1_size = wtssv_size_105,
+  .mk_out0_size = ofmsv_size_105,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa380, 0xcd80},
+  .read_ifm_mem = ifm_pattern_105,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_105, l1_write_pattern_105),
+  .read_wts_mem = wts_pattern_105,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_105, l1_wts_write_pattern_105),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_105, l1_read_pattern_105),
+  .write_ofm_mem = ofm_pattern_105,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_105,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_106 = {
+  .mk_in0_size = ifmsv_size_106,
+  .mk_in1_size = wtssv_size_106,
+  .mk_out0_size = ofmsv_size_106,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa380, 0xcd80},
+  .read_ifm_mem = ifm_pattern_106,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_106, l1_write_pattern_106),
+  .read_wts_mem = wts_pattern_106,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_106, l1_wts_write_pattern_106),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_106, l1_read_pattern_106),
+  .write_ofm_mem = ofm_pattern_106,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_106,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_107 = {
+  .mk_in0_size = ifmsv_size_107,
+  .mk_in1_size = wtssv_size_107,
+  .mk_out0_size = ofmsv_size_107,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa380, 0xcd80},
+  .read_ifm_mem = ifm_pattern_107,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_107, l1_write_pattern_107),
+  .read_wts_mem = wts_pattern_107,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_107, l1_wts_write_pattern_107),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_107, l1_read_pattern_107),
+  .write_ofm_mem = ofm_pattern_107,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_107,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_108 = {
+  .mk_in0_size = ifmsv_size_108,
+  .mk_in1_size = wtssv_size_108,
+  .mk_out0_size = ofmsv_size_108,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_108,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_108, l1_write_pattern_108),
+  .read_wts_mem = wts_pattern_108,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_108, l1_wts_write_pattern_108),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_108, l1_read_pattern_108),
+  .write_ofm_mem = ofm_pattern_108,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_108,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_108_1 = {
+  .mk_in0_size = ifm2sv_size_108,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_108,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_109 = {
+  .mk_in0_size = ifmsv_size_109,
+  .mk_in1_size = wtssv_size_109,
+  .mk_out0_size = ofmsv_size_109,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xf780, 0xaa00},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_109,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_109, l1_write_pattern_109),
+  .read_wts_mem = wts_pattern_109,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_109, l1_wts_write_pattern_109),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_109, l1_read_pattern_109),
+  .write_ofm_mem = ofm_pattern_109,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_109,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_110 = {
+  .mk_in0_size = ifmsv_size_110,
+  .mk_in1_size = wtssv_size_110,
+  .mk_out0_size = ofmsv_size_110,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa380, 0xcd80},
+  .read_ifm_mem = ifm_pattern_110,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_110, l1_write_pattern_110),
+  .read_wts_mem = wts_pattern_110,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_110, l1_wts_write_pattern_110),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_110, l1_read_pattern_110),
+  .write_ofm_mem = ofm_pattern_110,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_110,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_111 = {
+  .mk_in0_size = ifmsv_size_111,
+  .mk_in1_size = wtssv_size_111,
+  .mk_out0_size = ofmsv_size_111,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa380, 0xcd80},
+  .read_ifm_mem = ifm_pattern_111,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_111, l1_write_pattern_111),
+  .read_wts_mem = wts_pattern_111,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_111, l1_wts_write_pattern_111),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_111, l1_read_pattern_111),
+  .write_ofm_mem = ofm_pattern_111,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_111,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_112 = {
+  .mk_in0_size = ifmsv_size_112,
+  .mk_in1_size = wtssv_size_112,
+  .mk_out0_size = ofmsv_size_112,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa380, 0xcd80},
+  .read_ifm_mem = ifm_pattern_112,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_112, l1_write_pattern_112),
+  .read_wts_mem = wts_pattern_112,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_112, l1_wts_write_pattern_112),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_112, l1_read_pattern_112),
+  .write_ofm_mem = ofm_pattern_112,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_112,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_113 = {
+  .mk_in0_size = ifmsv_size_113,
+  .mk_in1_size = wtssv_size_113,
+  .mk_out0_size = ofmsv_size_113,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_113,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_113, l1_write_pattern_113),
+  .read_wts_mem = wts_pattern_113,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_113, l1_wts_write_pattern_113),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_113, l1_read_pattern_113),
+  .write_ofm_mem = ofm_pattern_113,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_113,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_113_1 = {
+  .mk_in0_size = ifm2sv_size_113,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_113,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_115 = {
+  .mk_in0_size = ifmsv_size_115,
+  .mk_in1_size = wtssv_size_115,
+  .mk_out0_size = ofmsv_size_115,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xb000, 0xcd80},
+  .read_ifm_mem = ifm_pattern_115,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_115, l1_write_pattern_115),
+  .read_wts_mem = wts_pattern_115,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_115, l1_wts_write_pattern_115),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_115, l1_read_pattern_115),
+  .write_ofm_mem = ofm_pattern_115,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_115,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_116 = {
+  .mk_in0_size = ifmsv_size_116,
+  .mk_in1_size = wtssv_size_116,
+  .mk_out0_size = ofmsv_size_116,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xd500, 0x8780},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_116,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_116, l1_write_pattern_116),
+  .read_wts_mem = wts_pattern_116,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_116, l1_wts_write_pattern_116),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_116, l1_read_pattern_116),
+  .write_ofm_mem = ofm_pattern_116,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_116,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_117 = {
+  .mk_in0_size = ifmsv_size_117,
+  .mk_in1_size = wtssv_size_117,
+  .mk_out0_size = ofmsv_size_117,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xd500, 0x8780},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_117,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_117, l1_write_pattern_117),
+  .read_wts_mem = wts_pattern_117,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_117, l1_wts_write_pattern_117),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_117, l1_read_pattern_117),
+  .write_ofm_mem = ofm_pattern_117,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_117,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_118 = {
+  .mk_in0_size = ifmsv_size_118,
+  .mk_in1_size = wtssv_size_118,
+  .mk_out0_size = ofmsv_size_118,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xaf80, 0xcd80},
+  .read_ifm_mem = ifm_pattern_118,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_118, l1_write_pattern_118),
+  .read_wts_mem = wts_pattern_118,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_118, l1_wts_write_pattern_118),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_118, l1_read_pattern_118),
+  .write_ofm_mem = ofm_pattern_118,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_118,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_119 = {
+  .mk_in0_size = ifmsv_size_119,
+  .mk_in1_size = wtssv_size_119,
+  .mk_out0_size = ofmsv_size_119,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xb080, 0xcd80},
+  .read_ifm_mem = ifm_pattern_119,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_119, l1_write_pattern_119),
+  .read_wts_mem = wts_pattern_119,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_119, l1_wts_write_pattern_119),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_119, l1_read_pattern_119),
+  .write_ofm_mem = ofm_pattern_119,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_119,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_120 = {
+  .mk_in0_size = ifmsv_size_120,
+  .mk_in1_size = wtssv_size_120,
+  .mk_out0_size = ofmsv_size_120,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xae80, 0xcd80},
+  .read_ifm_mem = ifm_pattern_120,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_120, l1_write_pattern_120),
+  .read_wts_mem = wts_pattern_120,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_120, l1_wts_write_pattern_120),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_120, l1_read_pattern_120),
+  .write_ofm_mem = ofm_pattern_120,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_120,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_122 = {
+  .mk_in0_size = ifmsv_size_122,
+  .mk_in1_size = wtssv_size_122,
+  .mk_out0_size = ofmsv_size_122,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_122,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_122, l1_write_pattern_122),
+  .read_wts_mem = wts_pattern_122,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_122, l1_wts_write_pattern_122),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_122, l1_read_pattern_122),
+  .write_ofm_mem = ofm_pattern_122,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_122,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_122_1 = {
+  .mk_in0_size = ifm2sv_size_122,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_122,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_123 = {
+  .mk_in0_size = ifmsv_size_123,
+  .mk_in1_size = wtssv_size_123,
+  .mk_out0_size = ofmsv_size_123,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe580, 0x9800},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_123,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_123, l1_write_pattern_123),
+  .read_wts_mem = wts_pattern_123,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_123, l1_wts_write_pattern_123),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_123, l1_read_pattern_123),
+  .write_ofm_mem = ofm_pattern_123,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_123,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_124 = {
+  .mk_in0_size = ifmsv_size_124,
+  .mk_in1_size = wtssv_size_124,
+  .mk_out0_size = ofmsv_size_124,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xdd80, 0x9000},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_124,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_124, l1_write_pattern_124),
+  .read_wts_mem = wts_pattern_124,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_124, l1_wts_write_pattern_124),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_124, l1_read_pattern_124),
+  .write_ofm_mem = ofm_pattern_124,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_124,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_125 = {
+  .mk_in0_size = ifmsv_size_125,
+  .mk_in1_size = wtssv_size_125,
+  .mk_out0_size = ofmsv_size_125,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_125,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_125, l1_write_pattern_125),
+  .read_wts_mem = wts_pattern_125,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_125, l1_wts_write_pattern_125),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_125, l1_read_pattern_125),
+  .write_ofm_mem = ofm_pattern_125,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_125,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_126 = {
+  .mk_in0_size = ifmsv_size_126,
+  .mk_in1_size = wtssv_size_126,
+  .mk_out0_size = ofmsv_size_126,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_126,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_126, l1_write_pattern_126),
+  .read_wts_mem = wts_pattern_126,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_126, l1_wts_write_pattern_126),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_126, l1_read_pattern_126),
+  .write_ofm_mem = ofm_pattern_126,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_126,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_127 = {
+  .mk_in0_size = ifmsv_size_127,
+  .mk_in1_size = wtssv_size_127,
+  .mk_out0_size = ofmsv_size_127,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_127,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_127, l1_write_pattern_127),
+  .read_wts_mem = wts_pattern_127,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_127, l1_wts_write_pattern_127),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_127, l1_read_pattern_127),
+  .write_ofm_mem = ofm_pattern_127,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_127,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_128 = {
+  .mk_in0_size = ifmsv_size_128,
+  .mk_in1_size = wtssv_size_128,
+  .mk_out0_size = ofmsv_size_128,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_128,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_128, l1_write_pattern_128),
+  .read_wts_mem = wts_pattern_128,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_128, l1_wts_write_pattern_128),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_128, l1_read_pattern_128),
+  .write_ofm_mem = ofm_pattern_128,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_128,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_128_1 = {
+  .mk_in0_size = ifm2sv_size_128,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_128,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_129 = {
+  .mk_in0_size = ifmsv_size_129,
+  .mk_in1_size = wtssv_size_129,
+  .mk_out0_size = ofmsv_size_129,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xf780, 0xaa00},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_129,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_129, l1_write_pattern_129),
+  .read_wts_mem = wts_pattern_129,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_129, l1_wts_write_pattern_129),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_129, l1_read_pattern_129),
+  .write_ofm_mem = ofm_pattern_129,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_129,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_130 = {
+  .mk_in0_size = ifmsv_size_130,
+  .mk_in1_size = wtssv_size_130,
+  .mk_out0_size = ofmsv_size_130,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_130,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_130, l1_write_pattern_130),
+  .read_wts_mem = wts_pattern_130,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_130, l1_wts_write_pattern_130),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_130, l1_read_pattern_130),
+  .write_ofm_mem = ofm_pattern_130,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_130,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_131 = {
+  .mk_in0_size = ifmsv_size_131,
+  .mk_in1_size = wtssv_size_131,
+  .mk_out0_size = ofmsv_size_131,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_131,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_131, l1_write_pattern_131),
+  .read_wts_mem = wts_pattern_131,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_131, l1_wts_write_pattern_131),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_131, l1_read_pattern_131),
+  .write_ofm_mem = ofm_pattern_131,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_131,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_132 = {
+  .mk_in0_size = ifmsv_size_132,
+  .mk_in1_size = wtssv_size_132,
+  .mk_out0_size = ofmsv_size_132,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_132,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_132, l1_write_pattern_132),
+  .read_wts_mem = wts_pattern_132,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_132, l1_wts_write_pattern_132),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_132, l1_read_pattern_132),
+  .write_ofm_mem = ofm_pattern_132,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_132,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_133 = {
+  .mk_in0_size = ifmsv_size_133,
+  .mk_in1_size = wtssv_size_133,
+  .mk_out0_size = ofmsv_size_133,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_133,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_133, l1_write_pattern_133),
+  .read_wts_mem = wts_pattern_133,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_133, l1_wts_write_pattern_133),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_133, l1_read_pattern_133),
+  .write_ofm_mem = ofm_pattern_133,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_133,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_133_1 = {
+  .mk_in0_size = ifm2sv_size_133,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_133,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_135 = {
+  .mk_in0_size = ifmsv_size_135,
+  .mk_in1_size = wtssv_size_135,
+  .mk_out0_size = ofmsv_size_135,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xaf00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_135,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_135, l1_write_pattern_135),
+  .read_wts_mem = wts_pattern_135,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_135, l1_wts_write_pattern_135),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_135, l1_read_pattern_135),
+  .write_ofm_mem = ofm_pattern_135,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_135,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_136 = {
+  .mk_in0_size = ifmsv_size_136,
+  .mk_in1_size = wtssv_size_136,
+  .mk_out0_size = ofmsv_size_136,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xd380, 0x8600},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_136,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_136, l1_write_pattern_136),
+  .read_wts_mem = wts_pattern_136,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_136, l1_wts_write_pattern_136),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_136, l1_read_pattern_136),
+  .write_ofm_mem = ofm_pattern_136,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_136,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_137 = {
+  .mk_in0_size = ifmsv_size_137,
+  .mk_in1_size = wtssv_size_137,
+  .mk_out0_size = ofmsv_size_137,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe280, 0x9500},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_137,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_137, l1_write_pattern_137),
+  .read_wts_mem = wts_pattern_137,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_137, l1_wts_write_pattern_137),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_137, l1_read_pattern_137),
+  .write_ofm_mem = ofm_pattern_137,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_137,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_138 = {
+  .mk_in0_size = ifmsv_size_138,
+  .mk_in1_size = wtssv_size_138,
+  .mk_out0_size = ofmsv_size_138,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xaf80, 0xcd80},
+  .read_ifm_mem = ifm_pattern_138,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_138, l1_write_pattern_138),
+  .read_wts_mem = wts_pattern_138,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_138, l1_wts_write_pattern_138),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_138, l1_read_pattern_138),
+  .write_ofm_mem = ofm_pattern_138,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_138,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_139 = {
+  .mk_in0_size = ifmsv_size_139,
+  .mk_in1_size = wtssv_size_139,
+  .mk_out0_size = ofmsv_size_139,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xb080, 0xcd80},
+  .read_ifm_mem = ifm_pattern_139,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_139, l1_write_pattern_139),
+  .read_wts_mem = wts_pattern_139,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_139, l1_wts_write_pattern_139),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_139, l1_read_pattern_139),
+  .write_ofm_mem = ofm_pattern_139,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_139,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_140 = {
+  .mk_in0_size = ifmsv_size_140,
+  .mk_in1_size = wtssv_size_140,
+  .mk_out0_size = ofmsv_size_140,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xae80, 0xcd80},
+  .read_ifm_mem = ifm_pattern_140,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_140, l1_write_pattern_140),
+  .read_wts_mem = wts_pattern_140,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_140, l1_wts_write_pattern_140),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_140, l1_read_pattern_140),
+  .write_ofm_mem = ofm_pattern_140,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_140,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_142 = {
+  .mk_in0_size = ifmsv_size_142,
+  .mk_in1_size = wtssv_size_142,
+  .mk_out0_size = ofmsv_size_142,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_142,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_142, l1_write_pattern_142),
+  .read_wts_mem = wts_pattern_142,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_142, l1_wts_write_pattern_142),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_142, l1_read_pattern_142),
+  .write_ofm_mem = ofm_pattern_142,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_142,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_142_1 = {
+  .mk_in0_size = ifm2sv_size_142,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_142,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_143 = {
+  .mk_in0_size = ifmsv_size_143,
+  .mk_in1_size = wtssv_size_143,
+  .mk_out0_size = ofmsv_size_143,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe580, 0x9800},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_143,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_143, l1_write_pattern_143),
+  .read_wts_mem = wts_pattern_143,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_143, l1_wts_write_pattern_143),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_143, l1_read_pattern_143),
+  .write_ofm_mem = ofm_pattern_143,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_143,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_143_1 = {
+  .mk_in0_size = ifm2sv_size_143,
+  .mk_in0_addr = {0x2000, 0x6000},
+  .read_ifm_mem = ifm2_pattern_143,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_144 = {
+  .mk_in0_size = ifmsv_size_144,
+  .mk_in1_size = wtssv_size_144,
+  .mk_out0_size = ofmsv_size_144,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xdd80, 0x9000},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_144,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_144, l1_write_pattern_144),
+  .read_wts_mem = wts_pattern_144,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_144, l1_wts_write_pattern_144),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_144, l1_read_pattern_144),
+  .write_ofm_mem = ofm_pattern_144,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_144,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_145 = {
+  .mk_in0_size = ifmsv_size_145,
+  .mk_in1_size = wtssv_size_145,
+  .mk_out0_size = ofmsv_size_145,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_145,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_145, l1_write_pattern_145),
+  .read_wts_mem = wts_pattern_145,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_145, l1_wts_write_pattern_145),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_145, l1_read_pattern_145),
+  .write_ofm_mem = ofm_pattern_145,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_145,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_146 = {
+  .mk_in0_size = ifmsv_size_146,
+  .mk_in1_size = wtssv_size_146,
+  .mk_out0_size = ofmsv_size_146,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_146,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_146, l1_write_pattern_146),
+  .read_wts_mem = wts_pattern_146,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_146, l1_wts_write_pattern_146),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_146, l1_read_pattern_146),
+  .write_ofm_mem = ofm_pattern_146,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_146,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_147 = {
+  .mk_in0_size = ifmsv_size_147,
+  .mk_in1_size = wtssv_size_147,
+  .mk_out0_size = ofmsv_size_147,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_147,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_147, l1_write_pattern_147),
+  .read_wts_mem = wts_pattern_147,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_147, l1_wts_write_pattern_147),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_147, l1_read_pattern_147),
+  .write_ofm_mem = ofm_pattern_147,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_147,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_148 = {
+  .mk_in0_size = ifmsv_size_148,
+  .mk_in1_size = wtssv_size_148,
+  .mk_out0_size = ofmsv_size_148,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_148,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_148, l1_write_pattern_148),
+  .read_wts_mem = wts_pattern_148,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_148, l1_wts_write_pattern_148),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_148, l1_read_pattern_148),
+  .write_ofm_mem = ofm_pattern_148,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_148,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_148_1 = {
+  .mk_in0_size = ifm2sv_size_148,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_148,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_149 = {
+  .mk_in0_size = ifmsv_size_149,
+  .mk_in1_size = wtssv_size_149,
+  .mk_out0_size = ofmsv_size_149,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xf580, 0xa800},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_149,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_149, l1_write_pattern_149),
+  .read_wts_mem = wts_pattern_149,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_149, l1_wts_write_pattern_149),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_149, l1_read_pattern_149),
+  .write_ofm_mem = ofm_pattern_149,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_149,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_150 = {
+  .mk_in0_size = ifmsv_size_150,
+  .mk_in1_size = wtssv_size_150,
+  .mk_out0_size = ofmsv_size_150,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_150,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_150, l1_write_pattern_150),
+  .read_wts_mem = wts_pattern_150,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_150, l1_wts_write_pattern_150),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_150, l1_read_pattern_150),
+  .write_ofm_mem = ofm_pattern_150,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_150,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_151 = {
+  .mk_in0_size = ifmsv_size_151,
+  .mk_in1_size = wtssv_size_151,
+  .mk_out0_size = ofmsv_size_151,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_151,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_151, l1_write_pattern_151),
+  .read_wts_mem = wts_pattern_151,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_151, l1_wts_write_pattern_151),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_151, l1_read_pattern_151),
+  .write_ofm_mem = ofm_pattern_151,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_151,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_152 = {
+  .mk_in0_size = ifmsv_size_152,
+  .mk_in1_size = wtssv_size_152,
+  .mk_out0_size = ofmsv_size_152,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_152,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_152, l1_write_pattern_152),
+  .read_wts_mem = wts_pattern_152,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_152, l1_wts_write_pattern_152),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_152, l1_read_pattern_152),
+  .write_ofm_mem = ofm_pattern_152,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_152,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_153 = {
+  .mk_in0_size = ifmsv_size_153,
+  .mk_in1_size = wtssv_size_153,
+  .mk_out0_size = ofmsv_size_153,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_153,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_153, l1_write_pattern_153),
+  .read_wts_mem = wts_pattern_153,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_153, l1_wts_write_pattern_153),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_153, l1_read_pattern_153),
+  .write_ofm_mem = ofm_pattern_153,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_153,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_153_1 = {
+  .mk_in0_size = ifm2sv_size_153,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_153,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_155 = {
+  .mk_in0_size = ifmsv_size_155,
+  .mk_in1_size = wtssv_size_155,
+  .mk_out0_size = ofmsv_size_155,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xaf00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_155,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_155, l1_write_pattern_155),
+  .read_wts_mem = wts_pattern_155,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_155, l1_wts_write_pattern_155),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_155, l1_read_pattern_155),
+  .write_ofm_mem = ofm_pattern_155,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_155,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_156 = {
+  .mk_in0_size = ifmsv_size_156,
+  .mk_in1_size = wtssv_size_156,
+  .mk_out0_size = ofmsv_size_156,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xd380, 0x8600},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_156,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_156, l1_write_pattern_156),
+  .read_wts_mem = wts_pattern_156,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_156, l1_wts_write_pattern_156),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_156, l1_read_pattern_156),
+  .write_ofm_mem = ofm_pattern_156,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_156,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_157 = {
+  .mk_in0_size = ifmsv_size_157,
+  .mk_in1_size = wtssv_size_157,
+  .mk_out0_size = ofmsv_size_157,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe280, 0x9500},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_157,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_157, l1_write_pattern_157),
+  .read_wts_mem = wts_pattern_157,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_157, l1_wts_write_pattern_157),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_157, l1_read_pattern_157),
+  .write_ofm_mem = ofm_pattern_157,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_157,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_158 = {
+  .mk_in0_size = ifmsv_size_158,
+  .mk_in1_size = wtssv_size_158,
+  .mk_out0_size = ofmsv_size_158,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xaf80, 0xcd80},
+  .read_ifm_mem = ifm_pattern_158,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_158, l1_write_pattern_158),
+  .read_wts_mem = wts_pattern_158,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_158, l1_wts_write_pattern_158),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_158, l1_read_pattern_158),
+  .write_ofm_mem = ofm_pattern_158,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_158,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_159 = {
+  .mk_in0_size = ifmsv_size_159,
+  .mk_in1_size = wtssv_size_159,
+  .mk_out0_size = ofmsv_size_159,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xb080, 0xcd80},
+  .read_ifm_mem = ifm_pattern_159,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_159, l1_write_pattern_159),
+  .read_wts_mem = wts_pattern_159,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_159, l1_wts_write_pattern_159),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_159, l1_read_pattern_159),
+  .write_ofm_mem = ofm_pattern_159,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_159,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_160 = {
+  .mk_in0_size = ifmsv_size_160,
+  .mk_in1_size = wtssv_size_160,
+  .mk_out0_size = ofmsv_size_160,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xae80, 0xcd80},
+  .read_ifm_mem = ifm_pattern_160,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_160, l1_write_pattern_160),
+  .read_wts_mem = wts_pattern_160,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_160, l1_wts_write_pattern_160),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_160, l1_read_pattern_160),
+  .write_ofm_mem = ofm_pattern_160,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_160,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_162 = {
+  .mk_in0_size = ifmsv_size_162,
+  .mk_in1_size = wtssv_size_162,
+  .mk_out0_size = ofmsv_size_162,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_162,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_162, l1_write_pattern_162),
+  .read_wts_mem = wts_pattern_162,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_162, l1_wts_write_pattern_162),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_162, l1_read_pattern_162),
+  .write_ofm_mem = ofm_pattern_162,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_162,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_162_1 = {
+  .mk_in0_size = ifm2sv_size_162,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_162,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_163 = {
+  .mk_in0_size = ifmsv_size_163,
+  .mk_in1_size = wtssv_size_163,
+  .mk_out0_size = ofmsv_size_163,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe180, 0x9400},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_163,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_163, l1_write_pattern_163),
+  .read_wts_mem = wts_pattern_163,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_163, l1_wts_write_pattern_163),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_163, l1_read_pattern_163),
+  .write_ofm_mem = ofm_pattern_163,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_163,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_164 = {
+  .mk_in0_size = ifmsv_size_164,
+  .mk_in1_size = wtssv_size_164,
+  .mk_out0_size = ofmsv_size_164,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe180, 0x9400},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_164,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_164, l1_write_pattern_164),
+  .read_wts_mem = wts_pattern_164,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_164, l1_wts_write_pattern_164),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_164, l1_read_pattern_164),
+  .write_ofm_mem = ofm_pattern_164,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_164,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_165 = {
+  .mk_in0_size = ifmsv_size_165,
+  .mk_in1_size = wtssv_size_165,
+  .mk_out0_size = ofmsv_size_165,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa600, 0xcd80},
+  .read_ifm_mem = ifm_pattern_165,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_165, l1_write_pattern_165),
+  .read_wts_mem = wts_pattern_165,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_165, l1_wts_write_pattern_165),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_165, l1_read_pattern_165),
+  .write_ofm_mem = ofm_pattern_165,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_165,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_166 = {
+  .mk_in0_size = ifmsv_size_166,
+  .mk_in1_size = wtssv_size_166,
+  .mk_out0_size = ofmsv_size_166,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa600, 0xcd80},
+  .read_ifm_mem = ifm_pattern_166,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_166, l1_write_pattern_166),
+  .read_wts_mem = wts_pattern_166,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_166, l1_wts_write_pattern_166),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_166, l1_read_pattern_166),
+  .write_ofm_mem = ofm_pattern_166,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_166,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_167 = {
+  .mk_in0_size = ifmsv_size_167,
+  .mk_in1_size = wtssv_size_167,
+  .mk_out0_size = ofmsv_size_167,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa600, 0xcd80},
+  .read_ifm_mem = ifm_pattern_167,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_167, l1_write_pattern_167),
+  .read_wts_mem = wts_pattern_167,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_167, l1_wts_write_pattern_167),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_167, l1_read_pattern_167),
+  .write_ofm_mem = ofm_pattern_167,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_167,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_168 = {
+  .mk_in0_size = ifmsv_size_168,
+  .mk_in1_size = wtssv_size_168,
+  .mk_out0_size = ofmsv_size_168,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_168,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_168, l1_write_pattern_168),
+  .read_wts_mem = wts_pattern_168,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_168, l1_wts_write_pattern_168),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_168, l1_read_pattern_168),
+  .write_ofm_mem = ofm_pattern_168,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_168,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_168_1 = {
+  .mk_in0_size = ifm2sv_size_168,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_168,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_169 = {
+  .mk_in0_size = ifmsv_size_169,
+  .mk_in1_size = wtssv_size_169,
+  .mk_out0_size = ofmsv_size_169,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xf580, 0xa800},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_169,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_169, l1_write_pattern_169),
+  .read_wts_mem = wts_pattern_169,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_169, l1_wts_write_pattern_169),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_169, l1_read_pattern_169),
+  .write_ofm_mem = ofm_pattern_169,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_169,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_170 = {
+  .mk_in0_size = ifmsv_size_170,
+  .mk_in1_size = wtssv_size_170,
+  .mk_out0_size = ofmsv_size_170,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa600, 0xcd80},
+  .read_ifm_mem = ifm_pattern_170,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_170, l1_write_pattern_170),
+  .read_wts_mem = wts_pattern_170,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_170, l1_wts_write_pattern_170),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_170, l1_read_pattern_170),
+  .write_ofm_mem = ofm_pattern_170,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_170,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_171 = {
+  .mk_in0_size = ifmsv_size_171,
+  .mk_in1_size = wtssv_size_171,
+  .mk_out0_size = ofmsv_size_171,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa600, 0xcd80},
+  .read_ifm_mem = ifm_pattern_171,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_171, l1_write_pattern_171),
+  .read_wts_mem = wts_pattern_171,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_171, l1_wts_write_pattern_171),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_171, l1_read_pattern_171),
+  .write_ofm_mem = ofm_pattern_171,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_171,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_172 = {
+  .mk_in0_size = ifmsv_size_172,
+  .mk_in1_size = wtssv_size_172,
+  .mk_out0_size = ofmsv_size_172,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa600, 0xcd80},
+  .read_ifm_mem = ifm_pattern_172,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_172, l1_write_pattern_172),
+  .read_wts_mem = wts_pattern_172,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_172, l1_wts_write_pattern_172),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_172, l1_read_pattern_172),
+  .write_ofm_mem = ofm_pattern_172,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_172,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_173 = {
+  .mk_in0_size = ifmsv_size_173,
+  .mk_in1_size = wtssv_size_173,
+  .mk_out0_size = ofmsv_size_173,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_173,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_173, l1_write_pattern_173),
+  .read_wts_mem = wts_pattern_173,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_173, l1_wts_write_pattern_173),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_173, l1_read_pattern_173),
+  .write_ofm_mem = ofm_pattern_173,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_173,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_173_1 = {
+  .mk_in0_size = ifm2sv_size_173,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_173,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_175 = {
+  .mk_in0_size = ifmsv_size_175,
+  .mk_in1_size = wtssv_size_175,
+  .mk_out0_size = ofmsv_size_175,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xb000, 0xcd80},
+  .read_ifm_mem = ifm_pattern_175,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_175, l1_write_pattern_175),
+  .read_wts_mem = wts_pattern_175,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_175, l1_wts_write_pattern_175),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_175, l1_read_pattern_175),
+  .write_ofm_mem = ofm_pattern_175,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_175,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_176 = {
+  .mk_in0_size = ifmsv_size_176,
+  .mk_in1_size = wtssv_size_176,
+  .mk_out0_size = ofmsv_size_176,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe580, 0x9800},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_176,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_176, l1_write_pattern_176),
+  .read_wts_mem = wts_pattern_176,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_176, l1_wts_write_pattern_176),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_176, l1_read_pattern_176),
+  .write_ofm_mem = ofm_pattern_176,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_176,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_177 = {
+  .mk_in0_size = ifmsv_size_177,
+  .mk_in1_size = wtssv_size_177,
+  .mk_out0_size = ofmsv_size_177,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xd280, 0x8500},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_177,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_177, l1_write_pattern_177),
+  .read_wts_mem = wts_pattern_177,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_177, l1_wts_write_pattern_177),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_177, l1_read_pattern_177),
+  .write_ofm_mem = ofm_pattern_177,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_177,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_178 = {
+  .mk_in0_size = ifmsv_size_178,
+  .mk_in1_size = wtssv_size_178,
+  .mk_out0_size = ofmsv_size_178,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xaf80, 0xcd80},
+  .read_ifm_mem = ifm_pattern_178,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_178, l1_write_pattern_178),
+  .read_wts_mem = wts_pattern_178,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_178, l1_wts_write_pattern_178),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_178, l1_read_pattern_178),
+  .write_ofm_mem = ofm_pattern_178,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_178,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_179 = {
+  .mk_in0_size = ifmsv_size_179,
+  .mk_in1_size = wtssv_size_179,
+  .mk_out0_size = ofmsv_size_179,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xb080, 0xcd80},
+  .read_ifm_mem = ifm_pattern_179,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_179, l1_write_pattern_179),
+  .read_wts_mem = wts_pattern_179,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_179, l1_wts_write_pattern_179),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_179, l1_read_pattern_179),
+  .write_ofm_mem = ofm_pattern_179,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_179,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_180 = {
+  .mk_in0_size = ifmsv_size_180,
+  .mk_in1_size = wtssv_size_180,
+  .mk_out0_size = ofmsv_size_180,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xae80, 0xcd80},
+  .read_ifm_mem = ifm_pattern_180,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_180, l1_write_pattern_180),
+  .read_wts_mem = wts_pattern_180,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_180, l1_wts_write_pattern_180),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_180, l1_read_pattern_180),
+  .write_ofm_mem = ofm_pattern_180,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_180,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_182 = {
+  .mk_in0_size = ifmsv_size_182,
+  .mk_in1_size = wtssv_size_182,
+  .mk_out0_size = ofmsv_size_182,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_182,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_182, l1_write_pattern_182),
+  .read_wts_mem = wts_pattern_182,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_182, l1_wts_write_pattern_182),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_182, l1_read_pattern_182),
+  .write_ofm_mem = ofm_pattern_182,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_182,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_182_1 = {
+  .mk_in0_size = ifm2sv_size_182,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_182,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_183 = {
+  .mk_in0_size = ifmsv_size_183,
+  .mk_in1_size = wtssv_size_183,
+  .mk_out0_size = ofmsv_size_183,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe980, 0x9c00},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_183,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_183, l1_write_pattern_183),
+  .read_wts_mem = wts_pattern_183,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_183, l1_wts_write_pattern_183),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_183, l1_read_pattern_183),
+  .write_ofm_mem = ofm_pattern_183,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_183,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_183_1 = {
+  .mk_in0_size = ifm2sv_size_183,
+  .mk_in0_addr = {0x2000, 0x6000},
+  .read_ifm_mem = ifm2_pattern_183,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_184 = {
+  .mk_in0_size = ifmsv_size_184,
+  .mk_in1_size = wtssv_size_184,
+  .mk_out0_size = ofmsv_size_184,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe180, 0x9400},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_184,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_184, l1_write_pattern_184),
+  .read_wts_mem = wts_pattern_184,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_184, l1_wts_write_pattern_184),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_184, l1_read_pattern_184),
+  .write_ofm_mem = ofm_pattern_184,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_184,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_185 = {
+  .mk_in0_size = ifmsv_size_185,
+  .mk_in1_size = wtssv_size_185,
+  .mk_out0_size = ofmsv_size_185,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa600, 0xcd80},
+  .read_ifm_mem = ifm_pattern_185,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_185, l1_write_pattern_185),
+  .read_wts_mem = wts_pattern_185,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_185, l1_wts_write_pattern_185),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_185, l1_read_pattern_185),
+  .write_ofm_mem = ofm_pattern_185,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_185,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_186 = {
+  .mk_in0_size = ifmsv_size_186,
+  .mk_in1_size = wtssv_size_186,
+  .mk_out0_size = ofmsv_size_186,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa600, 0xcd80},
+  .read_ifm_mem = ifm_pattern_186,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_186, l1_write_pattern_186),
+  .read_wts_mem = wts_pattern_186,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_186, l1_wts_write_pattern_186),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_186, l1_read_pattern_186),
+  .write_ofm_mem = ofm_pattern_186,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_186,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_187 = {
+  .mk_in0_size = ifmsv_size_187,
+  .mk_in1_size = wtssv_size_187,
+  .mk_out0_size = ofmsv_size_187,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa600, 0xcd80},
+  .read_ifm_mem = ifm_pattern_187,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_187, l1_write_pattern_187),
+  .read_wts_mem = wts_pattern_187,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_187, l1_wts_write_pattern_187),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_187, l1_read_pattern_187),
+  .write_ofm_mem = ofm_pattern_187,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_187,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_188 = {
+  .mk_in0_size = ifmsv_size_188,
+  .mk_in1_size = wtssv_size_188,
+  .mk_out0_size = ofmsv_size_188,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_188,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_188, l1_write_pattern_188),
+  .read_wts_mem = wts_pattern_188,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_188, l1_wts_write_pattern_188),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_188, l1_read_pattern_188),
+  .write_ofm_mem = ofm_pattern_188,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_188,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_188_1 = {
+  .mk_in0_size = ifm2sv_size_188,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_188,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_189 = {
+  .mk_in0_size = ifmsv_size_189,
+  .mk_in1_size = wtssv_size_189,
+  .mk_out0_size = ofmsv_size_189,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xf580, 0xa800},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_189,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_189, l1_write_pattern_189),
+  .read_wts_mem = wts_pattern_189,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_189, l1_wts_write_pattern_189),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_189, l1_read_pattern_189),
+  .write_ofm_mem = ofm_pattern_189,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_189,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_190 = {
+  .mk_in0_size = ifmsv_size_190,
+  .mk_in1_size = wtssv_size_190,
+  .mk_out0_size = ofmsv_size_190,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa600, 0xcd80},
+  .read_ifm_mem = ifm_pattern_190,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_190, l1_write_pattern_190),
+  .read_wts_mem = wts_pattern_190,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_190, l1_wts_write_pattern_190),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_190, l1_read_pattern_190),
+  .write_ofm_mem = ofm_pattern_190,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_190,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_191 = {
+  .mk_in0_size = ifmsv_size_191,
+  .mk_in1_size = wtssv_size_191,
+  .mk_out0_size = ofmsv_size_191,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa600, 0xcd80},
+  .read_ifm_mem = ifm_pattern_191,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_191, l1_write_pattern_191),
+  .read_wts_mem = wts_pattern_191,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_191, l1_wts_write_pattern_191),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_191, l1_read_pattern_191),
+  .write_ofm_mem = ofm_pattern_191,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_191,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_192 = {
+  .mk_in0_size = ifmsv_size_192,
+  .mk_in1_size = wtssv_size_192,
+  .mk_out0_size = ofmsv_size_192,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa600, 0xcd80},
+  .read_ifm_mem = ifm_pattern_192,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_192, l1_write_pattern_192),
+  .read_wts_mem = wts_pattern_192,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_192, l1_wts_write_pattern_192),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_192, l1_read_pattern_192),
+  .write_ofm_mem = ofm_pattern_192,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_192,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_193 = {
+  .mk_in0_size = ifmsv_size_193,
+  .mk_in1_size = wtssv_size_193,
+  .mk_out0_size = ofmsv_size_193,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_193,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_193, l1_write_pattern_193),
+  .read_wts_mem = wts_pattern_193,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_193, l1_wts_write_pattern_193),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_193, l1_read_pattern_193),
+  .write_ofm_mem = ofm_pattern_193,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_193,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_193_1 = {
+  .mk_in0_size = ifm2sv_size_193,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_193,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_195 = {
+  .mk_in0_size = ifmsv_size_195,
+  .mk_in1_size = wtssv_size_195,
+  .mk_out0_size = ofmsv_size_195,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xb000, 0xcd80},
+  .read_ifm_mem = ifm_pattern_195,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_195, l1_write_pattern_195),
+  .read_wts_mem = wts_pattern_195,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_195, l1_wts_write_pattern_195),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_195, l1_read_pattern_195),
+  .write_ofm_mem = ofm_pattern_195,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_195,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_196 = {
+  .mk_in0_size = ifmsv_size_196,
+  .mk_in1_size = wtssv_size_196,
+  .mk_out0_size = ofmsv_size_196,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe580, 0x9800},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_196,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_196, l1_write_pattern_196),
+  .read_wts_mem = wts_pattern_196,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_196, l1_wts_write_pattern_196),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_196, l1_read_pattern_196),
+  .write_ofm_mem = ofm_pattern_196,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_196,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_197 = {
+  .mk_in0_size = ifmsv_size_197,
+  .mk_in1_size = wtssv_size_197,
+  .mk_out0_size = ofmsv_size_197,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xd280, 0x8500},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_197,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_197, l1_write_pattern_197),
+  .read_wts_mem = wts_pattern_197,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_197, l1_wts_write_pattern_197),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_197, l1_read_pattern_197),
+  .write_ofm_mem = ofm_pattern_197,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_197,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_198 = {
+  .mk_in0_size = ifmsv_size_198,
+  .mk_in1_size = wtssv_size_198,
+  .mk_out0_size = ofmsv_size_198,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xaf80, 0xcd80},
+  .read_ifm_mem = ifm_pattern_198,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_198, l1_write_pattern_198),
+  .read_wts_mem = wts_pattern_198,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_198, l1_wts_write_pattern_198),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_198, l1_read_pattern_198),
+  .write_ofm_mem = ofm_pattern_198,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_198,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_199 = {
+  .mk_in0_size = ifmsv_size_199,
+  .mk_in1_size = wtssv_size_199,
+  .mk_out0_size = ofmsv_size_199,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xb080, 0xcd80},
+  .read_ifm_mem = ifm_pattern_199,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_199, l1_write_pattern_199),
+  .read_wts_mem = wts_pattern_199,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_199, l1_wts_write_pattern_199),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_199, l1_read_pattern_199),
+  .write_ofm_mem = ofm_pattern_199,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_199,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_200 = {
+  .mk_in0_size = ifmsv_size_200,
+  .mk_in1_size = wtssv_size_200,
+  .mk_out0_size = ofmsv_size_200,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xae80, 0xcd80},
+  .read_ifm_mem = ifm_pattern_200,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_200, l1_write_pattern_200),
+  .read_wts_mem = wts_pattern_200,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_200, l1_wts_write_pattern_200),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_200, l1_read_pattern_200),
+  .write_ofm_mem = ofm_pattern_200,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_200,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_202 = {
+  .mk_in0_size = ifmsv_size_202,
+  .mk_in1_size = wtssv_size_202,
+  .mk_out0_size = ofmsv_size_202,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_202,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_202, l1_write_pattern_202),
+  .read_wts_mem = wts_pattern_202,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_202, l1_wts_write_pattern_202),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_202, l1_read_pattern_202),
+  .write_ofm_mem = ofm_pattern_202,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_202,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_202_1 = {
+  .mk_in0_size = ifm2sv_size_202,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_202,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_203 = {
+  .mk_in0_size = ifmsv_size_203,
+  .mk_in1_size = wtssv_size_203,
+  .mk_out0_size = ofmsv_size_203,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe980, 0x9c00},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_203,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_203, l1_write_pattern_203),
+  .read_wts_mem = wts_pattern_203,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_203, l1_wts_write_pattern_203),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_203, l1_read_pattern_203),
+  .write_ofm_mem = ofm_pattern_203,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_203,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_203_1 = {
+  .mk_in0_size = ifm2sv_size_203,
+  .mk_in0_addr = {0x2000, 0x6000},
+  .read_ifm_mem = ifm2_pattern_203,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_204 = {
+  .mk_in0_size = ifmsv_size_204,
+  .mk_in1_size = wtssv_size_204,
+  .mk_out0_size = ofmsv_size_204,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe180, 0x9400},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_204,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_204, l1_write_pattern_204),
+  .read_wts_mem = wts_pattern_204,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_204, l1_wts_write_pattern_204),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_204, l1_read_pattern_204),
+  .write_ofm_mem = ofm_pattern_204,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_204,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_205 = {
+  .mk_in0_size = ifmsv_size_205,
+  .mk_in1_size = wtssv_size_205,
+  .mk_out0_size = ofmsv_size_205,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa600, 0xcd80},
+  .read_ifm_mem = ifm_pattern_205,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_205, l1_write_pattern_205),
+  .read_wts_mem = wts_pattern_205,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_205, l1_wts_write_pattern_205),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_205, l1_read_pattern_205),
+  .write_ofm_mem = ofm_pattern_205,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_205,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_206 = {
+  .mk_in0_size = ifmsv_size_206,
+  .mk_in1_size = wtssv_size_206,
+  .mk_out0_size = ofmsv_size_206,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa600, 0xcd80},
+  .read_ifm_mem = ifm_pattern_206,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_206, l1_write_pattern_206),
+  .read_wts_mem = wts_pattern_206,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_206, l1_wts_write_pattern_206),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_206, l1_read_pattern_206),
+  .write_ofm_mem = ofm_pattern_206,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_206,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_207 = {
+  .mk_in0_size = ifmsv_size_207,
+  .mk_in1_size = wtssv_size_207,
+  .mk_out0_size = ofmsv_size_207,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa600, 0xcd80},
+  .read_ifm_mem = ifm_pattern_207,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_207, l1_write_pattern_207),
+  .read_wts_mem = wts_pattern_207,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_207, l1_wts_write_pattern_207),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_207, l1_read_pattern_207),
+  .write_ofm_mem = ofm_pattern_207,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_207,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_208 = {
+  .mk_in0_size = ifmsv_size_208,
+  .mk_in1_size = wtssv_size_208,
+  .mk_out0_size = ofmsv_size_208,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_208,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_208, l1_write_pattern_208),
+  .read_wts_mem = wts_pattern_208,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_208, l1_wts_write_pattern_208),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_208, l1_read_pattern_208),
+  .write_ofm_mem = ofm_pattern_208,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_208,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_208_1 = {
+  .mk_in0_size = ifm2sv_size_208,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_208,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_210 = {
+  .mk_in0_size = ifmsv_size_210,
+  .mk_in1_size = wtssv_size_210,
+  .mk_out0_size = ofmsv_size_210,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xb000, 0xcd80},
+  .read_ifm_mem = ifm_pattern_210,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_210, l1_write_pattern_210),
+  .read_wts_mem = wts_pattern_210,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_210, l1_wts_write_pattern_210),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_210, l1_read_pattern_210),
+  .write_ofm_mem = ofm_pattern_210,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_210,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_211 = {
+  .mk_in0_size = ifmsv_size_211,
+  .mk_in1_size = wtssv_size_211,
+  .mk_out0_size = ofmsv_size_211,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe580, 0x9800},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_211,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_211, l1_write_pattern_211),
+  .read_wts_mem = wts_pattern_211,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_211, l1_wts_write_pattern_211),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_211, l1_read_pattern_211),
+  .write_ofm_mem = ofm_pattern_211,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_211,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_212 = {
+  .mk_in0_size = ifmsv_size_212,
+  .mk_in1_size = wtssv_size_212,
+  .mk_out0_size = ofmsv_size_212,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xae80, 0xcd80},
+  .read_ifm_mem = ifm_pattern_212,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_212, l1_write_pattern_212),
+  .read_wts_mem = wts_pattern_212,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_212, l1_wts_write_pattern_212),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_212, l1_read_pattern_212),
+  .write_ofm_mem = ofm_pattern_212,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_212,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_214 = {
+  .mk_in0_size = ifmsv_size_214,
+  .mk_in1_size = wtssv_size_214,
+  .mk_out0_size = ofmsv_size_214,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe580, 0x9800},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_214,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_214, l1_write_pattern_214),
+  .read_wts_mem = wts_pattern_214,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_214, l1_wts_write_pattern_214),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_214, l1_read_pattern_214),
+  .write_ofm_mem = ofm_pattern_214,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_214,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_214_1 = {
+  .mk_in0_size = ifm2sv_size_214,
+  .mk_in0_addr = {0x2000, 0x6000},
+  .read_ifm_mem = ifm2_pattern_214,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_218 = {
+  .mk_in0_size = ifmsv_size_218,
+  .mk_in1_size = wtssv_size_218,
+  .mk_out0_size = ofmsv_size_218,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe2c0, 0x9540},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_218,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_218, l1_write_pattern_218),
+  .read_wts_mem = wts_pattern_218,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_218, l1_wts_write_pattern_218),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_218, l1_read_pattern_218),
+  .write_ofm_mem = ofm_pattern_218,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_218,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_219 = {
+  .mk_in0_size = ifmsv_size_219,
+  .mk_in1_size = wtssv_size_219,
+  .mk_out0_size = ofmsv_size_219,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa380, 0xcd80},
+  .read_ifm_mem = ifm_pattern_219,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_219, l1_write_pattern_219),
+  .read_wts_mem = wts_pattern_219,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_219, l1_wts_write_pattern_219),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_219, l1_read_pattern_219),
+  .write_ofm_mem = ofm_pattern_219,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_219,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_221 = {
+  .mk_in0_size = ifmsv_size_221,
+  .mk_in1_size = wtssv_size_221,
+  .mk_out0_size = ofmsv_size_221,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_221,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_221, l1_write_pattern_221),
+  .read_wts_mem = wts_pattern_221,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_221, l1_wts_write_pattern_221),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_221, l1_read_pattern_221),
+  .write_ofm_mem = ofm_pattern_221,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_221,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_221_1 = {
+  .mk_in0_size = ifm2sv_size_221,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_221,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_222 = {
+  .mk_in0_size = ifmsv_size_222,
+  .mk_in1_size = wtssv_size_222,
+  .mk_out0_size = ofmsv_size_222,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_222,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_222, l1_write_pattern_222),
+  .read_wts_mem = wts_pattern_222,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_222, l1_wts_write_pattern_222),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_222, l1_read_pattern_222),
+  .write_ofm_mem = ofm_pattern_222,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_222,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_222_1 = {
+  .mk_in0_size = ifm2sv_size_222,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_222,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_224 = {
+  .mk_in0_size = ifmsv_size_224,
+  .mk_in1_size = wtssv_size_224,
+  .mk_out0_size = ofmsv_size_224,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_224,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_224, l1_write_pattern_224),
+  .read_wts_mem = wts_pattern_224,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_224, l1_wts_write_pattern_224),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_224, l1_read_pattern_224),
+  .write_ofm_mem = ofm_pattern_224,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_224,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_224_1 = {
+  .mk_in0_size = ifm2sv_size_224,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_224,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_226 = {
+  .mk_in0_size = ifmsv_size_226,
+  .mk_in1_size = wtssv_size_226,
+  .mk_out0_size = ofmsv_size_226,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe2c0, 0x9540},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_226,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_226, l1_write_pattern_226),
+  .read_wts_mem = wts_pattern_226,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_226, l1_wts_write_pattern_226),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_226, l1_read_pattern_226),
+  .write_ofm_mem = ofm_pattern_226,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_226,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_227 = {
+  .mk_in0_size = ifmsv_size_227,
+  .mk_in1_size = wtssv_size_227,
+  .mk_out0_size = ofmsv_size_227,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_227,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_227, l1_write_pattern_227),
+  .read_wts_mem = wts_pattern_227,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_227, l1_wts_write_pattern_227),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_227, l1_read_pattern_227),
+  .write_ofm_mem = ofm_pattern_227,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_227,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_228 = {
+  .mk_in0_size = ifmsv_size_228,
+  .mk_in1_size = wtssv_size_228,
+  .mk_out0_size = ofmsv_size_228,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_228,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_228, l1_write_pattern_228),
+  .read_wts_mem = wts_pattern_228,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_228, l1_wts_write_pattern_228),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_228, l1_read_pattern_228),
+  .write_ofm_mem = ofm_pattern_228,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_228,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_228_1 = {
+  .mk_in0_size = ifm2sv_size_228,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_228,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_229 = {
+  .mk_in0_size = ifmsv_size_229,
+  .mk_in1_size = wtssv_size_229,
+  .mk_out0_size = ofmsv_size_229,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_229,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_229, l1_write_pattern_229),
+  .read_wts_mem = wts_pattern_229,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_229, l1_wts_write_pattern_229),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_229, l1_read_pattern_229),
+  .write_ofm_mem = ofm_pattern_229,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_229,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_229_1 = {
+  .mk_in0_size = ifm2sv_size_229,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_229,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_233 = {
+  .mk_in0_size = ifmsv_size_233,
+  .mk_in1_size = wtssv_size_233,
+  .mk_out0_size = ofmsv_size_233,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_233,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_233, l1_write_pattern_233),
+  .read_wts_mem = wts_pattern_233,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_233, l1_wts_write_pattern_233),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_233, l1_read_pattern_233),
+  .write_ofm_mem = ofm_pattern_233,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_233,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_234 = {
+  .mk_in0_size = ifmsv_size_234,
+  .mk_in1_size = wtssv_size_234,
+  .mk_out0_size = ofmsv_size_234,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_234,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_234, l1_write_pattern_234),
+  .read_wts_mem = wts_pattern_234,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_234, l1_wts_write_pattern_234),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_234, l1_read_pattern_234),
+  .write_ofm_mem = ofm_pattern_234,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_234,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_235 = {
+  .mk_in0_size = ifmsv_size_235,
+  .mk_in1_size = wtssv_size_235,
+  .mk_out0_size = ofmsv_size_235,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_235,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_235, l1_write_pattern_235),
+  .read_wts_mem = wts_pattern_235,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_235, l1_wts_write_pattern_235),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_235, l1_read_pattern_235),
+  .write_ofm_mem = ofm_pattern_235,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_235,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_237 = {
+  .mk_in0_size = ifmsv_size_237,
+  .mk_in1_size = wtssv_size_237,
+  .mk_out0_size = ofmsv_size_237,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xecc0, 0x9f40},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_237,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_237, l1_write_pattern_237),
+  .read_wts_mem = wts_pattern_237,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_237, l1_wts_write_pattern_237),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_237, l1_read_pattern_237),
+  .write_ofm_mem = ofm_pattern_237,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_237,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_241 = {
+  .mk_in0_size = ifmsv_size_241,
+  .mk_in1_size = wtssv_size_241,
+  .mk_out0_size = ofmsv_size_241,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xecc0, 0x9f40},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_241,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_241, l1_write_pattern_241),
+  .read_wts_mem = wts_pattern_241,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_241, l1_wts_write_pattern_241),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_241, l1_read_pattern_241),
+  .write_ofm_mem = ofm_pattern_241,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_241,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_242 = {
+  .mk_in0_size = ifmsv_size_242,
+  .mk_in1_size = wtssv_size_242,
+  .mk_out0_size = ofmsv_size_242,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa380, 0xcd80},
+  .read_ifm_mem = ifm_pattern_242,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_242, l1_write_pattern_242),
+  .read_wts_mem = wts_pattern_242,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_242, l1_wts_write_pattern_242),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_242, l1_read_pattern_242),
+  .write_ofm_mem = ofm_pattern_242,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_242,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_244 = {
+  .mk_in0_size = ifmsv_size_244,
+  .mk_in1_size = wtssv_size_244,
+  .mk_out0_size = ofmsv_size_244,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_244,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_244, l1_write_pattern_244),
+  .read_wts_mem = wts_pattern_244,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_244, l1_wts_write_pattern_244),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_244, l1_read_pattern_244),
+  .write_ofm_mem = ofm_pattern_244,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_244,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_244_1 = {
+  .mk_in0_size = ifm2sv_size_244,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_244,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_245 = {
+  .mk_in0_size = ifmsv_size_245,
+  .mk_in1_size = wtssv_size_245,
+  .mk_out0_size = ofmsv_size_245,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_245,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_245, l1_write_pattern_245),
+  .read_wts_mem = wts_pattern_245,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_245, l1_wts_write_pattern_245),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_245, l1_read_pattern_245),
+  .write_ofm_mem = ofm_pattern_245,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_245,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_245_1 = {
+  .mk_in0_size = ifm2sv_size_245,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_245,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_247 = {
+  .mk_in0_size = ifmsv_size_247,
+  .mk_in1_size = wtssv_size_247,
+  .mk_out0_size = ofmsv_size_247,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_247,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_247, l1_write_pattern_247),
+  .read_wts_mem = wts_pattern_247,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_247, l1_wts_write_pattern_247),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_247, l1_read_pattern_247),
+  .write_ofm_mem = ofm_pattern_247,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_247,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_247_1 = {
+  .mk_in0_size = ifm2sv_size_247,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_247,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_249 = {
+  .mk_in0_size = ifmsv_size_249,
+  .mk_in1_size = wtssv_size_249,
+  .mk_out0_size = ofmsv_size_249,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xecc0, 0x9f40},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_249,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_249, l1_write_pattern_249),
+  .read_wts_mem = wts_pattern_249,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_249, l1_wts_write_pattern_249),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_249, l1_read_pattern_249),
+  .write_ofm_mem = ofm_pattern_249,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_249,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_250 = {
+  .mk_in0_size = ifmsv_size_250,
+  .mk_in1_size = wtssv_size_250,
+  .mk_out0_size = ofmsv_size_250,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa380, 0xcd80},
+  .read_ifm_mem = ifm_pattern_250,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_250, l1_write_pattern_250),
+  .read_wts_mem = wts_pattern_250,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_250, l1_wts_write_pattern_250),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_250, l1_read_pattern_250),
+  .write_ofm_mem = ofm_pattern_250,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_250,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_251 = {
+  .mk_in0_size = ifmsv_size_251,
+  .mk_in1_size = wtssv_size_251,
+  .mk_out0_size = ofmsv_size_251,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_251,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_251, l1_write_pattern_251),
+  .read_wts_mem = wts_pattern_251,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_251, l1_wts_write_pattern_251),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_251, l1_read_pattern_251),
+  .write_ofm_mem = ofm_pattern_251,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_251,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_251_1 = {
+  .mk_in0_size = ifm2sv_size_251,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_251,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_252 = {
+  .mk_in0_size = ifmsv_size_252,
+  .mk_in1_size = wtssv_size_252,
+  .mk_out0_size = ofmsv_size_252,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_252,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_252, l1_write_pattern_252),
+  .read_wts_mem = wts_pattern_252,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_252, l1_wts_write_pattern_252),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_252, l1_read_pattern_252),
+  .write_ofm_mem = ofm_pattern_252,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_252,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_252_1 = {
+  .mk_in0_size = ifm2sv_size_252,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_252,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_257 = {
+  .mk_in0_size = ifmsv_size_257,
+  .mk_in1_size = wtssv_size_257,
+  .mk_out0_size = ofmsv_size_257,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xed00, 0x9f80},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_257,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_257, l1_write_pattern_257),
+  .read_wts_mem = wts_pattern_257,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_257, l1_wts_write_pattern_257),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_257, l1_read_pattern_257),
+  .write_ofm_mem = ofm_pattern_257,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_257,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_261 = {
+  .mk_in0_size = ifmsv_size_261,
+  .mk_in1_size = wtssv_size_261,
+  .mk_out0_size = ofmsv_size_261,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xed00, 0x9f80},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_261,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_261, l1_write_pattern_261),
+  .read_wts_mem = wts_pattern_261,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_261, l1_wts_write_pattern_261),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_261, l1_read_pattern_261),
+  .write_ofm_mem = ofm_pattern_261,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_261,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_262 = {
+  .mk_in0_size = ifmsv_size_262,
+  .mk_in1_size = wtssv_size_262,
+  .mk_out0_size = ofmsv_size_262,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa380, 0xcd80},
+  .read_ifm_mem = ifm_pattern_262,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_262, l1_write_pattern_262),
+  .read_wts_mem = wts_pattern_262,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_262, l1_wts_write_pattern_262),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_262, l1_read_pattern_262),
+  .write_ofm_mem = ofm_pattern_262,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_262,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_264 = {
+  .mk_in0_size = ifmsv_size_264,
+  .mk_in1_size = wtssv_size_264,
+  .mk_out0_size = ofmsv_size_264,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_264,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_264, l1_write_pattern_264),
+  .read_wts_mem = wts_pattern_264,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_264, l1_wts_write_pattern_264),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_264, l1_read_pattern_264),
+  .write_ofm_mem = ofm_pattern_264,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_264,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_264_1 = {
+  .mk_in0_size = ifm2sv_size_264,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_264,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_265 = {
+  .mk_in0_size = ifmsv_size_265,
+  .mk_in1_size = wtssv_size_265,
+  .mk_out0_size = ofmsv_size_265,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_265,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_265, l1_write_pattern_265),
+  .read_wts_mem = wts_pattern_265,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_265, l1_wts_write_pattern_265),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_265, l1_read_pattern_265),
+  .write_ofm_mem = ofm_pattern_265,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_265,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_265_1 = {
+  .mk_in0_size = ifm2sv_size_265,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_265,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_267 = {
+  .mk_in0_size = ifmsv_size_267,
+  .mk_in1_size = wtssv_size_267,
+  .mk_out0_size = ofmsv_size_267,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_267,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_267, l1_write_pattern_267),
+  .read_wts_mem = wts_pattern_267,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_267, l1_wts_write_pattern_267),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_267, l1_read_pattern_267),
+  .write_ofm_mem = ofm_pattern_267,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_267,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_267_1 = {
+  .mk_in0_size = ifm2sv_size_267,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_267,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_269 = {
+  .mk_in0_size = ifmsv_size_269,
+  .mk_in1_size = wtssv_size_269,
+  .mk_out0_size = ofmsv_size_269,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xeb40, 0x9dc0},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_269,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_269, l1_write_pattern_269),
+  .read_wts_mem = wts_pattern_269,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_269, l1_wts_write_pattern_269),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_269, l1_read_pattern_269),
+  .write_ofm_mem = ofm_pattern_269,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_269,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_270 = {
+  .mk_in0_size = ifmsv_size_270,
+  .mk_in1_size = wtssv_size_270,
+  .mk_out0_size = ofmsv_size_270,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa380, 0xcd80},
+  .read_ifm_mem = ifm_pattern_270,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_270, l1_write_pattern_270),
+  .read_wts_mem = wts_pattern_270,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_270, l1_wts_write_pattern_270),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_270, l1_read_pattern_270),
+  .write_ofm_mem = ofm_pattern_270,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_270,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_271 = {
+  .mk_in0_size = ifmsv_size_271,
+  .mk_in1_size = wtssv_size_271,
+  .mk_out0_size = ofmsv_size_271,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_271,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_271, l1_write_pattern_271),
+  .read_wts_mem = wts_pattern_271,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_271, l1_wts_write_pattern_271),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_271, l1_read_pattern_271),
+  .write_ofm_mem = ofm_pattern_271,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_271,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_271_1 = {
+  .mk_in0_size = ifm2sv_size_271,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_271,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_272 = {
+  .mk_in0_size = ifmsv_size_272,
+  .mk_in1_size = wtssv_size_272,
+  .mk_out0_size = ofmsv_size_272,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xab00, 0xcd80},
+  .read_ifm_mem = ifm_pattern_272,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_272, l1_write_pattern_272),
+  .read_wts_mem = wts_pattern_272,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_272, l1_wts_write_pattern_272),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_272, l1_read_pattern_272),
+  .write_ofm_mem = ofm_pattern_272,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_272,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_272_1 = {
+  .mk_in0_size = ifm2sv_size_272,
+  .mk_in0_addr = {0x5e00, 0x1e00},
+  .read_ifm_mem = ifm2_pattern_272,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_276 = {
+  .mk_in0_size = ifmsv_size_276,
+  .mk_in1_size = wtssv_size_276,
+  .mk_out0_size = ofmsv_size_276,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xeb40, 0x9dc0},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_276,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_276, l1_write_pattern_276),
+  .read_wts_mem = wts_pattern_276,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_276, l1_wts_write_pattern_276),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_276, l1_read_pattern_276),
+  .write_ofm_mem = ofm_pattern_276,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_276,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_280 = {
+  .mk_in0_size = ifmsv_size_280,
+  .mk_in1_size = wtssv_size_280,
+  .mk_out0_size = ofmsv_size_280,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe700, 0x9980},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_280,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_280, l1_write_pattern_280),
+  .read_wts_mem = wts_pattern_280,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_280, l1_wts_write_pattern_280),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_280, l1_read_pattern_280),
+  .write_ofm_mem = ofm_pattern_280,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_280,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_281 = {
+  .mk_in0_size = ifmsv_size_281,
+  .mk_in1_size = wtssv_size_281,
+  .mk_out0_size = ofmsv_size_281,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa280, 0xcd80},
+  .read_ifm_mem = ifm_pattern_281,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_281, l1_write_pattern_281),
+  .read_wts_mem = wts_pattern_281,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_281, l1_wts_write_pattern_281),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_281, l1_read_pattern_281),
+  .write_ofm_mem = ofm_pattern_281,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_281,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_283 = {
+  .mk_in0_size = ifmsv_size_283,
+  .mk_in1_size = wtssv_size_283,
+  .mk_out0_size = ofmsv_size_283,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xaa80, 0xcd80},
+  .read_ifm_mem = ifm_pattern_283,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_283, l1_write_pattern_283),
+  .read_wts_mem = wts_pattern_283,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_283, l1_wts_write_pattern_283),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_283, l1_read_pattern_283),
+  .write_ofm_mem = ofm_pattern_283,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_283,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_283_1 = {
+  .mk_in0_size = ifm2sv_size_283,
+  .mk_in0_addr = {0x6000, 0x2000},
+  .read_ifm_mem = ifm2_pattern_283,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_284 = {
+  .mk_in0_size = ifmsv_size_284,
+  .mk_in1_size = wtssv_size_284,
+  .mk_out0_size = ofmsv_size_284,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xaa80, 0xcd80},
+  .read_ifm_mem = ifm_pattern_284,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_284, l1_write_pattern_284),
+  .read_wts_mem = wts_pattern_284,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_284, l1_wts_write_pattern_284),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_284, l1_read_pattern_284),
+  .write_ofm_mem = ofm_pattern_284,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_284,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_284_1 = {
+  .mk_in0_size = ifm2sv_size_284,
+  .mk_in0_addr = {0x6000, 0x2000},
+  .read_ifm_mem = ifm2_pattern_284,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_286 = {
+  .mk_in0_size = ifmsv_size_286,
+  .mk_in1_size = wtssv_size_286,
+  .mk_out0_size = ofmsv_size_286,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xaa80, 0xcd80},
+  .read_ifm_mem = ifm_pattern_286,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_286, l1_write_pattern_286),
+  .read_wts_mem = wts_pattern_286,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_286, l1_wts_write_pattern_286),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_286, l1_read_pattern_286),
+  .write_ofm_mem = ofm_pattern_286,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_286,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_286_1 = {
+  .mk_in0_size = ifm2sv_size_286,
+  .mk_in0_addr = {0x6000, 0x2000},
+  .read_ifm_mem = ifm2_pattern_286,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_288 = {
+  .mk_in0_size = ifmsv_size_288,
+  .mk_in1_size = wtssv_size_288,
+  .mk_out0_size = ofmsv_size_288,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe700, 0x9980},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_288,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_288, l1_write_pattern_288),
+  .read_wts_mem = wts_pattern_288,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_288, l1_wts_write_pattern_288),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_288, l1_read_pattern_288),
+  .write_ofm_mem = ofm_pattern_288,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_288,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_289 = {
+  .mk_in0_size = ifmsv_size_289,
+  .mk_in1_size = wtssv_size_289,
+  .mk_out0_size = ofmsv_size_289,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa700, 0xcd80},
+  .read_ifm_mem = ifm_pattern_289,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_289, l1_write_pattern_289),
+  .read_wts_mem = wts_pattern_289,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_289, l1_wts_write_pattern_289),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_289, l1_read_pattern_289),
+  .write_ofm_mem = ofm_pattern_289,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_289,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_290 = {
+  .mk_in0_size = ifmsv_size_290,
+  .mk_in1_size = wtssv_size_290,
+  .mk_out0_size = ofmsv_size_290,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xaa80, 0xcd80},
+  .read_ifm_mem = ifm_pattern_290,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_290, l1_write_pattern_290),
+  .read_wts_mem = wts_pattern_290,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_290, l1_wts_write_pattern_290),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_290, l1_read_pattern_290),
+  .write_ofm_mem = ofm_pattern_290,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_290,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_290_1 = {
+  .mk_in0_size = ifm2sv_size_290,
+  .mk_in0_addr = {0x6000, 0x2000},
+  .read_ifm_mem = ifm2_pattern_290,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_291 = {
+  .mk_in0_size = ifmsv_size_291,
+  .mk_in1_size = wtssv_size_291,
+  .mk_out0_size = ofmsv_size_291,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xaa80, 0xcd80},
+  .read_ifm_mem = ifm_pattern_291,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_291, l1_write_pattern_291),
+  .read_wts_mem = wts_pattern_291,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_291, l1_wts_write_pattern_291),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_291, l1_read_pattern_291),
+  .write_ofm_mem = ofm_pattern_291,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_291,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_291_1 = {
+  .mk_in0_size = ifm2sv_size_291,
+  .mk_in0_addr = {0x6000, 0x2000},
+  .read_ifm_mem = ifm2_pattern_291,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_295 = {
+  .mk_in0_size = ifmsv_size_295,
+  .mk_in1_size = wtssv_size_295,
+  .mk_out0_size = ofmsv_size_295,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xe640, 0x98c0},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_295,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_295, l1_write_pattern_295),
+  .read_wts_mem = wts_pattern_295,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_295, l1_wts_write_pattern_295),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_295, l1_read_pattern_295),
+  .write_ofm_mem = ofm_pattern_295,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_295,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_296 = {
+  .mk_in0_size = ifmsv_size_296,
+  .mk_in1_size = wtssv_size_296,
+  .mk_out0_size = ofmsv_size_296,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xeb40, 0x9dc0},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_296,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_296, l1_write_pattern_296),
+  .read_wts_mem = wts_pattern_296,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_296, l1_wts_write_pattern_296),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_296, l1_read_pattern_296),
+  .write_ofm_mem = ofm_pattern_296,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_296,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_297 = {
+  .mk_in0_size = ifmsv_size_297,
+  .mk_in1_size = wtssv_size_297,
+  .mk_out0_size = ofmsv_size_297,
+  .mk_in0_addr = {0x8000, 0xcd80},
+  .mk_in1_addr = {0xed80, 0xa000},
+  .mk_out0_addr = {0x0, 0x4000},
+  .read_ifm_mem = ifm_pattern_297,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_297, l1_write_pattern_297),
+  .read_wts_mem = wts_pattern_297,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_297, l1_wts_write_pattern_297),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_297, l1_read_pattern_297),
+  .write_ofm_mem = ofm_pattern_297,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_297,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_299 = {
+  .mk_in0_size = ifmsv_size_299,
+  .mk_in1_size = wtssv_size_299,
+  .mk_out0_size = ofmsv_size_299,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa600, 0xcd80},
+  .read_ifm_mem = ifm_pattern_299,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_299, l1_write_pattern_299),
+  .read_wts_mem = wts_pattern_299,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_299, l1_wts_write_pattern_299),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_299, l1_read_pattern_299),
+  .write_ofm_mem = ofm_pattern_299,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_299,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_301 = {
+  .mk_in0_size = ifmsv_size_301,
+  .mk_in1_size = wtssv_size_301,
+  .mk_out0_size = ofmsv_size_301,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_in1_addr = {0x0, 0x0},
+  .mk_out0_addr = {0xad80, 0xcd80},
+  .read_ifm_mem = ifm_pattern_301,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_301, l1_write_pattern_301),
+  .read_wts_mem = wts_pattern_301,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_301, l1_wts_write_pattern_301),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_301, l1_read_pattern_301),
+  .write_ofm_mem = ofm_pattern_301,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_301,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_301_1 = {
+  .mk_in0_size = ifm2sv_size_301,
+  .mk_in0_addr = {0x5400, 0x1400},
+  .read_ifm_mem = ifm2_pattern_301,
+};
+
+ml_adf_overlay_4x4::tiling_params_t tiling_params_layer_302 = {
+  .mk_in0_size = ifmsv_size_302,
+  .mk_in1_size = wtssv_size_302,
+  .mk_out0_size = ofmsv_size_302,
+  .mk_in0_addr = {0x0, 0x4000},
+  .mk_out0_addr = {0xa600, 0xcd80},
+  .read_ifm_mem = ifm_pattern_302,
+  .write_mk_in0 = get_l1_write_pattern(has_l1_write_access_pattern_302, l1_write_pattern_302),
+  .read_wts_mem = wts_pattern_302,
+  .write_mk_in1 = get_l1_wts_write_pattern(has_l1_wts_write_access_pattern_302, l1_wts_write_pattern_302),
+  .read_mk_out0 = get_l1_read_pattern(has_l1_read_access_pattern_302, l1_read_pattern_302),
+  .write_ofm_mem = ofm_pattern_302,
+  .enable_async_ofm = 1,
+  .mk_out0_async_rep = ofm_repetition_302,
+};
+
+
+//Array of single layers
+single_layer_overlay flexml_layers[NUM_LAYERS] = {
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_1,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_1,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_1,/*ofm_repetition=*/ofm_repetition_1,/*tiling_params=*/tiling_params_layer_1),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_6,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/1,layer_params_6,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_6,/*ofm_repetition=*/ofm_repetition_6,/*tiling_params=*/tiling_params_layer_6),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_7,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_7,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_7,/*ofm_repetition=*/ofm_repetition_7,/*tiling_params=*/tiling_params_layer_7),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_8_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_8,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_8,/*wtsL2_size=*/2432,/*kernel_iter=*/kernel_iter_8,/*ofm_repetition=*/ofm_repetition_8,/*tiling_params=*/tiling_params_layer_8),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_9,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_9,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_9,/*ofm_repetition=*/ofm_repetition_9,/*tiling_params=*/tiling_params_layer_9),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_10,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_10,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_10,/*ofm_repetition=*/ofm_repetition_10,/*tiling_params=*/tiling_params_layer_10),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_11,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_11,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_11,/*ofm_repetition=*/ofm_repetition_11,/*tiling_params=*/tiling_params_layer_11),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_12,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_12,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_12,/*ofm_repetition=*/ofm_repetition_12,/*tiling_params=*/tiling_params_layer_12),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_13_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_13,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/10,/*kernel_type=*/-1,layer_params_13,/*wtsL2_size=*/512,/*kernel_iter=*/kernel_iter_13,/*ofm_repetition=*/ofm_repetition_13,/*tiling_params=*/tiling_params_layer_13),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_14_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_14,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/14,/*kernel_type=*/-1,layer_params_14,/*wtsL2_size=*/2176,/*kernel_iter=*/kernel_iter_14,/*ofm_repetition=*/ofm_repetition_14,/*tiling_params=*/tiling_params_layer_14),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_15_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_15,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_15,/*wtsL2_size=*/4352,/*kernel_iter=*/kernel_iter_15,/*ofm_repetition=*/ofm_repetition_15,/*tiling_params=*/tiling_params_layer_15),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_16_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_16,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/10,/*kernel_type=*/-1,layer_params_16,/*wtsL2_size=*/1024,/*kernel_iter=*/kernel_iter_16,/*ofm_repetition=*/ofm_repetition_16,/*tiling_params=*/tiling_params_layer_16),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_18_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_18,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_18,/*wtsL2_size=*/4352,/*kernel_iter=*/kernel_iter_18,/*ofm_repetition=*/ofm_repetition_18,/*tiling_params=*/tiling_params_layer_18),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_19_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_19,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_19,/*wtsL2_size=*/6528,/*kernel_iter=*/kernel_iter_19,/*ofm_repetition=*/ofm_repetition_19,/*tiling_params=*/tiling_params_layer_19),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_20_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_20,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/10,/*kernel_type=*/-1,layer_params_20,/*wtsL2_size=*/1536,/*kernel_iter=*/kernel_iter_20,/*ofm_repetition=*/ofm_repetition_20,/*tiling_params=*/tiling_params_layer_20),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_22_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_22,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/14,/*kernel_type=*/-1,layer_params_22,/*wtsL2_size=*/4864,/*kernel_iter=*/kernel_iter_22,/*ofm_repetition=*/ofm_repetition_22,/*tiling_params=*/tiling_params_layer_22),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_23_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_23,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_23,/*wtsL2_size=*/6528,/*kernel_iter=*/kernel_iter_23,/*ofm_repetition=*/ofm_repetition_23,/*tiling_params=*/tiling_params_layer_23),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_24_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_24,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/10,/*kernel_type=*/-1,layer_params_24,/*wtsL2_size=*/4224,/*kernel_iter=*/kernel_iter_24,/*ofm_repetition=*/ofm_repetition_24,/*tiling_params=*/tiling_params_layer_24),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_26,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/13,/*kernel_type=*/1,layer_params_26,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_26,/*ofm_repetition=*/ofm_repetition_26,/*tiling_params=*/tiling_params_layer_26),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_27_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_27,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_27,/*wtsL2_size=*/4864,/*kernel_iter=*/kernel_iter_27,/*ofm_repetition=*/ofm_repetition_27,/*tiling_params=*/tiling_params_layer_27),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_28_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_28,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_28,/*wtsL2_size=*/8704,/*kernel_iter=*/kernel_iter_28,/*ofm_repetition=*/ofm_repetition_28,/*tiling_params=*/tiling_params_layer_28),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_29,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_29,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_29,/*ofm_repetition=*/ofm_repetition_29,/*tiling_params=*/tiling_params_layer_29),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_30,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_30,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_30,/*ofm_repetition=*/ofm_repetition_30,/*tiling_params=*/tiling_params_layer_30),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_31,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_31,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_31,/*ofm_repetition=*/ofm_repetition_31,/*tiling_params=*/tiling_params_layer_31),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_33,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_33,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_33,/*ofm_repetition=*/ofm_repetition_33,/*tiling_params=*/tiling_params_layer_33),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_34_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_34,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_34,/*wtsL2_size=*/4864,/*kernel_iter=*/kernel_iter_34,/*ofm_repetition=*/ofm_repetition_34,/*tiling_params=*/tiling_params_layer_34),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_35_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_35,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_35,/*wtsL2_size=*/8704,/*kernel_iter=*/kernel_iter_35,/*ofm_repetition=*/ofm_repetition_35,/*tiling_params=*/tiling_params_layer_35),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_36_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_36,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/10,/*kernel_type=*/-1,layer_params_36,/*wtsL2_size=*/5632,/*kernel_iter=*/kernel_iter_36,/*ofm_repetition=*/ofm_repetition_36,/*tiling_params=*/tiling_params_layer_36),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_38,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/13,/*kernel_type=*/1,layer_params_38,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_38,/*ofm_repetition=*/ofm_repetition_38,/*tiling_params=*/tiling_params_layer_38),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_39_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_39,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_39,/*wtsL2_size=*/7936,/*kernel_iter=*/kernel_iter_39,/*ofm_repetition=*/ofm_repetition_39,/*tiling_params=*/tiling_params_layer_39),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_40_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_40,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_40,/*wtsL2_size=*/8704,/*kernel_iter=*/kernel_iter_40,/*ofm_repetition=*/ofm_repetition_40,/*tiling_params=*/tiling_params_layer_40),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_41,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_41,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_41,/*ofm_repetition=*/ofm_repetition_41,/*tiling_params=*/tiling_params_layer_41),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_42,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_42,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_42,/*ofm_repetition=*/ofm_repetition_42,/*tiling_params=*/tiling_params_layer_42),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_43,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_43,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_43,/*ofm_repetition=*/ofm_repetition_43,/*tiling_params=*/tiling_params_layer_43),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_45,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_45,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_45,/*ofm_repetition=*/ofm_repetition_45,/*tiling_params=*/tiling_params_layer_45),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_46_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_46,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/14,/*kernel_type=*/-1,layer_params_46,/*wtsL2_size=*/8704,/*kernel_iter=*/kernel_iter_46,/*ofm_repetition=*/ofm_repetition_46,/*tiling_params=*/tiling_params_layer_46),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_47_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_47,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_47,/*wtsL2_size=*/8704,/*kernel_iter=*/kernel_iter_47,/*ofm_repetition=*/ofm_repetition_47,/*tiling_params=*/tiling_params_layer_47),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_48_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_48,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/10,/*kernel_type=*/-1,layer_params_48,/*wtsL2_size=*/5632,/*kernel_iter=*/kernel_iter_48,/*ofm_repetition=*/ofm_repetition_48,/*tiling_params=*/tiling_params_layer_48),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_50,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/13,/*kernel_type=*/1,layer_params_50,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_50,/*ofm_repetition=*/ofm_repetition_50,/*tiling_params=*/tiling_params_layer_50),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_51_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_51,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_51,/*wtsL2_size=*/7936,/*kernel_iter=*/kernel_iter_51,/*ofm_repetition=*/ofm_repetition_51,/*tiling_params=*/tiling_params_layer_51),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_52_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_52,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_52,/*wtsL2_size=*/8704,/*kernel_iter=*/kernel_iter_52,/*ofm_repetition=*/ofm_repetition_52,/*tiling_params=*/tiling_params_layer_52),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_53,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_53,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_53,/*ofm_repetition=*/ofm_repetition_53,/*tiling_params=*/tiling_params_layer_53),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_54,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_54,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_54,/*ofm_repetition=*/ofm_repetition_54,/*tiling_params=*/tiling_params_layer_54),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_55,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_55,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_55,/*ofm_repetition=*/ofm_repetition_55,/*tiling_params=*/tiling_params_layer_55),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_57,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_57,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_57,/*ofm_repetition=*/ofm_repetition_57,/*tiling_params=*/tiling_params_layer_57),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_58_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_58,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/14,/*kernel_type=*/-1,layer_params_58,/*wtsL2_size=*/8704,/*kernel_iter=*/kernel_iter_58,/*ofm_repetition=*/ofm_repetition_58,/*tiling_params=*/tiling_params_layer_58),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_59_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_59,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_59,/*wtsL2_size=*/17408,/*kernel_iter=*/kernel_iter_59,/*ofm_repetition=*/ofm_repetition_59,/*tiling_params=*/tiling_params_layer_59),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_60,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_60,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_60,/*ofm_repetition=*/ofm_repetition_60,/*tiling_params=*/tiling_params_layer_60),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_61,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_61,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_61,/*ofm_repetition=*/ofm_repetition_61,/*tiling_params=*/tiling_params_layer_61),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_62,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_62,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_62,/*ofm_repetition=*/ofm_repetition_62,/*tiling_params=*/tiling_params_layer_62),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_63,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_63,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_63,/*ofm_repetition=*/ofm_repetition_63,/*tiling_params=*/tiling_params_layer_63),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_65_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_65,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/10,/*kernel_type=*/-1,layer_params_65,/*wtsL2_size=*/4096,/*kernel_iter=*/kernel_iter_65,/*ofm_repetition=*/ofm_repetition_65,/*tiling_params=*/tiling_params_layer_65),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_66,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_66,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_66,/*ofm_repetition=*/ofm_repetition_66,/*tiling_params=*/tiling_params_layer_66),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_67,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_67,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_67,/*ofm_repetition=*/ofm_repetition_67,/*tiling_params=*/tiling_params_layer_67),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_68,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_68,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_68,/*ofm_repetition=*/ofm_repetition_68,/*tiling_params=*/tiling_params_layer_68),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_69,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_69,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_69,/*ofm_repetition=*/ofm_repetition_69,/*tiling_params=*/tiling_params_layer_69),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_70_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_70,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_70,/*wtsL2_size=*/24192,/*kernel_iter=*/kernel_iter_70,/*ofm_repetition=*/ofm_repetition_70,/*tiling_params=*/tiling_params_layer_70),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_71_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_71,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_71,/*wtsL2_size=*/21504,/*kernel_iter=*/kernel_iter_71,/*ofm_repetition=*/ofm_repetition_71,/*tiling_params=*/tiling_params_layer_71),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_72,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_72,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_72,/*ofm_repetition=*/ofm_repetition_72,/*tiling_params=*/tiling_params_layer_72),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_73,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_73,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_73,/*ofm_repetition=*/ofm_repetition_73,/*tiling_params=*/tiling_params_layer_73),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_74,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_74,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_74,/*ofm_repetition=*/ofm_repetition_74,/*tiling_params=*/tiling_params_layer_74),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_75,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_75,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_75,/*ofm_repetition=*/ofm_repetition_75,/*tiling_params=*/tiling_params_layer_75),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_76_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_76,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/10,/*kernel_type=*/-1,layer_params_76,/*wtsL2_size=*/3584,/*kernel_iter=*/kernel_iter_76,/*ofm_repetition=*/ofm_repetition_76,/*tiling_params=*/tiling_params_layer_76),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_77,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_77,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_77,/*ofm_repetition=*/ofm_repetition_77,/*tiling_params=*/tiling_params_layer_77),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_78,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_78,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_78,/*ofm_repetition=*/ofm_repetition_78,/*tiling_params=*/tiling_params_layer_78),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_79,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_79,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_79,/*ofm_repetition=*/ofm_repetition_79,/*tiling_params=*/tiling_params_layer_79),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_80,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_80,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_80,/*ofm_repetition=*/ofm_repetition_80,/*tiling_params=*/tiling_params_layer_80),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_81_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_81,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/14,/*kernel_type=*/-1,layer_params_81,/*wtsL2_size=*/20736,/*kernel_iter=*/kernel_iter_81,/*ofm_repetition=*/ofm_repetition_81,/*tiling_params=*/tiling_params_layer_81),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_82_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_82,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_82,/*wtsL2_size=*/16128,/*kernel_iter=*/kernel_iter_82,/*ofm_repetition=*/ofm_repetition_82,/*tiling_params=*/tiling_params_layer_82),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_83,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_83,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_83,/*ofm_repetition=*/ofm_repetition_83,/*tiling_params=*/tiling_params_layer_83),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_84,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_84,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_84,/*ofm_repetition=*/ofm_repetition_84,/*tiling_params=*/tiling_params_layer_84),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_85,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_85,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_85,/*ofm_repetition=*/ofm_repetition_85,/*tiling_params=*/tiling_params_layer_85),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_86,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_86,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_86,/*ofm_repetition=*/ofm_repetition_86,/*tiling_params=*/tiling_params_layer_86),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_87_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_87,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/10,/*kernel_type=*/-1,layer_params_87,/*wtsL2_size=*/3072,/*kernel_iter=*/kernel_iter_87,/*ofm_repetition=*/ofm_repetition_87,/*tiling_params=*/tiling_params_layer_87),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_88,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_88,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_88,/*ofm_repetition=*/ofm_repetition_88,/*tiling_params=*/tiling_params_layer_88),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_89,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_89,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_89,/*ofm_repetition=*/ofm_repetition_89,/*tiling_params=*/tiling_params_layer_89),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_90,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_90,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_90,/*ofm_repetition=*/ofm_repetition_90,/*tiling_params=*/tiling_params_layer_90),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_91,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_91,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_91,/*ofm_repetition=*/ofm_repetition_91,/*tiling_params=*/tiling_params_layer_91),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_92_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_92,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/14,/*kernel_type=*/-1,layer_params_92,/*wtsL2_size=*/19200,/*kernel_iter=*/kernel_iter_92,/*ofm_repetition=*/ofm_repetition_92,/*tiling_params=*/tiling_params_layer_92),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_93_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_93,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_93,/*wtsL2_size=*/16128,/*kernel_iter=*/kernel_iter_93,/*ofm_repetition=*/ofm_repetition_93,/*tiling_params=*/tiling_params_layer_93),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_94,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_94,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_94,/*ofm_repetition=*/ofm_repetition_94,/*tiling_params=*/tiling_params_layer_94),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_95,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_95,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_95,/*ofm_repetition=*/ofm_repetition_95,/*tiling_params=*/tiling_params_layer_95),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_96,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_96,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_96,/*ofm_repetition=*/ofm_repetition_96,/*tiling_params=*/tiling_params_layer_96),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_97,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_97,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_97,/*ofm_repetition=*/ofm_repetition_97,/*tiling_params=*/tiling_params_layer_97),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_98_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_98,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/10,/*kernel_type=*/-1,layer_params_98,/*wtsL2_size=*/3072,/*kernel_iter=*/kernel_iter_98,/*ofm_repetition=*/ofm_repetition_98,/*tiling_params=*/tiling_params_layer_98),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_99,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_99,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_99,/*ofm_repetition=*/ofm_repetition_99,/*tiling_params=*/tiling_params_layer_99),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_100,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_100,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_100,/*ofm_repetition=*/ofm_repetition_100,/*tiling_params=*/tiling_params_layer_100),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_101,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_101,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_101,/*ofm_repetition=*/ofm_repetition_101,/*tiling_params=*/tiling_params_layer_101),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_102,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_102,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_102,/*ofm_repetition=*/ofm_repetition_102,/*tiling_params=*/tiling_params_layer_102),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_103_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_103,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/14,/*kernel_type=*/-1,layer_params_103,/*wtsL2_size=*/19200,/*kernel_iter=*/kernel_iter_103,/*ofm_repetition=*/ofm_repetition_103,/*tiling_params=*/tiling_params_layer_103),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_104_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_104,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_104,/*wtsL2_size=*/40320,/*kernel_iter=*/kernel_iter_104,/*ofm_repetition=*/ofm_repetition_104,/*tiling_params=*/tiling_params_layer_104),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_105,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_105,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_105,/*ofm_repetition=*/ofm_repetition_105,/*tiling_params=*/tiling_params_layer_105),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_106,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_106,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_106,/*ofm_repetition=*/ofm_repetition_106,/*tiling_params=*/tiling_params_layer_106),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_107,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_107,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_107,/*ofm_repetition=*/ofm_repetition_107,/*tiling_params=*/tiling_params_layer_107),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_108,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_108,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_108,/*ofm_repetition=*/ofm_repetition_108,/*tiling_params=*/tiling_params_layer_108),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_109_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_109,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/10,/*kernel_type=*/-1,layer_params_109,/*wtsL2_size=*/7680,/*kernel_iter=*/kernel_iter_109,/*ofm_repetition=*/ofm_repetition_109,/*tiling_params=*/tiling_params_layer_109),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_110,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_110,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_110,/*ofm_repetition=*/ofm_repetition_110,/*tiling_params=*/tiling_params_layer_110),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_111,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_111,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_111,/*ofm_repetition=*/ofm_repetition_111,/*tiling_params=*/tiling_params_layer_111),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_112,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_112,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_112,/*ofm_repetition=*/ofm_repetition_112,/*tiling_params=*/tiling_params_layer_112),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_113,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_113,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_113,/*ofm_repetition=*/ofm_repetition_113,/*tiling_params=*/tiling_params_layer_113),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_115,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/13,/*kernel_type=*/1,layer_params_115,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_115,/*ofm_repetition=*/ofm_repetition_115,/*tiling_params=*/tiling_params_layer_115),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_116_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_116,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_116,/*wtsL2_size=*/63488,/*kernel_iter=*/kernel_iter_116,/*ofm_repetition=*/ofm_repetition_116,/*tiling_params=*/tiling_params_layer_116),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_117_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_117,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_117,/*wtsL2_size=*/63488,/*kernel_iter=*/kernel_iter_117,/*ofm_repetition=*/ofm_repetition_117,/*tiling_params=*/tiling_params_layer_117),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_118,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_118,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_118,/*ofm_repetition=*/ofm_repetition_118,/*tiling_params=*/tiling_params_layer_118),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_119,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_119,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_119,/*ofm_repetition=*/ofm_repetition_119,/*tiling_params=*/tiling_params_layer_119),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_120,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_120,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_120,/*ofm_repetition=*/ofm_repetition_120,/*tiling_params=*/tiling_params_layer_120),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_122,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_122,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_122,/*ofm_repetition=*/ofm_repetition_122,/*tiling_params=*/tiling_params_layer_122),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_123_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_123,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_123,/*wtsL2_size=*/64000,/*kernel_iter=*/kernel_iter_123,/*ofm_repetition=*/ofm_repetition_123,/*tiling_params=*/tiling_params_layer_123),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_124_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_124,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_124,/*wtsL2_size=*/91392,/*kernel_iter=*/kernel_iter_124,/*ofm_repetition=*/ofm_repetition_124,/*tiling_params=*/tiling_params_layer_124),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_125,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_125,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_125,/*ofm_repetition=*/ofm_repetition_125,/*tiling_params=*/tiling_params_layer_125),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_126,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_126,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_126,/*ofm_repetition=*/ofm_repetition_126,/*tiling_params=*/tiling_params_layer_126),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_127,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_127,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_127,/*ofm_repetition=*/ofm_repetition_127,/*tiling_params=*/tiling_params_layer_127),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_128,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_128,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_128,/*ofm_repetition=*/ofm_repetition_128,/*tiling_params=*/tiling_params_layer_128),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_129_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_129,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/10,/*kernel_type=*/-1,layer_params_129,/*wtsL2_size=*/10752,/*kernel_iter=*/kernel_iter_129,/*ofm_repetition=*/ofm_repetition_129,/*tiling_params=*/tiling_params_layer_129),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_130,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_130,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_130,/*ofm_repetition=*/ofm_repetition_130,/*tiling_params=*/tiling_params_layer_130),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_131,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_131,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_131,/*ofm_repetition=*/ofm_repetition_131,/*tiling_params=*/tiling_params_layer_131),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_132,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_132,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_132,/*ofm_repetition=*/ofm_repetition_132,/*tiling_params=*/tiling_params_layer_132),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_133,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_133,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_133,/*ofm_repetition=*/ofm_repetition_133,/*tiling_params=*/tiling_params_layer_133),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_135,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/13,/*kernel_type=*/1,layer_params_135,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_135,/*ofm_repetition=*/ofm_repetition_135,/*tiling_params=*/tiling_params_layer_135),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_136_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_136,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_136,/*wtsL2_size=*/134400,/*kernel_iter=*/kernel_iter_136,/*ofm_repetition=*/ofm_repetition_136,/*tiling_params=*/tiling_params_layer_136),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_137_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_137,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_137,/*wtsL2_size=*/121088,/*kernel_iter=*/kernel_iter_137,/*ofm_repetition=*/ofm_repetition_137,/*tiling_params=*/tiling_params_layer_137),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_138,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_138,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_138,/*ofm_repetition=*/ofm_repetition_138,/*tiling_params=*/tiling_params_layer_138),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_139,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_139,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_139,/*ofm_repetition=*/ofm_repetition_139,/*tiling_params=*/tiling_params_layer_139),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_140,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_140,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_140,/*ofm_repetition=*/ofm_repetition_140,/*tiling_params=*/tiling_params_layer_140),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_142,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_142,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_142,/*ofm_repetition=*/ofm_repetition_142,/*tiling_params=*/tiling_params_layer_142),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_143_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_143,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/14,/*kernel_type=*/-1,layer_params_143,/*wtsL2_size=*/89600,/*kernel_iter=*/kernel_iter_143,/*ofm_repetition=*/ofm_repetition_143,/*tiling_params=*/tiling_params_layer_143),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_144_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_144,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_144,/*wtsL2_size=*/91392,/*kernel_iter=*/kernel_iter_144,/*ofm_repetition=*/ofm_repetition_144,/*tiling_params=*/tiling_params_layer_144),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_145,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_145,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_145,/*ofm_repetition=*/ofm_repetition_145,/*tiling_params=*/tiling_params_layer_145),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_146,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_146,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_146,/*ofm_repetition=*/ofm_repetition_146,/*tiling_params=*/tiling_params_layer_146),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_147,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_147,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_147,/*ofm_repetition=*/ofm_repetition_147,/*tiling_params=*/tiling_params_layer_147),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_148,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_148,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_148,/*ofm_repetition=*/ofm_repetition_148,/*tiling_params=*/tiling_params_layer_148),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_149_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_149,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/10,/*kernel_type=*/-1,layer_params_149,/*wtsL2_size=*/75264,/*kernel_iter=*/kernel_iter_149,/*ofm_repetition=*/ofm_repetition_149,/*tiling_params=*/tiling_params_layer_149),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_150,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_150,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_150,/*ofm_repetition=*/ofm_repetition_150,/*tiling_params=*/tiling_params_layer_150),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_151,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_151,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_151,/*ofm_repetition=*/ofm_repetition_151,/*tiling_params=*/tiling_params_layer_151),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_152,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_152,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_152,/*ofm_repetition=*/ofm_repetition_152,/*tiling_params=*/tiling_params_layer_152),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_153,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_153,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_153,/*ofm_repetition=*/ofm_repetition_153,/*tiling_params=*/tiling_params_layer_153),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_155,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/13,/*kernel_type=*/1,layer_params_155,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_155,/*ofm_repetition=*/ofm_repetition_155,/*tiling_params=*/tiling_params_layer_155),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_156_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_156,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_156,/*wtsL2_size=*/134400,/*kernel_iter=*/kernel_iter_156,/*ofm_repetition=*/ofm_repetition_156,/*tiling_params=*/tiling_params_layer_156),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_157_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_157,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_157,/*wtsL2_size=*/121088,/*kernel_iter=*/kernel_iter_157,/*ofm_repetition=*/ofm_repetition_157,/*tiling_params=*/tiling_params_layer_157),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_158,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_158,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_158,/*ofm_repetition=*/ofm_repetition_158,/*tiling_params=*/tiling_params_layer_158),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_159,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_159,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_159,/*ofm_repetition=*/ofm_repetition_159,/*tiling_params=*/tiling_params_layer_159),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_160,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_160,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_160,/*ofm_repetition=*/ofm_repetition_160,/*tiling_params=*/tiling_params_layer_160),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_162,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_162,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_162,/*ofm_repetition=*/ofm_repetition_162,/*tiling_params=*/tiling_params_layer_162),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_163_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_163,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_163,/*wtsL2_size=*/120960,/*kernel_iter=*/kernel_iter_163,/*ofm_repetition=*/ofm_repetition_163,/*tiling_params=*/tiling_params_layer_163),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_164_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_164,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_164,/*wtsL2_size=*/161280,/*kernel_iter=*/kernel_iter_164,/*ofm_repetition=*/ofm_repetition_164,/*tiling_params=*/tiling_params_layer_164),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_165,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_165,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_165,/*ofm_repetition=*/ofm_repetition_165,/*tiling_params=*/tiling_params_layer_165),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_166,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_166,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_166,/*ofm_repetition=*/ofm_repetition_166,/*tiling_params=*/tiling_params_layer_166),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_167,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_167,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_167,/*ofm_repetition=*/ofm_repetition_167,/*tiling_params=*/tiling_params_layer_167),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_168,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_168,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_168,/*ofm_repetition=*/ofm_repetition_168,/*tiling_params=*/tiling_params_layer_168),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_169_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_169,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/10,/*kernel_type=*/-1,layer_params_169,/*wtsL2_size=*/107520,/*kernel_iter=*/kernel_iter_169,/*ofm_repetition=*/ofm_repetition_169,/*tiling_params=*/tiling_params_layer_169),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_170,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_170,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_170,/*ofm_repetition=*/ofm_repetition_170,/*tiling_params=*/tiling_params_layer_170),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_171,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_171,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_171,/*ofm_repetition=*/ofm_repetition_171,/*tiling_params=*/tiling_params_layer_171),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_172,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_172,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_172,/*ofm_repetition=*/ofm_repetition_172,/*tiling_params=*/tiling_params_layer_172),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_173,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_173,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_173,/*ofm_repetition=*/ofm_repetition_173,/*tiling_params=*/tiling_params_layer_173),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_175,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/13,/*kernel_type=*/1,layer_params_175,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_175,/*ofm_repetition=*/ofm_repetition_175,/*tiling_params=*/tiling_params_layer_175),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_176_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_176,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_176,/*wtsL2_size=*/250880,/*kernel_iter=*/kernel_iter_176,/*ofm_repetition=*/ofm_repetition_176,/*tiling_params=*/tiling_params_layer_176),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_177_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_177,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_177,/*wtsL2_size=*/241920,/*kernel_iter=*/kernel_iter_177,/*ofm_repetition=*/ofm_repetition_177,/*tiling_params=*/tiling_params_layer_177),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_178,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_178,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_178,/*ofm_repetition=*/ofm_repetition_178,/*tiling_params=*/tiling_params_layer_178),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_179,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_179,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_179,/*ofm_repetition=*/ofm_repetition_179,/*tiling_params=*/tiling_params_layer_179),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_180,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_180,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_180,/*ofm_repetition=*/ofm_repetition_180,/*tiling_params=*/tiling_params_layer_180),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_182,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_182,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_182,/*ofm_repetition=*/ofm_repetition_182,/*tiling_params=*/tiling_params_layer_182),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_183_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_183,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/14,/*kernel_type=*/-1,layer_params_183,/*wtsL2_size=*/200448,/*kernel_iter=*/kernel_iter_183,/*ofm_repetition=*/ofm_repetition_183,/*tiling_params=*/tiling_params_layer_183),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_184_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_184,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_184,/*wtsL2_size=*/161280,/*kernel_iter=*/kernel_iter_184,/*ofm_repetition=*/ofm_repetition_184,/*tiling_params=*/tiling_params_layer_184),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_185,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_185,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_185,/*ofm_repetition=*/ofm_repetition_185,/*tiling_params=*/tiling_params_layer_185),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_186,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_186,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_186,/*ofm_repetition=*/ofm_repetition_186,/*tiling_params=*/tiling_params_layer_186),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_187,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_187,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_187,/*ofm_repetition=*/ofm_repetition_187,/*tiling_params=*/tiling_params_layer_187),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_188,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_188,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_188,/*ofm_repetition=*/ofm_repetition_188,/*tiling_params=*/tiling_params_layer_188),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_189_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_189,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/10,/*kernel_type=*/-1,layer_params_189,/*wtsL2_size=*/107520,/*kernel_iter=*/kernel_iter_189,/*ofm_repetition=*/ofm_repetition_189,/*tiling_params=*/tiling_params_layer_189),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_190,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_190,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_190,/*ofm_repetition=*/ofm_repetition_190,/*tiling_params=*/tiling_params_layer_190),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_191,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_191,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_191,/*ofm_repetition=*/ofm_repetition_191,/*tiling_params=*/tiling_params_layer_191),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_192,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_192,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_192,/*ofm_repetition=*/ofm_repetition_192,/*tiling_params=*/tiling_params_layer_192),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_193,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_193,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_193,/*ofm_repetition=*/ofm_repetition_193,/*tiling_params=*/tiling_params_layer_193),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_195,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/13,/*kernel_type=*/1,layer_params_195,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_195,/*ofm_repetition=*/ofm_repetition_195,/*tiling_params=*/tiling_params_layer_195),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_196_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_196,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_196,/*wtsL2_size=*/250880,/*kernel_iter=*/kernel_iter_196,/*ofm_repetition=*/ofm_repetition_196,/*tiling_params=*/tiling_params_layer_196),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_197_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_197,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_197,/*wtsL2_size=*/241920,/*kernel_iter=*/kernel_iter_197,/*ofm_repetition=*/ofm_repetition_197,/*tiling_params=*/tiling_params_layer_197),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_198,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_198,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_198,/*ofm_repetition=*/ofm_repetition_198,/*tiling_params=*/tiling_params_layer_198),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_199,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_199,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_199,/*ofm_repetition=*/ofm_repetition_199,/*tiling_params=*/tiling_params_layer_199),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_200,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_200,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_200,/*ofm_repetition=*/ofm_repetition_200,/*tiling_params=*/tiling_params_layer_200),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_202,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_202,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_202,/*ofm_repetition=*/ofm_repetition_202,/*tiling_params=*/tiling_params_layer_202),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_203_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_203,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/14,/*kernel_type=*/-1,layer_params_203,/*wtsL2_size=*/200448,/*kernel_iter=*/kernel_iter_203,/*ofm_repetition=*/ofm_repetition_203,/*tiling_params=*/tiling_params_layer_203),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_204_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_204,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_204,/*wtsL2_size=*/161280,/*kernel_iter=*/kernel_iter_204,/*ofm_repetition=*/ofm_repetition_204,/*tiling_params=*/tiling_params_layer_204),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_205,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/2,layer_params_205,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_205,/*ofm_repetition=*/ofm_repetition_205,/*tiling_params=*/tiling_params_layer_205),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_206,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_206,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_206,/*ofm_repetition=*/ofm_repetition_206,/*tiling_params=*/tiling_params_layer_206),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_207,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/1,layer_params_207,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_207,/*ofm_repetition=*/ofm_repetition_207,/*tiling_params=*/tiling_params_layer_207),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_208,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_208,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_208,/*ofm_repetition=*/ofm_repetition_208,/*tiling_params=*/tiling_params_layer_208),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_210,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/13,/*kernel_type=*/1,layer_params_210,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_210,/*ofm_repetition=*/ofm_repetition_210,/*tiling_params=*/tiling_params_layer_210),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_211_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_211,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_211,/*wtsL2_size=*/125440,/*kernel_iter=*/kernel_iter_211,/*ofm_repetition=*/ofm_repetition_211,/*tiling_params=*/tiling_params_layer_211),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_212,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/4,layer_params_212,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_212,/*ofm_repetition=*/ofm_repetition_212,/*tiling_params=*/tiling_params_layer_212),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_214_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_214,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/14,/*kernel_type=*/-1,layer_params_214,/*wtsL2_size=*/128000,/*kernel_iter=*/kernel_iter_214,/*ofm_repetition=*/ofm_repetition_214,/*tiling_params=*/tiling_params_layer_214),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_218_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_218,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_218,/*wtsL2_size=*/151552,/*kernel_iter=*/kernel_iter_218,/*ofm_repetition=*/ofm_repetition_218,/*tiling_params=*/tiling_params_layer_218),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_219,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/4,layer_params_219,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_219,/*ofm_repetition=*/ofm_repetition_219,/*tiling_params=*/tiling_params_layer_219),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_221,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/3,layer_params_221,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_221,/*ofm_repetition=*/ofm_repetition_221,/*tiling_params=*/tiling_params_layer_221),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_222,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_222,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_222,/*ofm_repetition=*/ofm_repetition_222,/*tiling_params=*/tiling_params_layer_222),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_224,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_224,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_224,/*ofm_repetition=*/ofm_repetition_224,/*tiling_params=*/tiling_params_layer_224),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_226_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_226,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_226,/*wtsL2_size=*/75776,/*kernel_iter=*/kernel_iter_226,/*ofm_repetition=*/ofm_repetition_226,/*tiling_params=*/tiling_params_layer_226),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_227,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/5,layer_params_227,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_227,/*ofm_repetition=*/ofm_repetition_227,/*tiling_params=*/tiling_params_layer_227),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_228,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_228,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_228,/*ofm_repetition=*/ofm_repetition_228,/*tiling_params=*/tiling_params_layer_228),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_229,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/1,layer_params_229,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_229,/*ofm_repetition=*/ofm_repetition_229,/*tiling_params=*/tiling_params_layer_229),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_233,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/7,/*kernel_type=*/-1,layer_params_233,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_233,/*ofm_repetition=*/ofm_repetition_233,/*tiling_params=*/tiling_params_layer_233),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_234,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/7,/*kernel_type=*/-1,layer_params_234,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_234,/*ofm_repetition=*/ofm_repetition_234,/*tiling_params=*/tiling_params_layer_234),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_235,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/7,/*kernel_type=*/-1,layer_params_235,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_235,/*ofm_repetition=*/ofm_repetition_235,/*tiling_params=*/tiling_params_layer_235),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_237_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_237,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_237,/*wtsL2_size=*/208384,/*kernel_iter=*/kernel_iter_237,/*ofm_repetition=*/ofm_repetition_237,/*tiling_params=*/tiling_params_layer_237),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_241_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_241,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_241,/*wtsL2_size=*/94720,/*kernel_iter=*/kernel_iter_241,/*ofm_repetition=*/ofm_repetition_241,/*tiling_params=*/tiling_params_layer_241),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_242,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/4,layer_params_242,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_242,/*ofm_repetition=*/ofm_repetition_242,/*tiling_params=*/tiling_params_layer_242),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_244,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/3,layer_params_244,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_244,/*ofm_repetition=*/ofm_repetition_244,/*tiling_params=*/tiling_params_layer_244),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_245,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_245,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_245,/*ofm_repetition=*/ofm_repetition_245,/*tiling_params=*/tiling_params_layer_245),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_247,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_247,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_247,/*ofm_repetition=*/ofm_repetition_247,/*tiling_params=*/tiling_params_layer_247),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_249_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_249,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_249,/*wtsL2_size=*/47360,/*kernel_iter=*/kernel_iter_249,/*ofm_repetition=*/ofm_repetition_249,/*tiling_params=*/tiling_params_layer_249),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_250,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/5,layer_params_250,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_250,/*ofm_repetition=*/ofm_repetition_250,/*tiling_params=*/tiling_params_layer_250),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_251,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_251,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_251,/*ofm_repetition=*/ofm_repetition_251,/*tiling_params=*/tiling_params_layer_251),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_252,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/1,layer_params_252,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_252,/*ofm_repetition=*/ofm_repetition_252,/*tiling_params=*/tiling_params_layer_252),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_257_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_257,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_257,/*wtsL2_size=*/66304,/*kernel_iter=*/kernel_iter_257,/*ofm_repetition=*/ofm_repetition_257,/*tiling_params=*/tiling_params_layer_257),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_261_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_261,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_261,/*wtsL2_size=*/28416,/*kernel_iter=*/kernel_iter_261,/*ofm_repetition=*/ofm_repetition_261,/*tiling_params=*/tiling_params_layer_261),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_262,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/4,layer_params_262,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_262,/*ofm_repetition=*/ofm_repetition_262,/*tiling_params=*/tiling_params_layer_262),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_264,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/3,layer_params_264,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_264,/*ofm_repetition=*/ofm_repetition_264,/*tiling_params=*/tiling_params_layer_264),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_265,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_265,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_265,/*ofm_repetition=*/ofm_repetition_265,/*tiling_params=*/tiling_params_layer_265),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_267,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_267,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_267,/*ofm_repetition=*/ofm_repetition_267,/*tiling_params=*/tiling_params_layer_267),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_269_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_269,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_269,/*wtsL2_size=*/12160,/*kernel_iter=*/kernel_iter_269,/*ofm_repetition=*/ofm_repetition_269,/*tiling_params=*/tiling_params_layer_269),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_270,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/5,layer_params_270,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_270,/*ofm_repetition=*/ofm_repetition_270,/*tiling_params=*/tiling_params_layer_270),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_271,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_271,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_271,/*ofm_repetition=*/ofm_repetition_271,/*tiling_params=*/tiling_params_layer_271),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_272,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/1,layer_params_272,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_272,/*ofm_repetition=*/ofm_repetition_272,/*tiling_params=*/tiling_params_layer_272),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_276_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_276,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_276,/*wtsL2_size=*/18944,/*kernel_iter=*/kernel_iter_276,/*ofm_repetition=*/ofm_repetition_276,/*tiling_params=*/tiling_params_layer_276),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_280_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_280,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_280,/*wtsL2_size=*/9472,/*kernel_iter=*/kernel_iter_280,/*ofm_repetition=*/ofm_repetition_280,/*tiling_params=*/tiling_params_layer_280),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_281,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/4,layer_params_281,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_281,/*ofm_repetition=*/ofm_repetition_281,/*tiling_params=*/tiling_params_layer_281),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_283,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/3,layer_params_283,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_283,/*ofm_repetition=*/ofm_repetition_283,/*tiling_params=*/tiling_params_layer_283),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_284,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_284,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_284,/*ofm_repetition=*/ofm_repetition_284,/*tiling_params=*/tiling_params_layer_284),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_286,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_286,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_286,/*ofm_repetition=*/ofm_repetition_286,/*tiling_params=*/tiling_params_layer_286),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_288_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_288,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_288,/*wtsL2_size=*/9472,/*kernel_iter=*/kernel_iter_288,/*ofm_repetition=*/ofm_repetition_288,/*tiling_params=*/tiling_params_layer_288),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_289,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/5,layer_params_289,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_289,/*ofm_repetition=*/ofm_repetition_289,/*tiling_params=*/tiling_params_layer_289),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_290,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/2,layer_params_290,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_290,/*ofm_repetition=*/ofm_repetition_290,/*tiling_params=*/tiling_params_layer_290),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_291,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/1,layer_params_291,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_291,/*ofm_repetition=*/ofm_repetition_291,/*tiling_params=*/tiling_params_layer_291),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_295_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_295,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_295,/*wtsL2_size=*/12160,/*kernel_iter=*/kernel_iter_295,/*ofm_repetition=*/ofm_repetition_295,/*tiling_params=*/tiling_params_layer_295),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_296_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_296,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_296,/*wtsL2_size=*/4736,/*kernel_iter=*/kernel_iter_296,/*ofm_repetition=*/ofm_repetition_296,/*tiling_params=*/tiling_params_layer_296),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_297_l2_wts,/*wtsShimDMACount=*/2,/*ofm=*/l2_297,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/0,/*kernel_type=*/-1,layer_params_297,/*wtsL2_size=*/2176,/*kernel_iter=*/kernel_iter_297,/*ofm_repetition=*/ofm_repetition_297,/*tiling_params=*/tiling_params_layer_297),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/L2_OFM_Buffer_layer_299,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_299,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_299,/*ofm_repetition=*/ofm_repetition_299,/*tiling_params=*/tiling_params_layer_299),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/l2_301,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/8,/*kernel_type=*/1,layer_params_301,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_301,/*ofm_repetition=*/ofm_repetition_301,/*tiling_params=*/tiling_params_layer_301),
+single_layer_overlay(/*is_ofm_int8=*/false,/*wts=*/Layer_l2_wts_dummy,/*wtsShimDMACount=*/2,/*ofm=*/L2_OFM_Buffer_layer_302,ofm_dummy_compareop,/*predecessor_idx=*/0,/*super_kernel_mode=*/5,/*kernel_type=*/3,layer_params_302,/*wtsL2_size=*/0,/*kernel_iter=*/kernel_iter_302,/*ofm_repetition=*/ofm_repetition_302,/*tiling_params=*/tiling_params_layer_302)
+};
+
+FlexMLGraph() : 
+templated_graph_2(l2l3_1_spill, l2l3_2_spill, params_graph_2), 
+templated_graph_3(l2l3_2_spill, l2l3_3_spill, l2l3_scratch_0_3_spill, params_graph_3), 
+templated_graph_4(l2l3_3_spill, l2l3_4_spill, params_graph_4), 
+templated_graph_5(l2l3_4_spill, l2l3_5_spill, l2l3_scratch_0_5_spill, params_graph_5), 
+templated_graph_17(l2l3_16_spill, l2l3_17_spill, l2l3_scratch_0_17_spill, params_graph_17), 
+templated_graph_21(l2l3_20_spill, l2l3_21_spill, l2l3_scratch_0_21_spill, params_graph_21), 
+templated_graph_25(l2l3_24_spill, l2l3_25_spill, params_graph_25), 
+templated_graph_32(l2l3_31_spill, l2l3_scratch_0_32_spill, l2l3_scratch_1_32_spill, l2l3_32_spill, params_graph_32), 
+templated_graph_37(l2l3_36_spill, l2l3_37_spill, params_graph_37), 
+templated_graph_44(l2l3_43_spill, l2l3_scratch_0_44_spill, l2l3_scratch_1_44_spill, l2l3_44_spill, params_graph_44), 
+templated_graph_49(l2l3_48_spill, l2l3_49_spill, params_graph_49), 
+templated_graph_56(l2l3_55_spill, l2l3_scratch_0_56_spill, l2l3_scratch_1_56_spill, l2l3_56_spill, params_graph_56), 
+templated_graph_64(l2l3_63_spill, l2l3_64_spill, l2l3_scratch_0_64_spill, params_graph_64), 
+templated_graph_114(l2l3_113_spill, l2l3_114_spill, params_graph_114), 
+templated_graph_121(l2l3_120_spill, l2l3_scratch_0_121_spill, l2l3_scratch_1_121_spill, l2l3_121_spill, params_graph_121), 
+templated_graph_134(l2l3_133_spill, l2l3_134_spill, params_graph_134), 
+templated_graph_141(l2l3_140_spill, l2l3_scratch_0_141_spill, l2l3_scratch_1_141_spill, l2l3_141_spill, params_graph_141), 
+templated_graph_154(l2l3_153_spill, l2l3_154_spill, params_graph_154), 
+templated_graph_161(l2l3_160_spill, l2l3_scratch_0_161_spill, l2l3_scratch_1_161_spill, l2l3_161_spill, params_graph_161), 
+templated_graph_174(l2l3_173_spill, l2l3_174_spill, params_graph_174), 
+templated_graph_181(l2l3_180_spill, l2l3_scratch_0_181_spill, l2l3_scratch_1_181_spill, l2l3_181_spill, params_graph_181), 
+templated_graph_194(l2l3_193_spill, l2l3_194_spill, params_graph_194), 
+templated_graph_201(l2l3_200_spill, l2l3_scratch_0_201_spill, l2l3_scratch_1_201_spill, l2l3_201_spill, params_graph_201), 
+templated_graph_209(l2l3_208_spill, l2l3_209_spill, params_graph_209), 
+templated_graph_213(l2l3_212_spill, l2l3_scratch_0_213_spill, l2l3_scratch_1_213_spill, l2l3_213_spill, params_graph_213), 
+templated_graph_215(l2l3_214_spill, l2l3_215_spill, params_graph_215), 
+templated_graph_216(l2l3_214_spill, l2l3_216_spill, params_graph_216), 
+templated_graph_220(l2l3_219_spill, l2l3_220_spill, params_graph_220), 
+templated_graph_223(l2l3_219_spill, l2l3_223_spill, params_graph_223), 
+templated_graph_231(spill_L3_Concat_Buffer_layer_230, l2l3_231_spill, params_graph_231), 
+templated_graph_232(l2l3_231_spill, l2l3_232_spill, params_graph_232), 
+templated_graph_238(l2l3_237_spill, l2l3_238_spill, params_graph_238), 
+templated_graph_239(l2l3_237_spill, l2l3_239_spill, params_graph_239), 
+templated_graph_243(l2l3_242_spill, l2l3_243_spill, params_graph_243), 
+templated_graph_246(l2l3_242_spill, l2l3_246_spill, params_graph_246), 
+templated_graph_254(spill_L3_Concat_Buffer_layer_253, l2l3_254_spill, params_graph_254), 
+templated_graph_255(l2l3_254_spill, l2l3_255_spill, params_graph_255), 
+templated_graph_258(l2l3_257_spill, l2l3_258_spill, params_graph_258), 
+templated_graph_259(l2l3_257_spill, l2l3_259_spill, params_graph_259), 
+templated_graph_260(l2l3_259_spill, ifm_ddr_2, l2l3_260_spill, params_graph_260), 
+templated_graph_263(l2l3_262_spill, l2l3_263_spill, params_graph_263), 
+templated_graph_266(l2l3_262_spill, l2l3_266_spill, params_graph_266), 
+templated_graph_268(l2l3_259_spill, l2l3_267_spill, l2l3_268_spill, params_graph_268), 
+templated_graph_273(l2l3_258_spill, ofm_ddr_2_l2l3_272_spill, l2l3_273_spill, params_graph_273), 
+templated_graph_274(l2l3_273_spill, spill_L3_Concat_Buffer_layer_275, params_graph_274), 
+templated_graph_277(l2l3_276_spill, l2l3_277_spill, params_graph_277), 
+templated_graph_278(l2l3_276_spill, l2l3_278_spill, params_graph_278), 
+templated_graph_282(l2l3_281_spill, l2l3_282_spill, params_graph_282), 
+templated_graph_285(l2l3_281_spill, l2l3_285_spill, params_graph_285), 
+templated_graph_293(spill_L3_Concat_Buffer_layer_292, spill_L3_Concat_Buffer_layer_294, params_graph_293), 
+templated_graph_298(l2l3_297_spill, l2l3_298_spill, params_graph_298), 
+templated_graph_300(l2l3_297_spill, l2l3_300_spill, params_graph_300) {
+
+//L2 Buffer repetition count
+repetition_count(L2_CONST_IFM_Buffer_for_input5_0_port1) = 9;
+repetition_count(L2_IFM_Buffer_from_layer_5_for_layer_6_port0) = 9;
+repetition_count(l2_6) = 9;
+repetition_count(L2_CONST_IFM_Buffer_for_input4_0_port1) = 9;
+repetition_count(L2_IFM_Buffer_from_layer_6_for_layer_7_port0) = 9;
+repetition_count(l2_7) = 9;
+repetition_count(L2_IFM_Buffer_from_layer_7_for_layer_8_port0) = 3;
+repetition_count(l2_8) = 3;
+repetition_count(L2_IFM_Buffer_from_layer_9_for_layer_10_port0) = 2;
+repetition_count(l2_10) = 2;
+repetition_count(L2_IFM_Buffer_from_layer_8_for_layer_12_port0) = 3;
+repetition_count(L2_IFM_Buffer_from_layer_11_for_layer_12_port1) = 3;
+repetition_count(l2_12) = 3;
+repetition_count(L2_IFM_Buffer_from_layer_12_for_layer_14_port1) = 2;
+repetition_count(L2_IFM_Buffer_from_layer_13_for_layer_14_port0) = 2;
+repetition_count(l2_14) = 2;
+repetition_count(L2_IFM_Buffer_from_layer_14_for_layer_15_port0) = 5;
+repetition_count(l2_15) = 5;
+repetition_count(L2_IFM_Buffer_from_layer_15_for_layer_16_port0) = 6;
+repetition_count(l2_16) = 6;
+repetition_count(L2_IFM_Buffer_from_layer_19_for_layer_20_port0) = 2;
+repetition_count(l2_20) = 2;
+repetition_count(L2_IFM_Buffer_from_layer_59_for_layer_63_port0) = 2;
+repetition_count(L2_IFM_Buffer_from_layer_62_for_layer_63_port1) = 2;
+repetition_count(l2_63) = 2;
+repetition_count(L2_IFM_Buffer_from_layer_164_for_layer_168_port0) = 2;
+repetition_count(L2_IFM_Buffer_from_layer_167_for_layer_168_port1) = 2;
+repetition_count(l2_168) = 2;
+repetition_count(L2_IFM_Buffer_from_layer_169_for_layer_173_port0) = 2;
+repetition_count(L2_IFM_Buffer_from_layer_172_for_layer_173_port1) = 2;
+repetition_count(l2_173) = 2;
+repetition_count(L2_IFM_Buffer_from_layer_184_for_layer_188_port0) = 2;
+repetition_count(L2_IFM_Buffer_from_layer_187_for_layer_188_port1) = 2;
+repetition_count(l2_188) = 2;
+repetition_count(L2_IFM_Buffer_from_layer_189_for_layer_193_port0) = 2;
+repetition_count(L2_IFM_Buffer_from_layer_192_for_layer_193_port1) = 2;
+repetition_count(l2_193) = 2;
+repetition_count(L2_IFM_Buffer_from_layer_204_for_layer_208_port0) = 2;
+repetition_count(L2_IFM_Buffer_from_layer_207_for_layer_208_port1) = 2;
+repetition_count(l2_208) = 2;
+repetition_count(L2_IFM_Buffer_from_layer_5_for_layer_233_port0) = 3;
+repetition_count(l2_233) = 3;
+repetition_count(L2_IFM_Buffer_from_layer_275_for_layer_276_port0) = 5;
+repetition_count(l2_276) = 5;
+repetition_count(L2_IFM_Buffer_from_layer_279_for_layer_280_port0) = 3;
+repetition_count(l2_280) = 3;
+repetition_count(L2_IFM_Buffer_from_layer_280_for_layer_281_port0) = 3;
+repetition_count(l2_281) = 3;
+repetition_count(L2_CONST_IFM_Buffer_for_input0_0_port0) = 3;
+repetition_count(L2_IFM_Buffer_from_layer_282_for_layer_283_port1) = 3;
+repetition_count(l2_283) = 3;
+repetition_count(L2_IFM_Buffer_for_input1_1_port1) = 3;
+repetition_count(L2_IFM_Buffer_from_layer_283_for_layer_284_port0) = 3;
+repetition_count(l2_284) = 3;
+repetition_count(L2_IFM_Buffer_for_input1_2_port1) = 3;
+repetition_count(L2_IFM_Buffer_from_layer_285_for_layer_286_port0) = 3;
+repetition_count(l2_286) = 3;
+repetition_count(L2_IFM_Buffer_from_layer_287_for_layer_288_port0) = 3;
+repetition_count(l2_288) = 3;
+repetition_count(L2_IFM_Buffer_from_layer_282_for_layer_290_port0) = 3;
+repetition_count(L2_IFM_Buffer_from_layer_289_for_layer_290_port1) = 3;
+repetition_count(l2_290) = 3;
+repetition_count(L2_IFM_Buffer_from_layer_284_for_layer_291_port0) = 3;
+repetition_count(L2_IFM_Buffer_from_layer_290_for_layer_291_port1) = 3;
+repetition_count(l2_291) = 3;
+repetition_count(L2_IFM_Buffer_from_layer_294_for_layer_295_port0) = 12;
+repetition_count(l2_295) = 12;
+repetition_count(L2_IFM_Buffer_from_layer_295_for_layer_296_port0) = 9;
+repetition_count(l2_296) = 9;
+repetition_count(L2_IFM_Buffer_from_layer_296_for_layer_297_port0) = 9;
+repetition_count(l2_297) = 9;
+repetition_count(L2_IFM_Buffer_from_layer_298_for_layer_299_port0) = 9;
+repetition_count(L2_OFM_Buffer_layer_299) = 9;
+repetition_count(L2_IFM_Buffer_from_layer_5_for_layer_301_port1) = 9;
+repetition_count(L2_IFM_Buffer_from_layer_300_for_layer_301_port0) = 9;
+repetition_count(l2_301) = 9;
+repetition_count(L2_IFM_Buffer_from_layer_301_for_layer_302_port0) = 9;
+repetition_count(L2_OFM_Buffer_layer_302) = 9;
+location<buffer>(L2_IFM_Buffer_for_input0_0_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_for_input0_0_port0) =1;
+
+location<buffer>(l2_1) = { address(0, 0, 471040)};
+num_buffers(l2_1) =1;
+
+location<buffer>(L2_CONST_IFM_Buffer_for_input5_0_port1) = { address(2, 0, 319488), address(2, 0, 421888)};
+num_buffers(L2_CONST_IFM_Buffer_for_input5_0_port1) =2;
+
+location<buffer>(L2_IFM_Buffer_from_layer_5_for_layer_6_port0) = { address(2, 0, 114688), address(2, 0, 217088)};
+num_buffers(L2_IFM_Buffer_from_layer_5_for_layer_6_port0) =2;
+
+location<buffer>(l2_6) = { address(0, 0, 0), address(0, 0, 409600)};
+num_buffers(l2_6) =2;
+
+location<buffer>(L2_CONST_IFM_Buffer_for_input4_0_port1) = { address(2, 0, 319488), address(2, 0, 421888)};
+num_buffers(L2_CONST_IFM_Buffer_for_input4_0_port1) =2;
+
+location<buffer>(L2_IFM_Buffer_from_layer_6_for_layer_7_port0) = { address(2, 0, 114688), address(2, 0, 217088)};
+num_buffers(L2_IFM_Buffer_from_layer_6_for_layer_7_port0) =2;
+
+location<buffer>(l2_7) = { address(0, 0, 0), address(0, 0, 409600)};
+num_buffers(l2_7) =2;
+
+location<buffer>(L2_IFM_Buffer_from_layer_7_for_layer_8_port0) = { address(1, 0, 423936), address(2, 0, 211968)};
+num_buffers(L2_IFM_Buffer_from_layer_7_for_layer_8_port0) =2;
+
+location<buffer>(l2_8) = { address(0, 0, 0), address(0, 0, 327680)};
+num_buffers(l2_8) =2;
+
+location<buffer>(L2_IFM_Buffer_from_layer_8_for_layer_9_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_8_for_layer_9_port0) =1;
+
+location<buffer>(l2_9) = { address(0, 0, 460800)};
+num_buffers(l2_9) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_9_for_layer_10_port0) = { address(2, 0, 293888)};
+num_buffers(L2_IFM_Buffer_from_layer_9_for_layer_10_port0) =1;
+
+location<buffer>(l2_10) = { address(0, 0, 0)};
+num_buffers(l2_10) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_10_for_layer_11_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_10_for_layer_11_port0) =1;
+
+location<buffer>(l2_11) = { address(0, 0, 460800)};
+num_buffers(l2_11) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_8_for_layer_12_port0) = { address(2, 0, 217088), address(2, 0, 370688)};
+num_buffers(L2_IFM_Buffer_from_layer_8_for_layer_12_port0) =2;
+
+location<buffer>(L2_IFM_Buffer_from_layer_11_for_layer_12_port1) = { address(1, 0, 434176), address(2, 0, 63488)};
+num_buffers(L2_IFM_Buffer_from_layer_11_for_layer_12_port1) =2;
+
+location<buffer>(l2_12) = { address(0, 0, 0), address(0, 0, 327680)};
+num_buffers(l2_12) =2;
+
+location<buffer>(L2_IFM_Buffer_from_layer_12_for_layer_13_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_12_for_layer_13_port0) =1;
+
+location<buffer>(l2_13) = { address(0, 0, 460800)};
+num_buffers(l2_13) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_12_for_layer_14_port1) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_12_for_layer_14_port1) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_13_for_layer_14_port0) = { address(0, 0, 491520)};
+num_buffers(L2_IFM_Buffer_from_layer_13_for_layer_14_port0) =1;
+
+location<buffer>(l2_14) = { address(2, 0, 32768)};
+num_buffers(l2_14) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_14_for_layer_15_port0) = { address(2, 0, 339968), address(2, 0, 432128)};
+num_buffers(L2_IFM_Buffer_from_layer_14_for_layer_15_port0) =2;
+
+location<buffer>(l2_15) = { address(0, 0, 0), address(0, 0, 368640)};
+num_buffers(l2_15) =2;
+
+location<buffer>(L2_IFM_Buffer_from_layer_15_for_layer_16_port0) = { address(0, 0, 0), address(0, 0, 348160)};
+num_buffers(L2_IFM_Buffer_from_layer_15_for_layer_16_port0) =2;
+
+location<buffer>(l2_16) = { address(2, 0, 352256), address(2, 0, 438272)};
+num_buffers(l2_16) =2;
+
+location<buffer>(L2_IFM_Buffer_from_layer_17_for_layer_18_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_17_for_layer_18_port0) =1;
+
+location<buffer>(l2_18) = { address(1, 0, 522240)};
+num_buffers(l2_18) =1;
+
+location<buffer>(l2_19) = { address(0, 0, 0)};
+num_buffers(l2_19) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_19_for_layer_20_port0) = { address(2, 0, 236288)};
+num_buffers(L2_IFM_Buffer_from_layer_19_for_layer_20_port0) =1;
+
+location<buffer>(l2_20) = { address(0, 0, 0)};
+num_buffers(l2_20) =1;
+
+location<buffer>(L2_OFM_Buffer_layer_TGSpilling_1818) = { address(0, 0, 0)};
+num_buffers(L2_OFM_Buffer_layer_TGSpilling_1818) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_21_for_layer_22_port0) = { address(0, 0, 491520)};
+num_buffers(L2_IFM_Buffer_from_layer_21_for_layer_22_port0) =1;
+
+location<buffer>(l2_22) = { address(0, 0, 0)};
+num_buffers(l2_22) =1;
+
+location<buffer>(l2_23) = { address(1, 0, 163840)};
+num_buffers(l2_23) =1;
+
+location<buffer>(l2_24) = { address(0, 0, 0)};
+num_buffers(l2_24) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_25_for_layer_26_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_25_for_layer_26_port0) =1;
+
+location<buffer>(l2_26) = { address(2, 0, 523264)};
+num_buffers(l2_26) =1;
+
+location<buffer>(l2_27) = { address(0, 0, 0)};
+num_buffers(l2_27) =1;
+
+location<buffer>(l2_28) = { address(2, 0, 516096)};
+num_buffers(l2_28) =1;
+
+location<buffer>(l2_29) = { address(0, 0, 0)};
+num_buffers(l2_29) =1;
+
+location<buffer>(l2_30) = { address(2, 0, 516096)};
+num_buffers(l2_30) =1;
+
+location<buffer>(l2_31) = { address(0, 0, 0)};
+num_buffers(l2_31) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_32_for_layer_33_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_32_for_layer_33_port0) =1;
+
+location<buffer>(L2_OFM_Buffer_layer_TGSpilling_2424) = { address(0, 0, 132480)};
+num_buffers(L2_OFM_Buffer_layer_TGSpilling_2424) =1;
+
+location<buffer>(l2_33) = { address(2, 0, 339968)};
+num_buffers(l2_33) =1;
+
+location<buffer>(l2_34) = { address(0, 0, 0)};
+num_buffers(l2_34) =1;
+
+location<buffer>(l2_35) = { address(2, 0, 131072)};
+num_buffers(l2_35) =1;
+
+location<buffer>(l2_36) = { address(0, 0, 0)};
+num_buffers(l2_36) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_37_for_layer_38_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_37_for_layer_38_port0) =1;
+
+location<buffer>(l2_38) = { address(2, 0, 523264)};
+num_buffers(l2_38) =1;
+
+location<buffer>(l2_39) = { address(0, 0, 0)};
+num_buffers(l2_39) =1;
+
+location<buffer>(l2_40) = { address(2, 0, 516096)};
+num_buffers(l2_40) =1;
+
+location<buffer>(l2_41) = { address(0, 0, 0)};
+num_buffers(l2_41) =1;
+
+location<buffer>(l2_42) = { address(2, 0, 516096)};
+num_buffers(l2_42) =1;
+
+location<buffer>(l2_43) = { address(0, 0, 0)};
+num_buffers(l2_43) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_44_for_layer_45_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_44_for_layer_45_port0) =1;
+
+location<buffer>(L2_OFM_Buffer_layer_TGSpilling_3636) = { address(0, 0, 220800)};
+num_buffers(L2_OFM_Buffer_layer_TGSpilling_3636) =1;
+
+location<buffer>(l2_45) = { address(2, 0, 278528)};
+num_buffers(l2_45) =1;
+
+location<buffer>(L2_OFM_Buffer_layer_TGSpilling_3434) = { address(0, 0, 0)};
+num_buffers(L2_OFM_Buffer_layer_TGSpilling_3434) =1;
+
+location<buffer>(l2_46) = { address(0, 0, 0)};
+num_buffers(l2_46) =1;
+
+location<buffer>(l2_47) = { address(2, 0, 131072)};
+num_buffers(l2_47) =1;
+
+location<buffer>(l2_48) = { address(0, 0, 0)};
+num_buffers(l2_48) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_49_for_layer_50_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_49_for_layer_50_port0) =1;
+
+location<buffer>(l2_50) = { address(2, 0, 523264)};
+num_buffers(l2_50) =1;
+
+location<buffer>(l2_51) = { address(0, 0, 0)};
+num_buffers(l2_51) =1;
+
+location<buffer>(l2_52) = { address(2, 0, 516096)};
+num_buffers(l2_52) =1;
+
+location<buffer>(l2_53) = { address(0, 0, 0)};
+num_buffers(l2_53) =1;
+
+location<buffer>(l2_54) = { address(2, 0, 516096)};
+num_buffers(l2_54) =1;
+
+location<buffer>(l2_55) = { address(0, 0, 0)};
+num_buffers(l2_55) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_56_for_layer_57_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_56_for_layer_57_port0) =1;
+
+location<buffer>(L2_OFM_Buffer_layer_TGSpilling_4848) = { address(0, 0, 220800)};
+num_buffers(L2_OFM_Buffer_layer_TGSpilling_4848) =1;
+
+location<buffer>(l2_57) = { address(2, 0, 278528)};
+num_buffers(l2_57) =1;
+
+location<buffer>(L2_OFM_Buffer_layer_TGSpilling_4646) = { address(0, 0, 0)};
+num_buffers(L2_OFM_Buffer_layer_TGSpilling_4646) =1;
+
+location<buffer>(l2_58) = { address(0, 0, 0)};
+num_buffers(l2_58) =1;
+
+location<buffer>(l2_59) = { address(1, 0, 262144)};
+num_buffers(l2_59) =1;
+
+location<buffer>(l2_60) = { address(0, 0, 0)};
+num_buffers(l2_60) =1;
+
+location<buffer>(l2_61) = { address(2, 0, 32768)};
+num_buffers(l2_61) =1;
+
+location<buffer>(l2_62) = { address(0, 0, 0)};
+num_buffers(l2_62) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_59_for_layer_63_port0) = { address(2, 0, 293888)};
+num_buffers(L2_IFM_Buffer_from_layer_59_for_layer_63_port0) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_62_for_layer_63_port1) = { address(2, 0, 63488)};
+num_buffers(L2_IFM_Buffer_from_layer_62_for_layer_63_port1) =1;
+
+location<buffer>(l2_63) = { address(0, 0, 0)};
+num_buffers(l2_63) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_64_for_layer_65_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_64_for_layer_65_port0) =1;
+
+location<buffer>(l2_65) = { address(2, 0, 360448)};
+num_buffers(l2_65) =1;
+
+location<buffer>(l2_66) = { address(0, 0, 0)};
+num_buffers(l2_66) =1;
+
+location<buffer>(l2_67) = { address(2, 0, 237568)};
+num_buffers(l2_67) =1;
+
+location<buffer>(l2_68) = { address(0, 0, 0)};
+num_buffers(l2_68) =1;
+
+location<buffer>(l2_69) = { address(0, 0, 122880)};
+num_buffers(l2_69) =1;
+
+location<buffer>(l2_70) = { address(0, 0, 0)};
+num_buffers(l2_70) =1;
+
+location<buffer>(l2_71) = { address(0, 0, 73728)};
+num_buffers(l2_71) =1;
+
+location<buffer>(l2_72) = { address(0, 0, 270336)};
+num_buffers(l2_72) =1;
+
+location<buffer>(l2_73) = { address(2, 0, 401408)};
+num_buffers(l2_73) =1;
+
+location<buffer>(l2_74) = { address(0, 0, 270336)};
+num_buffers(l2_74) =1;
+
+location<buffer>(l2_75) = { address(2, 0, 401408)};
+num_buffers(l2_75) =1;
+
+location<buffer>(l2_76) = { address(0, 0, 73728)};
+num_buffers(l2_76) =1;
+
+location<buffer>(l2_77) = { address(0, 0, 245760)};
+num_buffers(l2_77) =1;
+
+location<buffer>(l2_78) = { address(2, 0, 401408)};
+num_buffers(l2_78) =1;
+
+location<buffer>(l2_79) = { address(0, 0, 245760)};
+num_buffers(l2_79) =1;
+
+location<buffer>(l2_80) = { address(2, 0, 401408)};
+num_buffers(l2_80) =1;
+
+location<buffer>(l2_81) = { address(0, 0, 0)};
+num_buffers(l2_81) =1;
+
+location<buffer>(l2_82) = { address(0, 0, 73728)};
+num_buffers(l2_82) =1;
+
+location<buffer>(l2_83) = { address(0, 0, 184320)};
+num_buffers(l2_83) =1;
+
+location<buffer>(l2_84) = { address(2, 0, 432128)};
+num_buffers(l2_84) =1;
+
+location<buffer>(l2_85) = { address(0, 0, 184320)};
+num_buffers(l2_85) =1;
+
+location<buffer>(l2_86) = { address(2, 0, 432128)};
+num_buffers(l2_86) =1;
+
+location<buffer>(l2_87) = { address(0, 0, 73728)};
+num_buffers(l2_87) =1;
+
+location<buffer>(l2_88) = { address(0, 0, 221184)};
+num_buffers(l2_88) =1;
+
+location<buffer>(l2_89) = { address(2, 0, 432128)};
+num_buffers(l2_89) =1;
+
+location<buffer>(l2_90) = { address(0, 0, 221184)};
+num_buffers(l2_90) =1;
+
+location<buffer>(l2_91) = { address(2, 0, 432128)};
+num_buffers(l2_91) =1;
+
+location<buffer>(l2_92) = { address(0, 0, 0)};
+num_buffers(l2_92) =1;
+
+location<buffer>(l2_93) = { address(0, 0, 73728)};
+num_buffers(l2_93) =1;
+
+location<buffer>(l2_94) = { address(0, 0, 184320)};
+num_buffers(l2_94) =1;
+
+location<buffer>(l2_95) = { address(2, 0, 432128)};
+num_buffers(l2_95) =1;
+
+location<buffer>(l2_96) = { address(0, 0, 184320)};
+num_buffers(l2_96) =1;
+
+location<buffer>(l2_97) = { address(2, 0, 432128)};
+num_buffers(l2_97) =1;
+
+location<buffer>(l2_98) = { address(0, 0, 73728)};
+num_buffers(l2_98) =1;
+
+location<buffer>(l2_99) = { address(0, 0, 221184)};
+num_buffers(l2_99) =1;
+
+location<buffer>(l2_100) = { address(2, 0, 432128)};
+num_buffers(l2_100) =1;
+
+location<buffer>(l2_101) = { address(0, 0, 221184)};
+num_buffers(l2_101) =1;
+
+location<buffer>(l2_102) = { address(2, 0, 432128)};
+num_buffers(l2_102) =1;
+
+location<buffer>(l2_103) = { address(0, 0, 0)};
+num_buffers(l2_103) =1;
+
+location<buffer>(l2_104) = { address(2, 0, 155648)};
+num_buffers(l2_104) =1;
+
+location<buffer>(l2_105) = { address(0, 0, 0)};
+num_buffers(l2_105) =1;
+
+location<buffer>(l2_106) = { address(1, 0, 434176)};
+num_buffers(l2_106) =1;
+
+location<buffer>(l2_107) = { address(0, 0, 0)};
+num_buffers(l2_107) =1;
+
+location<buffer>(l2_108) = { address(0, 0, 245760)};
+num_buffers(l2_108) =1;
+
+location<buffer>(l2_109) = { address(0, 0, 491520)};
+num_buffers(l2_109) =1;
+
+location<buffer>(l2_110) = { address(0, 0, 0)};
+num_buffers(l2_110) =1;
+
+location<buffer>(l2_111) = { address(2, 0, 278528)};
+num_buffers(l2_111) =1;
+
+location<buffer>(l2_112) = { address(0, 0, 0)};
+num_buffers(l2_112) =1;
+
+location<buffer>(l2_113) = { address(0, 0, 245760)};
+num_buffers(l2_113) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_114_for_layer_115_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_114_for_layer_115_port0) =1;
+
+location<buffer>(l2_115) = { address(2, 0, 520448)};
+num_buffers(l2_115) =1;
+
+location<buffer>(l2_116) = { address(0, 0, 0)};
+num_buffers(l2_116) =1;
+
+location<buffer>(l2_117) = { address(2, 0, 491520)};
+num_buffers(l2_117) =1;
+
+location<buffer>(l2_118) = { address(0, 0, 0)};
+num_buffers(l2_118) =1;
+
+location<buffer>(l2_119) = { address(2, 0, 516096)};
+num_buffers(l2_119) =1;
+
+location<buffer>(l2_120) = { address(0, 0, 0)};
+num_buffers(l2_120) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_121_for_layer_122_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_121_for_layer_122_port0) =1;
+
+location<buffer>(L2_OFM_Buffer_layer_TGSpilling_113113) = { address(0, 0, 230400)};
+num_buffers(L2_OFM_Buffer_layer_TGSpilling_113113) =1;
+
+location<buffer>(l2_122) = { address(2, 0, 278528)};
+num_buffers(l2_122) =1;
+
+location<buffer>(l2_123) = { address(0, 0, 0)};
+num_buffers(l2_123) =1;
+
+location<buffer>(l2_124) = { address(2, 0, 8192)};
+num_buffers(l2_124) =1;
+
+location<buffer>(l2_125) = { address(0, 0, 0)};
+num_buffers(l2_125) =1;
+
+location<buffer>(l2_126) = { address(1, 0, 194560)};
+num_buffers(l2_126) =1;
+
+location<buffer>(l2_127) = { address(0, 0, 0)};
+num_buffers(l2_127) =1;
+
+location<buffer>(l2_128) = { address(0, 0, 337920)};
+num_buffers(l2_128) =1;
+
+location<buffer>(l2_129) = { address(1, 0, 151552)};
+num_buffers(l2_129) =1;
+
+location<buffer>(l2_130) = { address(0, 0, 0)};
+num_buffers(l2_130) =1;
+
+location<buffer>(l2_131) = { address(2, 0, 186368)};
+num_buffers(l2_131) =1;
+
+location<buffer>(l2_132) = { address(0, 0, 0)};
+num_buffers(l2_132) =1;
+
+location<buffer>(l2_133) = { address(0, 0, 337920)};
+num_buffers(l2_133) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_134_for_layer_135_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_134_for_layer_135_port0) =1;
+
+location<buffer>(l2_135) = { address(2, 0, 518912)};
+num_buffers(l2_135) =1;
+
+location<buffer>(l2_136) = { address(0, 0, 0)};
+num_buffers(l2_136) =1;
+
+location<buffer>(l2_137) = { address(2, 0, 434176)};
+num_buffers(l2_137) =1;
+
+location<buffer>(l2_138) = { address(0, 0, 0)};
+num_buffers(l2_138) =1;
+
+location<buffer>(l2_139) = { address(2, 0, 516096)};
+num_buffers(l2_139) =1;
+
+location<buffer>(l2_140) = { address(0, 0, 0)};
+num_buffers(l2_140) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_141_for_layer_142_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_141_for_layer_142_port0) =1;
+
+location<buffer>(L2_OFM_Buffer_layer_TGSpilling_133133) = { address(0, 0, 322560)};
+num_buffers(L2_OFM_Buffer_layer_TGSpilling_133133) =1;
+
+location<buffer>(l2_142) = { address(2, 0, 186368)};
+num_buffers(l2_142) =1;
+
+location<buffer>(L2_OFM_Buffer_layer_TGSpilling_123123) = { address(0, 0, 0)};
+num_buffers(L2_OFM_Buffer_layer_TGSpilling_123123) =1;
+
+location<buffer>(l2_143) = { address(0, 0, 0)};
+num_buffers(l2_143) =1;
+
+location<buffer>(l2_144) = { address(2, 0, 8192)};
+num_buffers(l2_144) =1;
+
+location<buffer>(l2_145) = { address(0, 0, 0)};
+num_buffers(l2_145) =1;
+
+location<buffer>(l2_146) = { address(1, 0, 194560)};
+num_buffers(l2_146) =1;
+
+location<buffer>(l2_147) = { address(0, 0, 0)};
+num_buffers(l2_147) =1;
+
+location<buffer>(l2_148) = { address(0, 0, 337920)};
+num_buffers(l2_148) =1;
+
+location<buffer>(l2_149) = { address(1, 0, 151552)};
+num_buffers(l2_149) =1;
+
+location<buffer>(l2_150) = { address(0, 0, 0)};
+num_buffers(l2_150) =1;
+
+location<buffer>(l2_151) = { address(2, 0, 186368)};
+num_buffers(l2_151) =1;
+
+location<buffer>(l2_152) = { address(0, 0, 0)};
+num_buffers(l2_152) =1;
+
+location<buffer>(l2_153) = { address(0, 0, 337920)};
+num_buffers(l2_153) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_154_for_layer_155_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_154_for_layer_155_port0) =1;
+
+location<buffer>(l2_155) = { address(2, 0, 518912)};
+num_buffers(l2_155) =1;
+
+location<buffer>(l2_156) = { address(0, 0, 0)};
+num_buffers(l2_156) =1;
+
+location<buffer>(l2_157) = { address(2, 0, 434176)};
+num_buffers(l2_157) =1;
+
+location<buffer>(l2_158) = { address(0, 0, 0)};
+num_buffers(l2_158) =1;
+
+location<buffer>(l2_159) = { address(2, 0, 516096)};
+num_buffers(l2_159) =1;
+
+location<buffer>(l2_160) = { address(0, 0, 0)};
+num_buffers(l2_160) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_161_for_layer_162_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_161_for_layer_162_port0) =1;
+
+location<buffer>(L2_OFM_Buffer_layer_TGSpilling_153153) = { address(0, 0, 322560)};
+num_buffers(L2_OFM_Buffer_layer_TGSpilling_153153) =1;
+
+location<buffer>(l2_162) = { address(2, 0, 186368)};
+num_buffers(l2_162) =1;
+
+location<buffer>(l2_163) = { address(0, 0, 0)};
+num_buffers(l2_163) =1;
+
+location<buffer>(l2_164) = { address(1, 0, 311296)};
+num_buffers(l2_164) =1;
+
+location<buffer>(l2_165) = { address(0, 0, 0)};
+num_buffers(l2_165) =1;
+
+location<buffer>(l2_166) = { address(2, 0, 63488)};
+num_buffers(l2_166) =1;
+
+location<buffer>(l2_167) = { address(0, 0, 0)};
+num_buffers(l2_167) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_164_for_layer_168_port0) = { address(2, 0, 293888)};
+num_buffers(L2_IFM_Buffer_from_layer_164_for_layer_168_port0) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_167_for_layer_168_port1) = { address(2, 0, 63488)};
+num_buffers(L2_IFM_Buffer_from_layer_167_for_layer_168_port1) =1;
+
+location<buffer>(l2_168) = { address(0, 0, 0)};
+num_buffers(l2_168) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_168_for_layer_169_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_168_for_layer_169_port0) =1;
+
+location<buffer>(l2_169) = { address(1, 0, 311296)};
+num_buffers(l2_169) =1;
+
+location<buffer>(l2_170) = { address(0, 0, 0)};
+num_buffers(l2_170) =1;
+
+location<buffer>(l2_171) = { address(2, 0, 63488)};
+num_buffers(l2_171) =1;
+
+location<buffer>(l2_172) = { address(0, 0, 0)};
+num_buffers(l2_172) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_169_for_layer_173_port0) = { address(2, 0, 293888)};
+num_buffers(L2_IFM_Buffer_from_layer_169_for_layer_173_port0) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_172_for_layer_173_port1) = { address(2, 0, 63488)};
+num_buffers(L2_IFM_Buffer_from_layer_172_for_layer_173_port1) =1;
+
+location<buffer>(l2_173) = { address(0, 0, 0)};
+num_buffers(l2_173) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_174_for_layer_175_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_174_for_layer_175_port0) =1;
+
+location<buffer>(l2_175) = { address(2, 0, 516608)};
+num_buffers(l2_175) =1;
+
+location<buffer>(l2_176) = { address(0, 0, 0)};
+num_buffers(l2_176) =1;
+
+location<buffer>(l2_177) = { address(2, 0, 462848)};
+num_buffers(l2_177) =1;
+
+location<buffer>(l2_178) = { address(0, 0, 0)};
+num_buffers(l2_178) =1;
+
+location<buffer>(l2_179) = { address(2, 0, 516096)};
+num_buffers(l2_179) =1;
+
+location<buffer>(l2_180) = { address(0, 0, 0)};
+num_buffers(l2_180) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_173_for_layer_182_port1) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_173_for_layer_182_port1) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_181_for_layer_182_port0) = { address(0, 0, 460800)};
+num_buffers(L2_IFM_Buffer_from_layer_181_for_layer_182_port0) =1;
+
+location<buffer>(l2_182) = { address(2, 0, 63488)};
+num_buffers(l2_182) =1;
+
+location<buffer>(L2_OFM_Buffer_layer_TGSpilling_163163) = { address(0, 0, 0)};
+num_buffers(L2_OFM_Buffer_layer_TGSpilling_163163) =1;
+
+location<buffer>(l2_183) = { address(0, 0, 0)};
+num_buffers(l2_183) =1;
+
+location<buffer>(l2_184) = { address(1, 0, 311296)};
+num_buffers(l2_184) =1;
+
+location<buffer>(l2_185) = { address(0, 0, 0)};
+num_buffers(l2_185) =1;
+
+location<buffer>(l2_186) = { address(2, 0, 63488)};
+num_buffers(l2_186) =1;
+
+location<buffer>(l2_187) = { address(0, 0, 0)};
+num_buffers(l2_187) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_184_for_layer_188_port0) = { address(2, 0, 293888)};
+num_buffers(L2_IFM_Buffer_from_layer_184_for_layer_188_port0) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_187_for_layer_188_port1) = { address(2, 0, 63488)};
+num_buffers(L2_IFM_Buffer_from_layer_187_for_layer_188_port1) =1;
+
+location<buffer>(l2_188) = { address(0, 0, 0)};
+num_buffers(l2_188) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_188_for_layer_189_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_188_for_layer_189_port0) =1;
+
+location<buffer>(l2_189) = { address(1, 0, 311296)};
+num_buffers(l2_189) =1;
+
+location<buffer>(l2_190) = { address(0, 0, 0)};
+num_buffers(l2_190) =1;
+
+location<buffer>(l2_191) = { address(2, 0, 63488)};
+num_buffers(l2_191) =1;
+
+location<buffer>(l2_192) = { address(0, 0, 0)};
+num_buffers(l2_192) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_189_for_layer_193_port0) = { address(2, 0, 293888)};
+num_buffers(L2_IFM_Buffer_from_layer_189_for_layer_193_port0) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_192_for_layer_193_port1) = { address(2, 0, 63488)};
+num_buffers(L2_IFM_Buffer_from_layer_192_for_layer_193_port1) =1;
+
+location<buffer>(l2_193) = { address(0, 0, 0)};
+num_buffers(l2_193) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_194_for_layer_195_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_194_for_layer_195_port0) =1;
+
+location<buffer>(l2_195) = { address(2, 0, 516608)};
+num_buffers(l2_195) =1;
+
+location<buffer>(l2_196) = { address(0, 0, 0)};
+num_buffers(l2_196) =1;
+
+location<buffer>(l2_197) = { address(2, 0, 462848)};
+num_buffers(l2_197) =1;
+
+location<buffer>(l2_198) = { address(0, 0, 0)};
+num_buffers(l2_198) =1;
+
+location<buffer>(l2_199) = { address(2, 0, 516096)};
+num_buffers(l2_199) =1;
+
+location<buffer>(l2_200) = { address(0, 0, 0)};
+num_buffers(l2_200) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_193_for_layer_202_port1) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_193_for_layer_202_port1) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_201_for_layer_202_port0) = { address(0, 0, 460800)};
+num_buffers(L2_IFM_Buffer_from_layer_201_for_layer_202_port0) =1;
+
+location<buffer>(l2_202) = { address(2, 0, 63488)};
+num_buffers(l2_202) =1;
+
+location<buffer>(L2_OFM_Buffer_layer_TGSpilling_183183) = { address(0, 0, 0)};
+num_buffers(L2_OFM_Buffer_layer_TGSpilling_183183) =1;
+
+location<buffer>(l2_203) = { address(0, 0, 0)};
+num_buffers(l2_203) =1;
+
+location<buffer>(l2_204) = { address(1, 0, 311296)};
+num_buffers(l2_204) =1;
+
+location<buffer>(l2_205) = { address(0, 0, 0)};
+num_buffers(l2_205) =1;
+
+location<buffer>(l2_206) = { address(2, 0, 63488)};
+num_buffers(l2_206) =1;
+
+location<buffer>(l2_207) = { address(0, 0, 0)};
+num_buffers(l2_207) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_204_for_layer_208_port0) = { address(2, 0, 293888)};
+num_buffers(L2_IFM_Buffer_from_layer_204_for_layer_208_port0) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_207_for_layer_208_port1) = { address(2, 0, 63488)};
+num_buffers(L2_IFM_Buffer_from_layer_207_for_layer_208_port1) =1;
+
+location<buffer>(l2_208) = { address(0, 0, 0)};
+num_buffers(l2_208) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_209_for_layer_210_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_209_for_layer_210_port0) =1;
+
+location<buffer>(l2_210) = { address(2, 0, 516608)};
+num_buffers(l2_210) =1;
+
+location<buffer>(l2_211) = { address(0, 0, 0)};
+num_buffers(l2_211) =1;
+
+location<buffer>(l2_212) = { address(0, 0, 16384)};
+num_buffers(l2_212) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_208_for_layer_214_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_208_for_layer_214_port0) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_213_for_layer_214_port1) = { address(0, 0, 460800)};
+num_buffers(L2_IFM_Buffer_from_layer_213_for_layer_214_port1) =1;
+
+location<buffer>(l2_214) = { address(0, 0, 460800)};
+num_buffers(l2_214) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_216_for_layer_217_port0) = { address(1, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_216_for_layer_217_port0) =1;
+
+location<buffer>(L2_IFM_Buffer_for_input4_0_port1) = { address(1, 0, 0)};
+num_buffers(L2_IFM_Buffer_for_input4_0_port1) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_217_for_layer_218_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_217_for_layer_218_port0) =1;
+
+location<buffer>(l2_218) = { address(2, 0, 391168)};
+num_buffers(l2_218) =1;
+
+location<buffer>(l2_219) = { address(0, 0, 0)};
+num_buffers(l2_219) =1;
+
+location<buffer>(L2_CONST_IFM_Buffer_for_input3_0_port0) = { address(0, 0, 0)};
+num_buffers(L2_CONST_IFM_Buffer_for_input3_0_port0) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_220_for_layer_221_port1) = { address(0, 0, 30720)};
+num_buffers(L2_IFM_Buffer_from_layer_220_for_layer_221_port1) =1;
+
+location<buffer>(l2_221) = { address(2, 0, 493568)};
+num_buffers(l2_221) =1;
+
+location<buffer>(L2_IFM_Buffer_for_input4_1_port1) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_for_input4_1_port1) =1;
+
+location<buffer>(l2_222) = { address(0, 0, 30720)};
+num_buffers(l2_222) =1;
+
+location<buffer>(L2_IFM_Buffer_for_input4_2_port1) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_for_input4_2_port1) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_223_for_layer_224_port0) = { address(0, 0, 30720)};
+num_buffers(L2_IFM_Buffer_from_layer_223_for_layer_224_port0) =1;
+
+location<buffer>(l2_224) = { address(0, 0, 61440)};
+num_buffers(l2_224) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_216_for_layer_225_port0) = { address(1, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_216_for_layer_225_port0) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_225_for_layer_226_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_225_for_layer_226_port0) =1;
+
+location<buffer>(l2_226) = { address(2, 0, 475136)};
+num_buffers(l2_226) =1;
+
+location<buffer>(l2_227) = { address(0, 0, 0)};
+num_buffers(l2_227) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_220_for_layer_228_port0) = { address(0, 0, 30720)};
+num_buffers(L2_IFM_Buffer_from_layer_220_for_layer_228_port0) =1;
+
+location<buffer>(l2_228) = { address(2, 0, 493568)};
+num_buffers(l2_228) =1;
+
+location<buffer>(L2_OFM_Buffer_layer_TGSpilling_222222) = { address(0, 0, 0)};
+num_buffers(L2_OFM_Buffer_layer_TGSpilling_222222) =1;
+
+location<buffer>(l2_229) = { address(0, 0, 30720)};
+num_buffers(l2_229) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_215_for_layer_230_port0) = { address(1, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_215_for_layer_230_port0) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_232_for_layer_236_port0) = { address(1, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_232_for_layer_236_port0) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_5_for_layer_233_port0) = { address(1, 0, 434176), address(2, 0, 217088)};
+num_buffers(L2_IFM_Buffer_from_layer_5_for_layer_233_port0) =2;
+
+location<buffer>(l2_233) = { address(0, 0, 0), address(0, 0, 327680)};
+num_buffers(l2_233) =2;
+
+location<buffer>(L2_IFM_Buffer_from_layer_233_for_layer_234_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_233_for_layer_234_port0) =1;
+
+location<buffer>(l2_234) = { address(2, 0, 278528)};
+num_buffers(l2_234) =1;
+
+location<buffer>(l2_235) = { address(0, 0, 0)};
+num_buffers(l2_235) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_236_for_layer_237_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_236_for_layer_237_port0) =1;
+
+location<buffer>(l2_237) = { address(0, 0, 323840)};
+num_buffers(l2_237) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_239_for_layer_240_port0) = { address(1, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_239_for_layer_240_port0) =1;
+
+location<buffer>(L2_IFM_Buffer_for_input3_0_port1) = { address(1, 0, 0)};
+num_buffers(L2_IFM_Buffer_for_input3_0_port1) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_240_for_layer_241_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_240_for_layer_241_port0) =1;
+
+location<buffer>(l2_241) = { address(2, 0, 229376)};
+num_buffers(l2_241) =1;
+
+location<buffer>(l2_242) = { address(0, 0, 0)};
+num_buffers(l2_242) =1;
+
+location<buffer>(L2_CONST_IFM_Buffer_for_input2_0_port0) = { address(0, 0, 0)};
+num_buffers(L2_CONST_IFM_Buffer_for_input2_0_port0) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_243_for_layer_244_port1) = { address(0, 0, 73600)};
+num_buffers(L2_IFM_Buffer_from_layer_243_for_layer_244_port1) =1;
+
+location<buffer>(l2_244) = { address(2, 0, 401408)};
+num_buffers(l2_244) =1;
+
+location<buffer>(L2_IFM_Buffer_for_input3_1_port1) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_for_input3_1_port1) =1;
+
+location<buffer>(l2_245) = { address(0, 0, 73600)};
+num_buffers(l2_245) =1;
+
+location<buffer>(L2_IFM_Buffer_for_input3_2_port1) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_for_input3_2_port1) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_246_for_layer_247_port0) = { address(0, 0, 73600)};
+num_buffers(L2_IFM_Buffer_from_layer_246_for_layer_247_port0) =1;
+
+location<buffer>(l2_247) = { address(0, 0, 147200)};
+num_buffers(l2_247) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_239_for_layer_248_port0) = { address(1, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_239_for_layer_248_port0) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_248_for_layer_249_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_248_for_layer_249_port0) =1;
+
+location<buffer>(l2_249) = { address(2, 0, 376832)};
+num_buffers(l2_249) =1;
+
+location<buffer>(l2_250) = { address(0, 0, 0)};
+num_buffers(l2_250) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_243_for_layer_251_port0) = { address(0, 0, 122880)};
+num_buffers(L2_IFM_Buffer_from_layer_243_for_layer_251_port0) =1;
+
+location<buffer>(l2_251) = { address(2, 0, 401408)};
+num_buffers(l2_251) =1;
+
+location<buffer>(L2_OFM_Buffer_layer_TGSpilling_245245) = { address(0, 0, 0)};
+num_buffers(L2_OFM_Buffer_layer_TGSpilling_245245) =1;
+
+location<buffer>(l2_252) = { address(0, 0, 122880)};
+num_buffers(l2_252) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_238_for_layer_253_port0) = { address(1, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_238_for_layer_253_port0) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_255_for_layer_256_port0) = { address(1, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_255_for_layer_256_port0) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_256_for_layer_257_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_256_for_layer_257_port0) =1;
+
+location<buffer>(l2_257) = { address(1, 0, 282112)};
+num_buffers(l2_257) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_260_for_layer_261_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_260_for_layer_261_port0) =1;
+
+location<buffer>(l2_261) = { address(2, 0, 32768)};
+num_buffers(l2_261) =1;
+
+location<buffer>(l2_262) = { address(0, 0, 0)};
+num_buffers(l2_262) =1;
+
+location<buffer>(L2_CONST_IFM_Buffer_for_input1_0_port0) = { address(0, 0, 0)};
+num_buffers(L2_CONST_IFM_Buffer_for_input1_0_port0) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_263_for_layer_264_port1) = { address(0, 0, 172800)};
+num_buffers(L2_IFM_Buffer_from_layer_263_for_layer_264_port1) =1;
+
+location<buffer>(l2_264) = { address(2, 0, 278528)};
+num_buffers(l2_264) =1;
+
+location<buffer>(L2_IFM_Buffer_for_input2_1_port1) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_for_input2_1_port1) =1;
+
+location<buffer>(l2_265) = { address(0, 0, 172800)};
+num_buffers(l2_265) =1;
+
+location<buffer>(L2_IFM_Buffer_for_input2_2_port1) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_for_input2_2_port1) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_266_for_layer_267_port0) = { address(0, 0, 172800)};
+num_buffers(L2_IFM_Buffer_from_layer_266_for_layer_267_port0) =1;
+
+location<buffer>(l2_267) = { address(0, 0, 345600)};
+num_buffers(l2_267) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_268_for_layer_269_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_268_for_layer_269_port0) =1;
+
+location<buffer>(l2_269) = { address(2, 0, 229376)};
+num_buffers(l2_269) =1;
+
+location<buffer>(l2_270) = { address(0, 0, 0)};
+num_buffers(l2_270) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_263_for_layer_271_port0) = { address(0, 0, 245760)};
+num_buffers(L2_IFM_Buffer_from_layer_263_for_layer_271_port0) =1;
+
+location<buffer>(l2_271) = { address(2, 0, 278528)};
+num_buffers(l2_271) =1;
+
+location<buffer>(L2_OFM_Buffer_layer_TGSpilling_265265) = { address(0, 0, 0)};
+num_buffers(L2_OFM_Buffer_layer_TGSpilling_265265) =1;
+
+location<buffer>(l2_272) = { address(0, 0, 245760)};
+num_buffers(l2_272) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_275_for_layer_276_port0) = { address(0, 0, 0), address(0, 0, 409600)};
+num_buffers(L2_IFM_Buffer_from_layer_275_for_layer_276_port0) =2;
+
+location<buffer>(l2_276) = { address(2, 0, 114688), address(2, 0, 319488)};
+num_buffers(l2_276) =2;
+
+location<buffer>(L2_IFM_Buffer_from_layer_278_for_layer_279_port0) = { address(1, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_278_for_layer_279_port0) =1;
+
+location<buffer>(L2_IFM_Buffer_for_input1_0_port1) = { address(1, 0, 0)};
+num_buffers(L2_IFM_Buffer_for_input1_0_port1) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_279_for_layer_280_port0) = { address(0, 0, 0), address(0, 0, 327680)};
+num_buffers(L2_IFM_Buffer_from_layer_279_for_layer_280_port0) =2;
+
+location<buffer>(l2_280) = { address(1, 0, 393216), address(2, 0, 196608)};
+num_buffers(l2_280) =2;
+
+location<buffer>(L2_IFM_Buffer_from_layer_280_for_layer_281_port0) = { address(1, 0, 434176), address(2, 0, 217088)};
+num_buffers(L2_IFM_Buffer_from_layer_280_for_layer_281_port0) =2;
+
+location<buffer>(l2_281) = { address(0, 0, 0), address(0, 0, 327680)};
+num_buffers(l2_281) =2;
+
+location<buffer>(L2_CONST_IFM_Buffer_for_input0_0_port0) = { address(2, 0, 217088), address(2, 0, 370688)};
+num_buffers(L2_CONST_IFM_Buffer_for_input0_0_port0) =2;
+
+location<buffer>(L2_IFM_Buffer_from_layer_282_for_layer_283_port1) = { address(1, 0, 434176), address(2, 0, 63488)};
+num_buffers(L2_IFM_Buffer_from_layer_282_for_layer_283_port1) =2;
+
+location<buffer>(l2_283) = { address(0, 0, 0), address(0, 0, 327680)};
+num_buffers(l2_283) =2;
+
+location<buffer>(L2_IFM_Buffer_for_input1_1_port1) = { address(2, 0, 217088), address(2, 0, 370688)};
+num_buffers(L2_IFM_Buffer_for_input1_1_port1) =2;
+
+location<buffer>(L2_IFM_Buffer_from_layer_283_for_layer_284_port0) = { address(1, 0, 434176), address(2, 0, 63488)};
+num_buffers(L2_IFM_Buffer_from_layer_283_for_layer_284_port0) =2;
+
+location<buffer>(l2_284) = { address(0, 0, 0), address(0, 0, 327680)};
+num_buffers(l2_284) =2;
+
+location<buffer>(L2_IFM_Buffer_for_input1_2_port1) = { address(2, 0, 217088), address(2, 0, 370688)};
+num_buffers(L2_IFM_Buffer_for_input1_2_port1) =2;
+
+location<buffer>(L2_IFM_Buffer_from_layer_285_for_layer_286_port0) = { address(1, 0, 434176), address(2, 0, 63488)};
+num_buffers(L2_IFM_Buffer_from_layer_285_for_layer_286_port0) =2;
+
+location<buffer>(l2_286) = { address(0, 0, 0), address(0, 0, 327680)};
+num_buffers(l2_286) =2;
+
+location<buffer>(L2_IFM_Buffer_from_layer_278_for_layer_287_port0) = { address(1, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_278_for_layer_287_port0) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_287_for_layer_288_port0) = { address(0, 0, 0), address(0, 0, 327680)};
+num_buffers(L2_IFM_Buffer_from_layer_287_for_layer_288_port0) =2;
+
+location<buffer>(l2_288) = { address(1, 0, 393216), address(2, 0, 196608)};
+num_buffers(l2_288) =2;
+
+location<buffer>(L2_IFM_Buffer_from_layer_288_for_layer_289_port0) = { address(0, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_288_for_layer_289_port0) =1;
+
+location<buffer>(l2_289) = { address(0, 0, 460800)};
+num_buffers(l2_289) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_282_for_layer_290_port0) = { address(2, 0, 217088), address(2, 0, 370688)};
+num_buffers(L2_IFM_Buffer_from_layer_282_for_layer_290_port0) =2;
+
+location<buffer>(L2_IFM_Buffer_from_layer_289_for_layer_290_port1) = { address(1, 0, 434176), address(2, 0, 63488)};
+num_buffers(L2_IFM_Buffer_from_layer_289_for_layer_290_port1) =2;
+
+location<buffer>(l2_290) = { address(0, 0, 0), address(0, 0, 327680)};
+num_buffers(l2_290) =2;
+
+location<buffer>(L2_IFM_Buffer_from_layer_284_for_layer_291_port0) = { address(2, 0, 217088), address(2, 0, 370688)};
+num_buffers(L2_IFM_Buffer_from_layer_284_for_layer_291_port0) =2;
+
+location<buffer>(L2_IFM_Buffer_from_layer_290_for_layer_291_port1) = { address(1, 0, 434176), address(2, 0, 63488)};
+num_buffers(L2_IFM_Buffer_from_layer_290_for_layer_291_port1) =2;
+
+location<buffer>(l2_291) = { address(0, 0, 0), address(0, 0, 327680)};
+num_buffers(l2_291) =2;
+
+location<buffer>(L2_IFM_Buffer_from_layer_277_for_layer_292_port0) = { address(1, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_277_for_layer_292_port0) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_5_for_layer_294_port1) = { address(1, 0, 0)};
+num_buffers(L2_IFM_Buffer_from_layer_5_for_layer_294_port1) =1;
+
+location<buffer>(L2_IFM_Buffer_from_layer_294_for_layer_295_port0) = { address(0, 0, 0), address(0, 0, 435200)};
+num_buffers(L2_IFM_Buffer_from_layer_294_for_layer_295_port0) =2;
+
+location<buffer>(l2_295) = { address(1, 0, 393216), address(2, 0, 196608)};
+num_buffers(l2_295) =2;
+
+location<buffer>(L2_IFM_Buffer_from_layer_295_for_layer_296_port0) = { address(2, 0, 73728), address(2, 0, 299008)};
+num_buffers(L2_IFM_Buffer_from_layer_295_for_layer_296_port0) =2;
+
+location<buffer>(l2_296) = { address(0, 0, 0), address(0, 0, 409600)};
+num_buffers(l2_296) =2;
+
+location<buffer>(L2_IFM_Buffer_from_layer_296_for_layer_297_port0) = { address(2, 0, 114688), address(2, 0, 319488)};
+num_buffers(L2_IFM_Buffer_from_layer_296_for_layer_297_port0) =2;
+
+location<buffer>(l2_297) = { address(0, 0, 0), address(0, 0, 409600)};
+num_buffers(l2_297) =2;
+
+location<buffer>(L2_IFM_Buffer_from_layer_298_for_layer_299_port0) = { address(2, 0, 319488), address(2, 0, 421888)};
+num_buffers(L2_IFM_Buffer_from_layer_298_for_layer_299_port0) =2;
+
+location<buffer>(L2_OFM_Buffer_layer_299) = { address(0, 0, 0), address(0, 0, 409600)};
+num_buffers(L2_OFM_Buffer_layer_299) =2;
+
+location<buffer>(L2_IFM_Buffer_from_layer_5_for_layer_301_port1) = { address(2, 0, 319488), address(2, 0, 421888)};
+num_buffers(L2_IFM_Buffer_from_layer_5_for_layer_301_port1) =2;
+
+location<buffer>(L2_IFM_Buffer_from_layer_300_for_layer_301_port0) = { address(2, 0, 114688), address(2, 0, 217088)};
+num_buffers(L2_IFM_Buffer_from_layer_300_for_layer_301_port0) =2;
+
+location<buffer>(l2_301) = { address(0, 0, 0), address(0, 0, 409600)};
+num_buffers(l2_301) =2;
+
+location<buffer>(L2_IFM_Buffer_from_layer_301_for_layer_302_port0) = { address(2, 0, 319488), address(2, 0, 421888)};
+num_buffers(L2_IFM_Buffer_from_layer_301_for_layer_302_port0) =2;
+
+location<buffer>(L2_OFM_Buffer_layer_302) = { address(0, 0, 0), address(0, 0, 409600)};
+num_buffers(L2_OFM_Buffer_layer_302) =2;
+
+location<buffer>(Layer_8_l2_wts) = wts_loc_8;
+num_buffers(Layer_8_l2_wts) = 1;
+repetition_count(Layer_8_l2_wts) = wts_repetition_8;
+connect(Layer_8_wts_ddr.out[0],Layer_8_l2_wts.in[0]);
+read_access(Layer_8_wts_ddr.out[0]) = wts_ddr_read_pattern_8[0];
+write_access(Layer_8_l2_wts.in[0]) = wts_ddr_write_pattern_8[0];
+
+connect(Layer_8_wts_ddr.out[1],Layer_8_l2_wts.in[1]);
+read_access(Layer_8_wts_ddr.out[1]) = wts_ddr_read_pattern_8[1];
+write_access(Layer_8_l2_wts.in[1]) = wts_ddr_write_pattern_8[1];
+
+location<buffer>(Layer_13_l2_wts) = wts_loc_13;
+num_buffers(Layer_13_l2_wts) = 1;
+repetition_count(Layer_13_l2_wts) = wts_repetition_13;
+connect(Layer_13_wts_ddr.out[0],Layer_13_l2_wts.in[0]);
+read_access(Layer_13_wts_ddr.out[0]) = wts_ddr_read_pattern_13[0];
+write_access(Layer_13_l2_wts.in[0]) = wts_ddr_write_pattern_13[0];
+
+connect(Layer_13_wts_ddr.out[1],Layer_13_l2_wts.in[1]);
+read_access(Layer_13_wts_ddr.out[1]) = wts_ddr_read_pattern_13[1];
+write_access(Layer_13_l2_wts.in[1]) = wts_ddr_write_pattern_13[1];
+
+location<buffer>(Layer_14_l2_wts) = wts_loc_14;
+num_buffers(Layer_14_l2_wts) = 1;
+repetition_count(Layer_14_l2_wts) = wts_repetition_14;
+connect(Layer_14_wts_ddr.out[0],Layer_14_l2_wts.in[0]);
+read_access(Layer_14_wts_ddr.out[0]) = wts_ddr_read_pattern_14[0];
+write_access(Layer_14_l2_wts.in[0]) = wts_ddr_write_pattern_14[0];
+
+connect(Layer_14_wts_ddr.out[1],Layer_14_l2_wts.in[1]);
+read_access(Layer_14_wts_ddr.out[1]) = wts_ddr_read_pattern_14[1];
+write_access(Layer_14_l2_wts.in[1]) = wts_ddr_write_pattern_14[1];
+
+location<buffer>(Layer_15_l2_wts) = wts_loc_15;
+num_buffers(Layer_15_l2_wts) = 1;
+repetition_count(Layer_15_l2_wts) = wts_repetition_15;
+connect(Layer_15_wts_ddr.out[0],Layer_15_l2_wts.in[0]);
+read_access(Layer_15_wts_ddr.out[0]) = wts_ddr_read_pattern_15[0];
+write_access(Layer_15_l2_wts.in[0]) = wts_ddr_write_pattern_15[0];
+
+connect(Layer_15_wts_ddr.out[1],Layer_15_l2_wts.in[1]);
+read_access(Layer_15_wts_ddr.out[1]) = wts_ddr_read_pattern_15[1];
+write_access(Layer_15_l2_wts.in[1]) = wts_ddr_write_pattern_15[1];
+
+location<buffer>(Layer_16_l2_wts) = wts_loc_16;
+num_buffers(Layer_16_l2_wts) = 1;
+repetition_count(Layer_16_l2_wts) = wts_repetition_16;
+connect(Layer_16_wts_ddr.out[0],Layer_16_l2_wts.in[0]);
+read_access(Layer_16_wts_ddr.out[0]) = wts_ddr_read_pattern_16[0];
+write_access(Layer_16_l2_wts.in[0]) = wts_ddr_write_pattern_16[0];
+
+connect(Layer_16_wts_ddr.out[1],Layer_16_l2_wts.in[1]);
+read_access(Layer_16_wts_ddr.out[1]) = wts_ddr_read_pattern_16[1];
+write_access(Layer_16_l2_wts.in[1]) = wts_ddr_write_pattern_16[1];
+
+location<buffer>(Layer_18_l2_wts) = wts_loc_18;
+num_buffers(Layer_18_l2_wts) = 1;
+repetition_count(Layer_18_l2_wts) = wts_repetition_18;
+connect(Layer_18_wts_ddr.out[0],Layer_18_l2_wts.in[0]);
+read_access(Layer_18_wts_ddr.out[0]) = wts_ddr_read_pattern_18[0];
+write_access(Layer_18_l2_wts.in[0]) = wts_ddr_write_pattern_18[0];
+
+connect(Layer_18_wts_ddr.out[1],Layer_18_l2_wts.in[1]);
+read_access(Layer_18_wts_ddr.out[1]) = wts_ddr_read_pattern_18[1];
+write_access(Layer_18_l2_wts.in[1]) = wts_ddr_write_pattern_18[1];
+
+location<buffer>(Layer_19_l2_wts) = wts_loc_19;
+num_buffers(Layer_19_l2_wts) = 1;
+repetition_count(Layer_19_l2_wts) = wts_repetition_19;
+connect(Layer_19_wts_ddr.out[0],Layer_19_l2_wts.in[0]);
+read_access(Layer_19_wts_ddr.out[0]) = wts_ddr_read_pattern_19[0];
+write_access(Layer_19_l2_wts.in[0]) = wts_ddr_write_pattern_19[0];
+
+connect(Layer_19_wts_ddr.out[1],Layer_19_l2_wts.in[1]);
+read_access(Layer_19_wts_ddr.out[1]) = wts_ddr_read_pattern_19[1];
+write_access(Layer_19_l2_wts.in[1]) = wts_ddr_write_pattern_19[1];
+
+location<buffer>(Layer_20_l2_wts) = wts_loc_20;
+num_buffers(Layer_20_l2_wts) = 1;
+repetition_count(Layer_20_l2_wts) = wts_repetition_20;
+connect(Layer_20_wts_ddr.out[0],Layer_20_l2_wts.in[0]);
+read_access(Layer_20_wts_ddr.out[0]) = wts_ddr_read_pattern_20[0];
+write_access(Layer_20_l2_wts.in[0]) = wts_ddr_write_pattern_20[0];
+
+connect(Layer_20_wts_ddr.out[1],Layer_20_l2_wts.in[1]);
+read_access(Layer_20_wts_ddr.out[1]) = wts_ddr_read_pattern_20[1];
+write_access(Layer_20_l2_wts.in[1]) = wts_ddr_write_pattern_20[1];
+
+location<buffer>(Layer_22_l2_wts) = wts_loc_22;
+num_buffers(Layer_22_l2_wts) = 1;
+repetition_count(Layer_22_l2_wts) = wts_repetition_22;
+connect(Layer_22_wts_ddr.out[0],Layer_22_l2_wts.in[0]);
+read_access(Layer_22_wts_ddr.out[0]) = wts_ddr_read_pattern_22[0];
+write_access(Layer_22_l2_wts.in[0]) = wts_ddr_write_pattern_22[0];
+
+connect(Layer_22_wts_ddr.out[1],Layer_22_l2_wts.in[1]);
+read_access(Layer_22_wts_ddr.out[1]) = wts_ddr_read_pattern_22[1];
+write_access(Layer_22_l2_wts.in[1]) = wts_ddr_write_pattern_22[1];
+
+location<buffer>(Layer_23_l2_wts) = wts_loc_23;
+num_buffers(Layer_23_l2_wts) = 1;
+repetition_count(Layer_23_l2_wts) = wts_repetition_23;
+connect(Layer_23_wts_ddr.out[0],Layer_23_l2_wts.in[0]);
+read_access(Layer_23_wts_ddr.out[0]) = wts_ddr_read_pattern_23[0];
+write_access(Layer_23_l2_wts.in[0]) = wts_ddr_write_pattern_23[0];
+
+connect(Layer_23_wts_ddr.out[1],Layer_23_l2_wts.in[1]);
+read_access(Layer_23_wts_ddr.out[1]) = wts_ddr_read_pattern_23[1];
+write_access(Layer_23_l2_wts.in[1]) = wts_ddr_write_pattern_23[1];
+
+location<buffer>(Layer_24_l2_wts) = wts_loc_24;
+num_buffers(Layer_24_l2_wts) = 1;
+repetition_count(Layer_24_l2_wts) = wts_repetition_24;
+connect(Layer_24_wts_ddr.out[0],Layer_24_l2_wts.in[0]);
+read_access(Layer_24_wts_ddr.out[0]) = wts_ddr_read_pattern_24[0];
+write_access(Layer_24_l2_wts.in[0]) = wts_ddr_write_pattern_24[0];
+
+connect(Layer_24_wts_ddr.out[1],Layer_24_l2_wts.in[1]);
+read_access(Layer_24_wts_ddr.out[1]) = wts_ddr_read_pattern_24[1];
+write_access(Layer_24_l2_wts.in[1]) = wts_ddr_write_pattern_24[1];
+
+location<buffer>(Layer_27_l2_wts) = wts_loc_27;
+num_buffers(Layer_27_l2_wts) = 1;
+repetition_count(Layer_27_l2_wts) = wts_repetition_27;
+connect(Layer_27_wts_ddr.out[0],Layer_27_l2_wts.in[0]);
+read_access(Layer_27_wts_ddr.out[0]) = wts_ddr_read_pattern_27[0];
+write_access(Layer_27_l2_wts.in[0]) = wts_ddr_write_pattern_27[0];
+
+connect(Layer_27_wts_ddr.out[1],Layer_27_l2_wts.in[1]);
+read_access(Layer_27_wts_ddr.out[1]) = wts_ddr_read_pattern_27[1];
+write_access(Layer_27_l2_wts.in[1]) = wts_ddr_write_pattern_27[1];
+
+location<buffer>(Layer_28_l2_wts) = wts_loc_28;
+num_buffers(Layer_28_l2_wts) = 1;
+repetition_count(Layer_28_l2_wts) = wts_repetition_28;
+connect(Layer_28_wts_ddr.out[0],Layer_28_l2_wts.in[0]);
+read_access(Layer_28_wts_ddr.out[0]) = wts_ddr_read_pattern_28[0];
+write_access(Layer_28_l2_wts.in[0]) = wts_ddr_write_pattern_28[0];
+
+connect(Layer_28_wts_ddr.out[1],Layer_28_l2_wts.in[1]);
+read_access(Layer_28_wts_ddr.out[1]) = wts_ddr_read_pattern_28[1];
+write_access(Layer_28_l2_wts.in[1]) = wts_ddr_write_pattern_28[1];
+
+location<buffer>(Layer_34_l2_wts) = wts_loc_34;
+num_buffers(Layer_34_l2_wts) = 1;
+repetition_count(Layer_34_l2_wts) = wts_repetition_34;
+connect(Layer_34_wts_ddr.out[0],Layer_34_l2_wts.in[0]);
+read_access(Layer_34_wts_ddr.out[0]) = wts_ddr_read_pattern_34[0];
+write_access(Layer_34_l2_wts.in[0]) = wts_ddr_write_pattern_34[0];
+
+connect(Layer_34_wts_ddr.out[1],Layer_34_l2_wts.in[1]);
+read_access(Layer_34_wts_ddr.out[1]) = wts_ddr_read_pattern_34[1];
+write_access(Layer_34_l2_wts.in[1]) = wts_ddr_write_pattern_34[1];
+
+location<buffer>(Layer_35_l2_wts) = wts_loc_35;
+num_buffers(Layer_35_l2_wts) = 1;
+repetition_count(Layer_35_l2_wts) = wts_repetition_35;
+connect(Layer_35_wts_ddr.out[0],Layer_35_l2_wts.in[0]);
+read_access(Layer_35_wts_ddr.out[0]) = wts_ddr_read_pattern_35[0];
+write_access(Layer_35_l2_wts.in[0]) = wts_ddr_write_pattern_35[0];
+
+connect(Layer_35_wts_ddr.out[1],Layer_35_l2_wts.in[1]);
+read_access(Layer_35_wts_ddr.out[1]) = wts_ddr_read_pattern_35[1];
+write_access(Layer_35_l2_wts.in[1]) = wts_ddr_write_pattern_35[1];
+
+location<buffer>(Layer_36_l2_wts) = wts_loc_36;
+num_buffers(Layer_36_l2_wts) = 1;
+repetition_count(Layer_36_l2_wts) = wts_repetition_36;
+connect(Layer_36_wts_ddr.out[0],Layer_36_l2_wts.in[0]);
+read_access(Layer_36_wts_ddr.out[0]) = wts_ddr_read_pattern_36[0];
+write_access(Layer_36_l2_wts.in[0]) = wts_ddr_write_pattern_36[0];
+
+connect(Layer_36_wts_ddr.out[1],Layer_36_l2_wts.in[1]);
+read_access(Layer_36_wts_ddr.out[1]) = wts_ddr_read_pattern_36[1];
+write_access(Layer_36_l2_wts.in[1]) = wts_ddr_write_pattern_36[1];
+
+location<buffer>(Layer_39_l2_wts) = wts_loc_39;
+num_buffers(Layer_39_l2_wts) = 1;
+repetition_count(Layer_39_l2_wts) = wts_repetition_39;
+connect(Layer_39_wts_ddr.out[0],Layer_39_l2_wts.in[0]);
+read_access(Layer_39_wts_ddr.out[0]) = wts_ddr_read_pattern_39[0];
+write_access(Layer_39_l2_wts.in[0]) = wts_ddr_write_pattern_39[0];
+
+connect(Layer_39_wts_ddr.out[1],Layer_39_l2_wts.in[1]);
+read_access(Layer_39_wts_ddr.out[1]) = wts_ddr_read_pattern_39[1];
+write_access(Layer_39_l2_wts.in[1]) = wts_ddr_write_pattern_39[1];
+
+location<buffer>(Layer_40_l2_wts) = wts_loc_40;
+num_buffers(Layer_40_l2_wts) = 1;
+repetition_count(Layer_40_l2_wts) = wts_repetition_40;
+connect(Layer_40_wts_ddr.out[0],Layer_40_l2_wts.in[0]);
+read_access(Layer_40_wts_ddr.out[0]) = wts_ddr_read_pattern_40[0];
+write_access(Layer_40_l2_wts.in[0]) = wts_ddr_write_pattern_40[0];
+
+connect(Layer_40_wts_ddr.out[1],Layer_40_l2_wts.in[1]);
+read_access(Layer_40_wts_ddr.out[1]) = wts_ddr_read_pattern_40[1];
+write_access(Layer_40_l2_wts.in[1]) = wts_ddr_write_pattern_40[1];
+
+location<buffer>(Layer_46_l2_wts) = wts_loc_46;
+num_buffers(Layer_46_l2_wts) = 1;
+repetition_count(Layer_46_l2_wts) = wts_repetition_46;
+connect(Layer_46_wts_ddr.out[0],Layer_46_l2_wts.in[0]);
+read_access(Layer_46_wts_ddr.out[0]) = wts_ddr_read_pattern_46[0];
+write_access(Layer_46_l2_wts.in[0]) = wts_ddr_write_pattern_46[0];
+
+connect(Layer_46_wts_ddr.out[1],Layer_46_l2_wts.in[1]);
+read_access(Layer_46_wts_ddr.out[1]) = wts_ddr_read_pattern_46[1];
+write_access(Layer_46_l2_wts.in[1]) = wts_ddr_write_pattern_46[1];
+
+location<buffer>(Layer_47_l2_wts) = wts_loc_47;
+num_buffers(Layer_47_l2_wts) = 1;
+repetition_count(Layer_47_l2_wts) = wts_repetition_47;
+connect(Layer_47_wts_ddr.out[0],Layer_47_l2_wts.in[0]);
+read_access(Layer_47_wts_ddr.out[0]) = wts_ddr_read_pattern_47[0];
+write_access(Layer_47_l2_wts.in[0]) = wts_ddr_write_pattern_47[0];
+
+connect(Layer_47_wts_ddr.out[1],Layer_47_l2_wts.in[1]);
+read_access(Layer_47_wts_ddr.out[1]) = wts_ddr_read_pattern_47[1];
+write_access(Layer_47_l2_wts.in[1]) = wts_ddr_write_pattern_47[1];
+
+location<buffer>(Layer_48_l2_wts) = wts_loc_48;
+num_buffers(Layer_48_l2_wts) = 1;
+repetition_count(Layer_48_l2_wts) = wts_repetition_48;
+connect(Layer_48_wts_ddr.out[0],Layer_48_l2_wts.in[0]);
+read_access(Layer_48_wts_ddr.out[0]) = wts_ddr_read_pattern_48[0];
+write_access(Layer_48_l2_wts.in[0]) = wts_ddr_write_pattern_48[0];
+
+connect(Layer_48_wts_ddr.out[1],Layer_48_l2_wts.in[1]);
+read_access(Layer_48_wts_ddr.out[1]) = wts_ddr_read_pattern_48[1];
+write_access(Layer_48_l2_wts.in[1]) = wts_ddr_write_pattern_48[1];
+
+location<buffer>(Layer_51_l2_wts) = wts_loc_51;
+num_buffers(Layer_51_l2_wts) = 1;
+repetition_count(Layer_51_l2_wts) = wts_repetition_51;
+connect(Layer_51_wts_ddr.out[0],Layer_51_l2_wts.in[0]);
+read_access(Layer_51_wts_ddr.out[0]) = wts_ddr_read_pattern_51[0];
+write_access(Layer_51_l2_wts.in[0]) = wts_ddr_write_pattern_51[0];
+
+connect(Layer_51_wts_ddr.out[1],Layer_51_l2_wts.in[1]);
+read_access(Layer_51_wts_ddr.out[1]) = wts_ddr_read_pattern_51[1];
+write_access(Layer_51_l2_wts.in[1]) = wts_ddr_write_pattern_51[1];
+
+location<buffer>(Layer_52_l2_wts) = wts_loc_52;
+num_buffers(Layer_52_l2_wts) = 1;
+repetition_count(Layer_52_l2_wts) = wts_repetition_52;
+connect(Layer_52_wts_ddr.out[0],Layer_52_l2_wts.in[0]);
+read_access(Layer_52_wts_ddr.out[0]) = wts_ddr_read_pattern_52[0];
+write_access(Layer_52_l2_wts.in[0]) = wts_ddr_write_pattern_52[0];
+
+connect(Layer_52_wts_ddr.out[1],Layer_52_l2_wts.in[1]);
+read_access(Layer_52_wts_ddr.out[1]) = wts_ddr_read_pattern_52[1];
+write_access(Layer_52_l2_wts.in[1]) = wts_ddr_write_pattern_52[1];
+
+location<buffer>(Layer_58_l2_wts) = wts_loc_58;
+num_buffers(Layer_58_l2_wts) = 1;
+repetition_count(Layer_58_l2_wts) = wts_repetition_58;
+connect(Layer_58_wts_ddr.out[0],Layer_58_l2_wts.in[0]);
+read_access(Layer_58_wts_ddr.out[0]) = wts_ddr_read_pattern_58[0];
+write_access(Layer_58_l2_wts.in[0]) = wts_ddr_write_pattern_58[0];
+
+connect(Layer_58_wts_ddr.out[1],Layer_58_l2_wts.in[1]);
+read_access(Layer_58_wts_ddr.out[1]) = wts_ddr_read_pattern_58[1];
+write_access(Layer_58_l2_wts.in[1]) = wts_ddr_write_pattern_58[1];
+
+location<buffer>(Layer_59_l2_wts) = wts_loc_59;
+num_buffers(Layer_59_l2_wts) = 1;
+repetition_count(Layer_59_l2_wts) = wts_repetition_59;
+connect(Layer_59_wts_ddr.out[0],Layer_59_l2_wts.in[0]);
+read_access(Layer_59_wts_ddr.out[0]) = wts_ddr_read_pattern_59[0];
+write_access(Layer_59_l2_wts.in[0]) = wts_ddr_write_pattern_59[0];
+
+connect(Layer_59_wts_ddr.out[1],Layer_59_l2_wts.in[1]);
+read_access(Layer_59_wts_ddr.out[1]) = wts_ddr_read_pattern_59[1];
+write_access(Layer_59_l2_wts.in[1]) = wts_ddr_write_pattern_59[1];
+
+location<buffer>(Layer_65_l2_wts) = wts_loc_65;
+num_buffers(Layer_65_l2_wts) = 1;
+repetition_count(Layer_65_l2_wts) = wts_repetition_65;
+connect(Layer_65_wts_ddr.out[0],Layer_65_l2_wts.in[0]);
+read_access(Layer_65_wts_ddr.out[0]) = wts_ddr_read_pattern_65[0];
+write_access(Layer_65_l2_wts.in[0]) = wts_ddr_write_pattern_65[0];
+
+connect(Layer_65_wts_ddr.out[1],Layer_65_l2_wts.in[1]);
+read_access(Layer_65_wts_ddr.out[1]) = wts_ddr_read_pattern_65[1];
+write_access(Layer_65_l2_wts.in[1]) = wts_ddr_write_pattern_65[1];
+
+location<buffer>(Layer_70_l2_wts) = wts_loc_70;
+num_buffers(Layer_70_l2_wts) = 1;
+repetition_count(Layer_70_l2_wts) = wts_repetition_70;
+connect(Layer_70_wts_ddr.out[0],Layer_70_l2_wts.in[0]);
+read_access(Layer_70_wts_ddr.out[0]) = wts_ddr_read_pattern_70[0];
+write_access(Layer_70_l2_wts.in[0]) = wts_ddr_write_pattern_70[0];
+
+connect(Layer_70_wts_ddr.out[1],Layer_70_l2_wts.in[1]);
+read_access(Layer_70_wts_ddr.out[1]) = wts_ddr_read_pattern_70[1];
+write_access(Layer_70_l2_wts.in[1]) = wts_ddr_write_pattern_70[1];
+
+location<buffer>(Layer_71_l2_wts) = wts_loc_71;
+num_buffers(Layer_71_l2_wts) = 1;
+repetition_count(Layer_71_l2_wts) = wts_repetition_71;
+connect(Layer_71_wts_ddr.out[0],Layer_71_l2_wts.in[0]);
+read_access(Layer_71_wts_ddr.out[0]) = wts_ddr_read_pattern_71[0];
+write_access(Layer_71_l2_wts.in[0]) = wts_ddr_write_pattern_71[0];
+
+connect(Layer_71_wts_ddr.out[1],Layer_71_l2_wts.in[1]);
+read_access(Layer_71_wts_ddr.out[1]) = wts_ddr_read_pattern_71[1];
+write_access(Layer_71_l2_wts.in[1]) = wts_ddr_write_pattern_71[1];
+
+location<buffer>(Layer_76_l2_wts) = wts_loc_76;
+num_buffers(Layer_76_l2_wts) = 1;
+repetition_count(Layer_76_l2_wts) = wts_repetition_76;
+connect(Layer_76_wts_ddr.out[0],Layer_76_l2_wts.in[0]);
+read_access(Layer_76_wts_ddr.out[0]) = wts_ddr_read_pattern_76[0];
+write_access(Layer_76_l2_wts.in[0]) = wts_ddr_write_pattern_76[0];
+
+connect(Layer_76_wts_ddr.out[1],Layer_76_l2_wts.in[1]);
+read_access(Layer_76_wts_ddr.out[1]) = wts_ddr_read_pattern_76[1];
+write_access(Layer_76_l2_wts.in[1]) = wts_ddr_write_pattern_76[1];
+
+location<buffer>(Layer_81_l2_wts) = wts_loc_81;
+num_buffers(Layer_81_l2_wts) = 1;
+repetition_count(Layer_81_l2_wts) = wts_repetition_81;
+connect(Layer_81_wts_ddr.out[0],Layer_81_l2_wts.in[0]);
+read_access(Layer_81_wts_ddr.out[0]) = wts_ddr_read_pattern_81[0];
+write_access(Layer_81_l2_wts.in[0]) = wts_ddr_write_pattern_81[0];
+
+connect(Layer_81_wts_ddr.out[1],Layer_81_l2_wts.in[1]);
+read_access(Layer_81_wts_ddr.out[1]) = wts_ddr_read_pattern_81[1];
+write_access(Layer_81_l2_wts.in[1]) = wts_ddr_write_pattern_81[1];
+
+location<buffer>(Layer_82_l2_wts) = wts_loc_82;
+num_buffers(Layer_82_l2_wts) = 1;
+repetition_count(Layer_82_l2_wts) = wts_repetition_82;
+connect(Layer_82_wts_ddr.out[0],Layer_82_l2_wts.in[0]);
+read_access(Layer_82_wts_ddr.out[0]) = wts_ddr_read_pattern_82[0];
+write_access(Layer_82_l2_wts.in[0]) = wts_ddr_write_pattern_82[0];
+
+connect(Layer_82_wts_ddr.out[1],Layer_82_l2_wts.in[1]);
+read_access(Layer_82_wts_ddr.out[1]) = wts_ddr_read_pattern_82[1];
+write_access(Layer_82_l2_wts.in[1]) = wts_ddr_write_pattern_82[1];
+
+location<buffer>(Layer_87_l2_wts) = wts_loc_87;
+num_buffers(Layer_87_l2_wts) = 1;
+repetition_count(Layer_87_l2_wts) = wts_repetition_87;
+connect(Layer_87_wts_ddr.out[0],Layer_87_l2_wts.in[0]);
+read_access(Layer_87_wts_ddr.out[0]) = wts_ddr_read_pattern_87[0];
+write_access(Layer_87_l2_wts.in[0]) = wts_ddr_write_pattern_87[0];
+
+connect(Layer_87_wts_ddr.out[1],Layer_87_l2_wts.in[1]);
+read_access(Layer_87_wts_ddr.out[1]) = wts_ddr_read_pattern_87[1];
+write_access(Layer_87_l2_wts.in[1]) = wts_ddr_write_pattern_87[1];
+
+location<buffer>(Layer_92_l2_wts) = wts_loc_92;
+num_buffers(Layer_92_l2_wts) = 1;
+repetition_count(Layer_92_l2_wts) = wts_repetition_92;
+connect(Layer_92_wts_ddr.out[0],Layer_92_l2_wts.in[0]);
+read_access(Layer_92_wts_ddr.out[0]) = wts_ddr_read_pattern_92[0];
+write_access(Layer_92_l2_wts.in[0]) = wts_ddr_write_pattern_92[0];
+
+connect(Layer_92_wts_ddr.out[1],Layer_92_l2_wts.in[1]);
+read_access(Layer_92_wts_ddr.out[1]) = wts_ddr_read_pattern_92[1];
+write_access(Layer_92_l2_wts.in[1]) = wts_ddr_write_pattern_92[1];
+
+location<buffer>(Layer_93_l2_wts) = wts_loc_93;
+num_buffers(Layer_93_l2_wts) = 1;
+repetition_count(Layer_93_l2_wts) = wts_repetition_93;
+connect(Layer_93_wts_ddr.out[0],Layer_93_l2_wts.in[0]);
+read_access(Layer_93_wts_ddr.out[0]) = wts_ddr_read_pattern_93[0];
+write_access(Layer_93_l2_wts.in[0]) = wts_ddr_write_pattern_93[0];
+
+connect(Layer_93_wts_ddr.out[1],Layer_93_l2_wts.in[1]);
+read_access(Layer_93_wts_ddr.out[1]) = wts_ddr_read_pattern_93[1];
+write_access(Layer_93_l2_wts.in[1]) = wts_ddr_write_pattern_93[1];
+
+location<buffer>(Layer_98_l2_wts) = wts_loc_98;
+num_buffers(Layer_98_l2_wts) = 1;
+repetition_count(Layer_98_l2_wts) = wts_repetition_98;
+connect(Layer_98_wts_ddr.out[0],Layer_98_l2_wts.in[0]);
+read_access(Layer_98_wts_ddr.out[0]) = wts_ddr_read_pattern_98[0];
+write_access(Layer_98_l2_wts.in[0]) = wts_ddr_write_pattern_98[0];
+
+connect(Layer_98_wts_ddr.out[1],Layer_98_l2_wts.in[1]);
+read_access(Layer_98_wts_ddr.out[1]) = wts_ddr_read_pattern_98[1];
+write_access(Layer_98_l2_wts.in[1]) = wts_ddr_write_pattern_98[1];
+
+location<buffer>(Layer_103_l2_wts) = wts_loc_103;
+num_buffers(Layer_103_l2_wts) = 1;
+repetition_count(Layer_103_l2_wts) = wts_repetition_103;
+connect(Layer_103_wts_ddr.out[0],Layer_103_l2_wts.in[0]);
+read_access(Layer_103_wts_ddr.out[0]) = wts_ddr_read_pattern_103[0];
+write_access(Layer_103_l2_wts.in[0]) = wts_ddr_write_pattern_103[0];
+
+connect(Layer_103_wts_ddr.out[1],Layer_103_l2_wts.in[1]);
+read_access(Layer_103_wts_ddr.out[1]) = wts_ddr_read_pattern_103[1];
+write_access(Layer_103_l2_wts.in[1]) = wts_ddr_write_pattern_103[1];
+
+location<buffer>(Layer_104_l2_wts) = wts_loc_104;
+num_buffers(Layer_104_l2_wts) = 1;
+repetition_count(Layer_104_l2_wts) = wts_repetition_104;
+connect(Layer_104_wts_ddr.out[0],Layer_104_l2_wts.in[0]);
+read_access(Layer_104_wts_ddr.out[0]) = wts_ddr_read_pattern_104[0];
+write_access(Layer_104_l2_wts.in[0]) = wts_ddr_write_pattern_104[0];
+
+connect(Layer_104_wts_ddr.out[1],Layer_104_l2_wts.in[1]);
+read_access(Layer_104_wts_ddr.out[1]) = wts_ddr_read_pattern_104[1];
+write_access(Layer_104_l2_wts.in[1]) = wts_ddr_write_pattern_104[1];
+
+location<buffer>(Layer_109_l2_wts) = wts_loc_109;
+num_buffers(Layer_109_l2_wts) = 1;
+repetition_count(Layer_109_l2_wts) = wts_repetition_109;
+connect(Layer_109_wts_ddr.out[0],Layer_109_l2_wts.in[0]);
+read_access(Layer_109_wts_ddr.out[0]) = wts_ddr_read_pattern_109[0];
+write_access(Layer_109_l2_wts.in[0]) = wts_ddr_write_pattern_109[0];
+
+connect(Layer_109_wts_ddr.out[1],Layer_109_l2_wts.in[1]);
+read_access(Layer_109_wts_ddr.out[1]) = wts_ddr_read_pattern_109[1];
+write_access(Layer_109_l2_wts.in[1]) = wts_ddr_write_pattern_109[1];
+
+location<buffer>(Layer_116_l2_wts) = wts_loc_116;
+num_buffers(Layer_116_l2_wts) = 1;
+repetition_count(Layer_116_l2_wts) = wts_repetition_116;
+connect(Layer_116_wts_ddr.out[0],Layer_116_l2_wts.in[0]);
+read_access(Layer_116_wts_ddr.out[0]) = wts_ddr_read_pattern_116[0];
+write_access(Layer_116_l2_wts.in[0]) = wts_ddr_write_pattern_116[0];
+
+connect(Layer_116_wts_ddr.out[1],Layer_116_l2_wts.in[1]);
+read_access(Layer_116_wts_ddr.out[1]) = wts_ddr_read_pattern_116[1];
+write_access(Layer_116_l2_wts.in[1]) = wts_ddr_write_pattern_116[1];
+
+location<buffer>(Layer_117_l2_wts) = wts_loc_117;
+num_buffers(Layer_117_l2_wts) = 1;
+repetition_count(Layer_117_l2_wts) = wts_repetition_117;
+connect(Layer_117_wts_ddr.out[0],Layer_117_l2_wts.in[0]);
+read_access(Layer_117_wts_ddr.out[0]) = wts_ddr_read_pattern_117[0];
+write_access(Layer_117_l2_wts.in[0]) = wts_ddr_write_pattern_117[0];
+
+connect(Layer_117_wts_ddr.out[1],Layer_117_l2_wts.in[1]);
+read_access(Layer_117_wts_ddr.out[1]) = wts_ddr_read_pattern_117[1];
+write_access(Layer_117_l2_wts.in[1]) = wts_ddr_write_pattern_117[1];
+
+location<buffer>(Layer_123_l2_wts) = wts_loc_123;
+num_buffers(Layer_123_l2_wts) = 1;
+repetition_count(Layer_123_l2_wts) = wts_repetition_123;
+connect(Layer_123_wts_ddr.out[0],Layer_123_l2_wts.in[0]);
+read_access(Layer_123_wts_ddr.out[0]) = wts_ddr_read_pattern_123[0];
+write_access(Layer_123_l2_wts.in[0]) = wts_ddr_write_pattern_123[0];
+
+connect(Layer_123_wts_ddr.out[1],Layer_123_l2_wts.in[1]);
+read_access(Layer_123_wts_ddr.out[1]) = wts_ddr_read_pattern_123[1];
+write_access(Layer_123_l2_wts.in[1]) = wts_ddr_write_pattern_123[1];
+
+location<buffer>(Layer_124_l2_wts) = wts_loc_124;
+num_buffers(Layer_124_l2_wts) = 1;
+repetition_count(Layer_124_l2_wts) = wts_repetition_124;
+connect(Layer_124_wts_ddr.out[0],Layer_124_l2_wts.in[0]);
+read_access(Layer_124_wts_ddr.out[0]) = wts_ddr_read_pattern_124[0];
+write_access(Layer_124_l2_wts.in[0]) = wts_ddr_write_pattern_124[0];
+
+connect(Layer_124_wts_ddr.out[1],Layer_124_l2_wts.in[1]);
+read_access(Layer_124_wts_ddr.out[1]) = wts_ddr_read_pattern_124[1];
+write_access(Layer_124_l2_wts.in[1]) = wts_ddr_write_pattern_124[1];
+
+location<buffer>(Layer_129_l2_wts) = wts_loc_129;
+num_buffers(Layer_129_l2_wts) = 1;
+repetition_count(Layer_129_l2_wts) = wts_repetition_129;
+connect(Layer_129_wts_ddr.out[0],Layer_129_l2_wts.in[0]);
+read_access(Layer_129_wts_ddr.out[0]) = wts_ddr_read_pattern_129[0];
+write_access(Layer_129_l2_wts.in[0]) = wts_ddr_write_pattern_129[0];
+
+connect(Layer_129_wts_ddr.out[1],Layer_129_l2_wts.in[1]);
+read_access(Layer_129_wts_ddr.out[1]) = wts_ddr_read_pattern_129[1];
+write_access(Layer_129_l2_wts.in[1]) = wts_ddr_write_pattern_129[1];
+
+location<buffer>(Layer_136_l2_wts) = wts_loc_136;
+num_buffers(Layer_136_l2_wts) = 1;
+repetition_count(Layer_136_l2_wts) = wts_repetition_136;
+connect(Layer_136_wts_ddr.out[0],Layer_136_l2_wts.in[0]);
+read_access(Layer_136_wts_ddr.out[0]) = wts_ddr_read_pattern_136[0];
+write_access(Layer_136_l2_wts.in[0]) = wts_ddr_write_pattern_136[0];
+
+connect(Layer_136_wts_ddr.out[1],Layer_136_l2_wts.in[1]);
+read_access(Layer_136_wts_ddr.out[1]) = wts_ddr_read_pattern_136[1];
+write_access(Layer_136_l2_wts.in[1]) = wts_ddr_write_pattern_136[1];
+
+location<buffer>(Layer_137_l2_wts) = wts_loc_137;
+num_buffers(Layer_137_l2_wts) = 1;
+repetition_count(Layer_137_l2_wts) = wts_repetition_137;
+connect(Layer_137_wts_ddr.out[0],Layer_137_l2_wts.in[0]);
+read_access(Layer_137_wts_ddr.out[0]) = wts_ddr_read_pattern_137[0];
+write_access(Layer_137_l2_wts.in[0]) = wts_ddr_write_pattern_137[0];
+
+connect(Layer_137_wts_ddr.out[1],Layer_137_l2_wts.in[1]);
+read_access(Layer_137_wts_ddr.out[1]) = wts_ddr_read_pattern_137[1];
+write_access(Layer_137_l2_wts.in[1]) = wts_ddr_write_pattern_137[1];
+
+location<buffer>(Layer_143_l2_wts) = wts_loc_143;
+num_buffers(Layer_143_l2_wts) = 1;
+repetition_count(Layer_143_l2_wts) = wts_repetition_143;
+connect(Layer_143_wts_ddr.out[0],Layer_143_l2_wts.in[0]);
+read_access(Layer_143_wts_ddr.out[0]) = wts_ddr_read_pattern_143[0];
+write_access(Layer_143_l2_wts.in[0]) = wts_ddr_write_pattern_143[0];
+
+connect(Layer_143_wts_ddr.out[1],Layer_143_l2_wts.in[1]);
+read_access(Layer_143_wts_ddr.out[1]) = wts_ddr_read_pattern_143[1];
+write_access(Layer_143_l2_wts.in[1]) = wts_ddr_write_pattern_143[1];
+
+location<buffer>(Layer_144_l2_wts) = wts_loc_144;
+num_buffers(Layer_144_l2_wts) = 1;
+repetition_count(Layer_144_l2_wts) = wts_repetition_144;
+connect(Layer_144_wts_ddr.out[0],Layer_144_l2_wts.in[0]);
+read_access(Layer_144_wts_ddr.out[0]) = wts_ddr_read_pattern_144[0];
+write_access(Layer_144_l2_wts.in[0]) = wts_ddr_write_pattern_144[0];
+
+connect(Layer_144_wts_ddr.out[1],Layer_144_l2_wts.in[1]);
+read_access(Layer_144_wts_ddr.out[1]) = wts_ddr_read_pattern_144[1];
+write_access(Layer_144_l2_wts.in[1]) = wts_ddr_write_pattern_144[1];
+
+location<buffer>(Layer_149_l2_wts) = wts_loc_149;
+num_buffers(Layer_149_l2_wts) = 1;
+repetition_count(Layer_149_l2_wts) = wts_repetition_149;
+connect(Layer_149_wts_ddr.out[0],Layer_149_l2_wts.in[0]);
+read_access(Layer_149_wts_ddr.out[0]) = wts_ddr_read_pattern_149[0];
+write_access(Layer_149_l2_wts.in[0]) = wts_ddr_write_pattern_149[0];
+
+connect(Layer_149_wts_ddr.out[1],Layer_149_l2_wts.in[1]);
+read_access(Layer_149_wts_ddr.out[1]) = wts_ddr_read_pattern_149[1];
+write_access(Layer_149_l2_wts.in[1]) = wts_ddr_write_pattern_149[1];
+
+location<buffer>(Layer_156_l2_wts) = wts_loc_156;
+num_buffers(Layer_156_l2_wts) = 1;
+repetition_count(Layer_156_l2_wts) = wts_repetition_156;
+connect(Layer_156_wts_ddr.out[0],Layer_156_l2_wts.in[0]);
+read_access(Layer_156_wts_ddr.out[0]) = wts_ddr_read_pattern_156[0];
+write_access(Layer_156_l2_wts.in[0]) = wts_ddr_write_pattern_156[0];
+
+connect(Layer_156_wts_ddr.out[1],Layer_156_l2_wts.in[1]);
+read_access(Layer_156_wts_ddr.out[1]) = wts_ddr_read_pattern_156[1];
+write_access(Layer_156_l2_wts.in[1]) = wts_ddr_write_pattern_156[1];
+
+location<buffer>(Layer_157_l2_wts) = wts_loc_157;
+num_buffers(Layer_157_l2_wts) = 1;
+repetition_count(Layer_157_l2_wts) = wts_repetition_157;
+connect(Layer_157_wts_ddr.out[0],Layer_157_l2_wts.in[0]);
+read_access(Layer_157_wts_ddr.out[0]) = wts_ddr_read_pattern_157[0];
+write_access(Layer_157_l2_wts.in[0]) = wts_ddr_write_pattern_157[0];
+
+connect(Layer_157_wts_ddr.out[1],Layer_157_l2_wts.in[1]);
+read_access(Layer_157_wts_ddr.out[1]) = wts_ddr_read_pattern_157[1];
+write_access(Layer_157_l2_wts.in[1]) = wts_ddr_write_pattern_157[1];
+
+location<buffer>(Layer_163_l2_wts) = wts_loc_163;
+num_buffers(Layer_163_l2_wts) = 1;
+repetition_count(Layer_163_l2_wts) = wts_repetition_163;
+connect(Layer_163_wts_ddr.out[0],Layer_163_l2_wts.in[0]);
+read_access(Layer_163_wts_ddr.out[0]) = wts_ddr_read_pattern_163[0];
+write_access(Layer_163_l2_wts.in[0]) = wts_ddr_write_pattern_163[0];
+
+connect(Layer_163_wts_ddr.out[1],Layer_163_l2_wts.in[1]);
+read_access(Layer_163_wts_ddr.out[1]) = wts_ddr_read_pattern_163[1];
+write_access(Layer_163_l2_wts.in[1]) = wts_ddr_write_pattern_163[1];
+
+location<buffer>(Layer_164_l2_wts) = wts_loc_164;
+num_buffers(Layer_164_l2_wts) = 1;
+repetition_count(Layer_164_l2_wts) = wts_repetition_164;
+connect(Layer_164_wts_ddr.out[0],Layer_164_l2_wts.in[0]);
+read_access(Layer_164_wts_ddr.out[0]) = wts_ddr_read_pattern_164[0];
+write_access(Layer_164_l2_wts.in[0]) = wts_ddr_write_pattern_164[0];
+
+connect(Layer_164_wts_ddr.out[1],Layer_164_l2_wts.in[1]);
+read_access(Layer_164_wts_ddr.out[1]) = wts_ddr_read_pattern_164[1];
+write_access(Layer_164_l2_wts.in[1]) = wts_ddr_write_pattern_164[1];
+
+location<buffer>(Layer_169_l2_wts) = wts_loc_169;
+num_buffers(Layer_169_l2_wts) = 1;
+repetition_count(Layer_169_l2_wts) = wts_repetition_169;
+connect(Layer_169_wts_ddr.out[0],Layer_169_l2_wts.in[0]);
+read_access(Layer_169_wts_ddr.out[0]) = wts_ddr_read_pattern_169[0];
+write_access(Layer_169_l2_wts.in[0]) = wts_ddr_write_pattern_169[0];
+
+connect(Layer_169_wts_ddr.out[1],Layer_169_l2_wts.in[1]);
+read_access(Layer_169_wts_ddr.out[1]) = wts_ddr_read_pattern_169[1];
+write_access(Layer_169_l2_wts.in[1]) = wts_ddr_write_pattern_169[1];
+
+location<buffer>(Layer_176_l2_wts) = wts_loc_176;
+num_buffers(Layer_176_l2_wts) = 1;
+repetition_count(Layer_176_l2_wts) = wts_repetition_176;
+connect(Layer_176_wts_ddr.out[0],Layer_176_l2_wts.in[0]);
+read_access(Layer_176_wts_ddr.out[0]) = wts_ddr_read_pattern_176[0];
+write_access(Layer_176_l2_wts.in[0]) = wts_ddr_write_pattern_176[0];
+
+connect(Layer_176_wts_ddr.out[1],Layer_176_l2_wts.in[1]);
+read_access(Layer_176_wts_ddr.out[1]) = wts_ddr_read_pattern_176[1];
+write_access(Layer_176_l2_wts.in[1]) = wts_ddr_write_pattern_176[1];
+
+location<buffer>(Layer_177_l2_wts) = wts_loc_177;
+num_buffers(Layer_177_l2_wts) = 1;
+repetition_count(Layer_177_l2_wts) = wts_repetition_177;
+connect(Layer_177_wts_ddr.out[0],Layer_177_l2_wts.in[0]);
+read_access(Layer_177_wts_ddr.out[0]) = wts_ddr_read_pattern_177[0];
+write_access(Layer_177_l2_wts.in[0]) = wts_ddr_write_pattern_177[0];
+
+connect(Layer_177_wts_ddr.out[1],Layer_177_l2_wts.in[1]);
+read_access(Layer_177_wts_ddr.out[1]) = wts_ddr_read_pattern_177[1];
+write_access(Layer_177_l2_wts.in[1]) = wts_ddr_write_pattern_177[1];
+
+location<buffer>(Layer_183_l2_wts) = wts_loc_183;
+num_buffers(Layer_183_l2_wts) = 1;
+repetition_count(Layer_183_l2_wts) = wts_repetition_183;
+connect(Layer_183_wts_ddr.out[0],Layer_183_l2_wts.in[0]);
+read_access(Layer_183_wts_ddr.out[0]) = wts_ddr_read_pattern_183[0];
+write_access(Layer_183_l2_wts.in[0]) = wts_ddr_write_pattern_183[0];
+
+connect(Layer_183_wts_ddr.out[1],Layer_183_l2_wts.in[1]);
+read_access(Layer_183_wts_ddr.out[1]) = wts_ddr_read_pattern_183[1];
+write_access(Layer_183_l2_wts.in[1]) = wts_ddr_write_pattern_183[1];
+
+location<buffer>(Layer_184_l2_wts) = wts_loc_184;
+num_buffers(Layer_184_l2_wts) = 1;
+repetition_count(Layer_184_l2_wts) = wts_repetition_184;
+connect(Layer_184_wts_ddr.out[0],Layer_184_l2_wts.in[0]);
+read_access(Layer_184_wts_ddr.out[0]) = wts_ddr_read_pattern_184[0];
+write_access(Layer_184_l2_wts.in[0]) = wts_ddr_write_pattern_184[0];
+
+connect(Layer_184_wts_ddr.out[1],Layer_184_l2_wts.in[1]);
+read_access(Layer_184_wts_ddr.out[1]) = wts_ddr_read_pattern_184[1];
+write_access(Layer_184_l2_wts.in[1]) = wts_ddr_write_pattern_184[1];
+
+location<buffer>(Layer_189_l2_wts) = wts_loc_189;
+num_buffers(Layer_189_l2_wts) = 1;
+repetition_count(Layer_189_l2_wts) = wts_repetition_189;
+connect(Layer_189_wts_ddr.out[0],Layer_189_l2_wts.in[0]);
+read_access(Layer_189_wts_ddr.out[0]) = wts_ddr_read_pattern_189[0];
+write_access(Layer_189_l2_wts.in[0]) = wts_ddr_write_pattern_189[0];
+
+connect(Layer_189_wts_ddr.out[1],Layer_189_l2_wts.in[1]);
+read_access(Layer_189_wts_ddr.out[1]) = wts_ddr_read_pattern_189[1];
+write_access(Layer_189_l2_wts.in[1]) = wts_ddr_write_pattern_189[1];
+
+location<buffer>(Layer_196_l2_wts) = wts_loc_196;
+num_buffers(Layer_196_l2_wts) = 1;
+repetition_count(Layer_196_l2_wts) = wts_repetition_196;
+connect(Layer_196_wts_ddr.out[0],Layer_196_l2_wts.in[0]);
+read_access(Layer_196_wts_ddr.out[0]) = wts_ddr_read_pattern_196[0];
+write_access(Layer_196_l2_wts.in[0]) = wts_ddr_write_pattern_196[0];
+
+connect(Layer_196_wts_ddr.out[1],Layer_196_l2_wts.in[1]);
+read_access(Layer_196_wts_ddr.out[1]) = wts_ddr_read_pattern_196[1];
+write_access(Layer_196_l2_wts.in[1]) = wts_ddr_write_pattern_196[1];
+
+location<buffer>(Layer_197_l2_wts) = wts_loc_197;
+num_buffers(Layer_197_l2_wts) = 1;
+repetition_count(Layer_197_l2_wts) = wts_repetition_197;
+connect(Layer_197_wts_ddr.out[0],Layer_197_l2_wts.in[0]);
+read_access(Layer_197_wts_ddr.out[0]) = wts_ddr_read_pattern_197[0];
+write_access(Layer_197_l2_wts.in[0]) = wts_ddr_write_pattern_197[0];
+
+connect(Layer_197_wts_ddr.out[1],Layer_197_l2_wts.in[1]);
+read_access(Layer_197_wts_ddr.out[1]) = wts_ddr_read_pattern_197[1];
+write_access(Layer_197_l2_wts.in[1]) = wts_ddr_write_pattern_197[1];
+
+location<buffer>(Layer_203_l2_wts) = wts_loc_203;
+num_buffers(Layer_203_l2_wts) = 1;
+repetition_count(Layer_203_l2_wts) = wts_repetition_203;
+connect(Layer_203_wts_ddr.out[0],Layer_203_l2_wts.in[0]);
+read_access(Layer_203_wts_ddr.out[0]) = wts_ddr_read_pattern_203[0];
+write_access(Layer_203_l2_wts.in[0]) = wts_ddr_write_pattern_203[0];
+
+connect(Layer_203_wts_ddr.out[1],Layer_203_l2_wts.in[1]);
+read_access(Layer_203_wts_ddr.out[1]) = wts_ddr_read_pattern_203[1];
+write_access(Layer_203_l2_wts.in[1]) = wts_ddr_write_pattern_203[1];
+
+location<buffer>(Layer_204_l2_wts) = wts_loc_204;
+num_buffers(Layer_204_l2_wts) = 1;
+repetition_count(Layer_204_l2_wts) = wts_repetition_204;
+connect(Layer_204_wts_ddr.out[0],Layer_204_l2_wts.in[0]);
+read_access(Layer_204_wts_ddr.out[0]) = wts_ddr_read_pattern_204[0];
+write_access(Layer_204_l2_wts.in[0]) = wts_ddr_write_pattern_204[0];
+
+connect(Layer_204_wts_ddr.out[1],Layer_204_l2_wts.in[1]);
+read_access(Layer_204_wts_ddr.out[1]) = wts_ddr_read_pattern_204[1];
+write_access(Layer_204_l2_wts.in[1]) = wts_ddr_write_pattern_204[1];
+
+location<buffer>(Layer_211_l2_wts) = wts_loc_211;
+num_buffers(Layer_211_l2_wts) = 1;
+repetition_count(Layer_211_l2_wts) = wts_repetition_211;
+connect(Layer_211_wts_ddr.out[0],Layer_211_l2_wts.in[0]);
+read_access(Layer_211_wts_ddr.out[0]) = wts_ddr_read_pattern_211[0];
+write_access(Layer_211_l2_wts.in[0]) = wts_ddr_write_pattern_211[0];
+
+connect(Layer_211_wts_ddr.out[1],Layer_211_l2_wts.in[1]);
+read_access(Layer_211_wts_ddr.out[1]) = wts_ddr_read_pattern_211[1];
+write_access(Layer_211_l2_wts.in[1]) = wts_ddr_write_pattern_211[1];
+
+location<buffer>(Layer_214_l2_wts) = wts_loc_214;
+num_buffers(Layer_214_l2_wts) = 1;
+repetition_count(Layer_214_l2_wts) = wts_repetition_214;
+connect(Layer_214_wts_ddr.out[0],Layer_214_l2_wts.in[0]);
+read_access(Layer_214_wts_ddr.out[0]) = wts_ddr_read_pattern_214[0];
+write_access(Layer_214_l2_wts.in[0]) = wts_ddr_write_pattern_214[0];
+
+connect(Layer_214_wts_ddr.out[1],Layer_214_l2_wts.in[1]);
+read_access(Layer_214_wts_ddr.out[1]) = wts_ddr_read_pattern_214[1];
+write_access(Layer_214_l2_wts.in[1]) = wts_ddr_write_pattern_214[1];
+
+location<buffer>(Layer_218_l2_wts) = wts_loc_218;
+num_buffers(Layer_218_l2_wts) = 1;
+repetition_count(Layer_218_l2_wts) = wts_repetition_218;
+connect(Layer_218_wts_ddr.out[0],Layer_218_l2_wts.in[0]);
+read_access(Layer_218_wts_ddr.out[0]) = wts_ddr_read_pattern_218[0];
+write_access(Layer_218_l2_wts.in[0]) = wts_ddr_write_pattern_218[0];
+
+connect(Layer_218_wts_ddr.out[1],Layer_218_l2_wts.in[1]);
+read_access(Layer_218_wts_ddr.out[1]) = wts_ddr_read_pattern_218[1];
+write_access(Layer_218_l2_wts.in[1]) = wts_ddr_write_pattern_218[1];
+
+location<buffer>(Layer_226_l2_wts) = wts_loc_226;
+num_buffers(Layer_226_l2_wts) = 1;
+repetition_count(Layer_226_l2_wts) = wts_repetition_226;
+connect(Layer_226_wts_ddr.out[0],Layer_226_l2_wts.in[0]);
+read_access(Layer_226_wts_ddr.out[0]) = wts_ddr_read_pattern_226[0];
+write_access(Layer_226_l2_wts.in[0]) = wts_ddr_write_pattern_226[0];
+
+connect(Layer_226_wts_ddr.out[1],Layer_226_l2_wts.in[1]);
+read_access(Layer_226_wts_ddr.out[1]) = wts_ddr_read_pattern_226[1];
+write_access(Layer_226_l2_wts.in[1]) = wts_ddr_write_pattern_226[1];
+
+location<buffer>(Layer_237_l2_wts) = wts_loc_237;
+num_buffers(Layer_237_l2_wts) = 1;
+repetition_count(Layer_237_l2_wts) = wts_repetition_237;
+connect(Layer_237_wts_ddr.out[0],Layer_237_l2_wts.in[0]);
+read_access(Layer_237_wts_ddr.out[0]) = wts_ddr_read_pattern_237[0];
+write_access(Layer_237_l2_wts.in[0]) = wts_ddr_write_pattern_237[0];
+
+connect(Layer_237_wts_ddr.out[1],Layer_237_l2_wts.in[1]);
+read_access(Layer_237_wts_ddr.out[1]) = wts_ddr_read_pattern_237[1];
+write_access(Layer_237_l2_wts.in[1]) = wts_ddr_write_pattern_237[1];
+
+location<buffer>(Layer_241_l2_wts) = wts_loc_241;
+num_buffers(Layer_241_l2_wts) = 1;
+repetition_count(Layer_241_l2_wts) = wts_repetition_241;
+connect(Layer_241_wts_ddr.out[0],Layer_241_l2_wts.in[0]);
+read_access(Layer_241_wts_ddr.out[0]) = wts_ddr_read_pattern_241[0];
+write_access(Layer_241_l2_wts.in[0]) = wts_ddr_write_pattern_241[0];
+
+connect(Layer_241_wts_ddr.out[1],Layer_241_l2_wts.in[1]);
+read_access(Layer_241_wts_ddr.out[1]) = wts_ddr_read_pattern_241[1];
+write_access(Layer_241_l2_wts.in[1]) = wts_ddr_write_pattern_241[1];
+
+location<buffer>(Layer_249_l2_wts) = wts_loc_249;
+num_buffers(Layer_249_l2_wts) = 1;
+repetition_count(Layer_249_l2_wts) = wts_repetition_249;
+connect(Layer_249_wts_ddr.out[0],Layer_249_l2_wts.in[0]);
+read_access(Layer_249_wts_ddr.out[0]) = wts_ddr_read_pattern_249[0];
+write_access(Layer_249_l2_wts.in[0]) = wts_ddr_write_pattern_249[0];
+
+connect(Layer_249_wts_ddr.out[1],Layer_249_l2_wts.in[1]);
+read_access(Layer_249_wts_ddr.out[1]) = wts_ddr_read_pattern_249[1];
+write_access(Layer_249_l2_wts.in[1]) = wts_ddr_write_pattern_249[1];
+
+location<buffer>(Layer_257_l2_wts) = wts_loc_257;
+num_buffers(Layer_257_l2_wts) = 1;
+repetition_count(Layer_257_l2_wts) = wts_repetition_257;
+connect(Layer_257_wts_ddr.out[0],Layer_257_l2_wts.in[0]);
+read_access(Layer_257_wts_ddr.out[0]) = wts_ddr_read_pattern_257[0];
+write_access(Layer_257_l2_wts.in[0]) = wts_ddr_write_pattern_257[0];
+
+connect(Layer_257_wts_ddr.out[1],Layer_257_l2_wts.in[1]);
+read_access(Layer_257_wts_ddr.out[1]) = wts_ddr_read_pattern_257[1];
+write_access(Layer_257_l2_wts.in[1]) = wts_ddr_write_pattern_257[1];
+
+location<buffer>(Layer_261_l2_wts) = wts_loc_261;
+num_buffers(Layer_261_l2_wts) = 1;
+repetition_count(Layer_261_l2_wts) = wts_repetition_261;
+connect(Layer_261_wts_ddr.out[0],Layer_261_l2_wts.in[0]);
+read_access(Layer_261_wts_ddr.out[0]) = wts_ddr_read_pattern_261[0];
+write_access(Layer_261_l2_wts.in[0]) = wts_ddr_write_pattern_261[0];
+
+connect(Layer_261_wts_ddr.out[1],Layer_261_l2_wts.in[1]);
+read_access(Layer_261_wts_ddr.out[1]) = wts_ddr_read_pattern_261[1];
+write_access(Layer_261_l2_wts.in[1]) = wts_ddr_write_pattern_261[1];
+
+location<buffer>(Layer_269_l2_wts) = wts_loc_269;
+num_buffers(Layer_269_l2_wts) = 1;
+repetition_count(Layer_269_l2_wts) = wts_repetition_269;
+connect(Layer_269_wts_ddr.out[0],Layer_269_l2_wts.in[0]);
+read_access(Layer_269_wts_ddr.out[0]) = wts_ddr_read_pattern_269[0];
+write_access(Layer_269_l2_wts.in[0]) = wts_ddr_write_pattern_269[0];
+
+connect(Layer_269_wts_ddr.out[1],Layer_269_l2_wts.in[1]);
+read_access(Layer_269_wts_ddr.out[1]) = wts_ddr_read_pattern_269[1];
+write_access(Layer_269_l2_wts.in[1]) = wts_ddr_write_pattern_269[1];
+
+location<buffer>(Layer_276_l2_wts) = wts_loc_276;
+num_buffers(Layer_276_l2_wts) = 1;
+repetition_count(Layer_276_l2_wts) = wts_repetition_276;
+connect(Layer_276_wts_ddr.out[0],Layer_276_l2_wts.in[0]);
+read_access(Layer_276_wts_ddr.out[0]) = wts_ddr_read_pattern_276[0];
+write_access(Layer_276_l2_wts.in[0]) = wts_ddr_write_pattern_276[0];
+
+connect(Layer_276_wts_ddr.out[1],Layer_276_l2_wts.in[1]);
+read_access(Layer_276_wts_ddr.out[1]) = wts_ddr_read_pattern_276[1];
+write_access(Layer_276_l2_wts.in[1]) = wts_ddr_write_pattern_276[1];
+
+location<buffer>(Layer_280_l2_wts) = wts_loc_280;
+num_buffers(Layer_280_l2_wts) = 1;
+repetition_count(Layer_280_l2_wts) = wts_repetition_280;
+connect(Layer_280_wts_ddr.out[0],Layer_280_l2_wts.in[0]);
+read_access(Layer_280_wts_ddr.out[0]) = wts_ddr_read_pattern_280[0];
+write_access(Layer_280_l2_wts.in[0]) = wts_ddr_write_pattern_280[0];
+
+connect(Layer_280_wts_ddr.out[1],Layer_280_l2_wts.in[1]);
+read_access(Layer_280_wts_ddr.out[1]) = wts_ddr_read_pattern_280[1];
+write_access(Layer_280_l2_wts.in[1]) = wts_ddr_write_pattern_280[1];
+
+location<buffer>(Layer_288_l2_wts) = wts_loc_288;
+num_buffers(Layer_288_l2_wts) = 1;
+repetition_count(Layer_288_l2_wts) = wts_repetition_288;
+connect(Layer_288_wts_ddr.out[0],Layer_288_l2_wts.in[0]);
+read_access(Layer_288_wts_ddr.out[0]) = wts_ddr_read_pattern_288[0];
+write_access(Layer_288_l2_wts.in[0]) = wts_ddr_write_pattern_288[0];
+
+connect(Layer_288_wts_ddr.out[1],Layer_288_l2_wts.in[1]);
+read_access(Layer_288_wts_ddr.out[1]) = wts_ddr_read_pattern_288[1];
+write_access(Layer_288_l2_wts.in[1]) = wts_ddr_write_pattern_288[1];
+
+location<buffer>(Layer_295_l2_wts) = wts_loc_295;
+num_buffers(Layer_295_l2_wts) = 1;
+repetition_count(Layer_295_l2_wts) = wts_repetition_295;
+connect(Layer_295_wts_ddr.out[0],Layer_295_l2_wts.in[0]);
+read_access(Layer_295_wts_ddr.out[0]) = wts_ddr_read_pattern_295[0];
+write_access(Layer_295_l2_wts.in[0]) = wts_ddr_write_pattern_295[0];
+
+connect(Layer_295_wts_ddr.out[1],Layer_295_l2_wts.in[1]);
+read_access(Layer_295_wts_ddr.out[1]) = wts_ddr_read_pattern_295[1];
+write_access(Layer_295_l2_wts.in[1]) = wts_ddr_write_pattern_295[1];
+
+location<buffer>(Layer_296_l2_wts) = wts_loc_296;
+num_buffers(Layer_296_l2_wts) = 1;
+repetition_count(Layer_296_l2_wts) = wts_repetition_296;
+connect(Layer_296_wts_ddr.out[0],Layer_296_l2_wts.in[0]);
+read_access(Layer_296_wts_ddr.out[0]) = wts_ddr_read_pattern_296[0];
+write_access(Layer_296_l2_wts.in[0]) = wts_ddr_write_pattern_296[0];
+
+connect(Layer_296_wts_ddr.out[1],Layer_296_l2_wts.in[1]);
+read_access(Layer_296_wts_ddr.out[1]) = wts_ddr_read_pattern_296[1];
+write_access(Layer_296_l2_wts.in[1]) = wts_ddr_write_pattern_296[1];
+
+location<buffer>(Layer_297_l2_wts) = wts_loc_297;
+num_buffers(Layer_297_l2_wts) = 1;
+repetition_count(Layer_297_l2_wts) = wts_repetition_297;
+connect(Layer_297_wts_ddr.out[0],Layer_297_l2_wts.in[0]);
+read_access(Layer_297_wts_ddr.out[0]) = wts_ddr_read_pattern_297[0];
+write_access(Layer_297_l2_wts.in[0]) = wts_ddr_write_pattern_297[0];
+
+connect(Layer_297_wts_ddr.out[1],Layer_297_l2_wts.in[1]);
+read_access(Layer_297_wts_ddr.out[1]) = wts_ddr_read_pattern_297[1];
+write_access(Layer_297_l2_wts.in[1]) = wts_ddr_write_pattern_297[1];
+
+location<dma>(L2_IFM_Buffer_for_input0_0_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(ifm_ddr.out[0], L2_IFM_Buffer_for_input0_0_port0.in[0]);
+read_access(ifm_ddr.out[0]) = {
+  tiling({.buffer_dimension = {8, 4, 23, 320}, .tiling_dimension = {8, 4, 23, 160}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_for_input0_0_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 4, 23, 320}, .tiling_dimension = {8, 4, 23, 160}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_for_input0_0_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(ifm_ddr.out[1], L2_IFM_Buffer_for_input0_0_port0.in[1]);
+read_access(ifm_ddr.out[1]) = {
+  tiling({.buffer_dimension = {8, 4, 23, 320}, .tiling_dimension = {8, 4, 23, 160}, .offset = {0, 0, 0, 160}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_for_input0_0_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 4, 23, 320}, .tiling_dimension = {8, 4, 23, 160}, .offset = {0, 0, 0, 160}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[0].compute_node,
+                          L2_IFM_Buffer_for_input0_0_port0, tiling_params_layer_1, 0, 0);
+location<dma>(l2_1.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_1.out[0], l2l3_1_spill.in[0]);
+read_access(l2_1.out[0]) = {
+  tiling({.buffer_dimension = {8, 4, 24, 320}, .tiling_dimension = {8, 4, 23, 160}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_1_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 4, 23, 320}, .tiling_dimension = {8, 4, 23, 160}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_1.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_1.out[1], l2l3_1_spill.in[1]);
+read_access(l2_1.out[1]) = {
+  tiling({.buffer_dimension = {8, 4, 24, 320}, .tiling_dimension = {8, 4, 23, 160}, .offset = {0, 0, 0, 160}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_1_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 4, 23, 320}, .tiling_dimension = {8, 4, 23, 160}, .offset = {0, 0, 0, 160}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_CONST_IFM_Buffer_for_input5_0_port1.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(const_ifm_ddr_5.out[0], L2_CONST_IFM_Buffer_for_input5_0_port1.in[0]);
+read_access(const_ifm_ddr_5.out[0]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_CONST_IFM_Buffer_for_input5_0_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_CONST_IFM_Buffer_for_input5_0_port1.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(const_ifm_ddr_5.out[1], L2_CONST_IFM_Buffer_for_input5_0_port1.in[1]);
+read_access(const_ifm_ddr_5.out[1]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_CONST_IFM_Buffer_for_input5_0_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_5_for_layer_6_port0.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_5_spill.out[0], L2_IFM_Buffer_from_layer_5_for_layer_6_port0.in[0]);
+read_access(l2l3_5_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_5_for_layer_6_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_5_for_layer_6_port0.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_5_spill.out[1], L2_IFM_Buffer_from_layer_5_for_layer_6_port0.in[1]);
+read_access(l2l3_5_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_5_for_layer_6_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[1].compute_node,
+                          L2_IFM_Buffer_from_layer_5_for_layer_6_port0, tiling_params_layer_6, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[1].compute_node,
+                          L2_CONST_IFM_Buffer_for_input5_0_port1, tiling_params_layer_6_1, 0, 2);
+location<dma>(l2_6.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_6.out[0], l2l3_6_spill.in[0]);
+read_access(l2_6.out[0]) = {
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_6_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_6.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_6.out[1], l2l3_6_spill.in[1]);
+read_access(l2_6.out[1]) = {
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_6_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_CONST_IFM_Buffer_for_input4_0_port1.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(const_ifm_ddr_4.out[0], L2_CONST_IFM_Buffer_for_input4_0_port1.in[0]);
+read_access(const_ifm_ddr_4.out[0]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_CONST_IFM_Buffer_for_input4_0_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_CONST_IFM_Buffer_for_input4_0_port1.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(const_ifm_ddr_4.out[1], L2_CONST_IFM_Buffer_for_input4_0_port1.in[1]);
+read_access(const_ifm_ddr_4.out[1]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_CONST_IFM_Buffer_for_input4_0_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_6_for_layer_7_port0.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_6_spill.out[0], L2_IFM_Buffer_from_layer_6_for_layer_7_port0.in[0]);
+read_access(l2l3_6_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_6_for_layer_7_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_6_for_layer_7_port0.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_6_spill.out[1], L2_IFM_Buffer_from_layer_6_for_layer_7_port0.in[1]);
+read_access(l2l3_6_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_6_for_layer_7_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[2].compute_node,
+                          L2_IFM_Buffer_from_layer_6_for_layer_7_port0, tiling_params_layer_7, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[2].compute_node,
+                          L2_CONST_IFM_Buffer_for_input4_0_port1, tiling_params_layer_7_1, 0, 2);
+location<dma>(l2_7.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_7.out[0], l2l3_7_spill.in[0]);
+read_access(l2_7.out[0]) = {
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_7_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_7.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_7.out[1], l2l3_7_spill.in[1]);
+read_access(l2_7.out[1]) = {
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_7_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_7_for_layer_8_port0.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_7_spill.out[0], L2_IFM_Buffer_from_layer_7_for_layer_8_port0.in[0]);
+read_access(l2l3_7_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 30}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 30}, .offset = {0, 0, 0, 59}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 30}, .offset = {0, 0, 0, 119}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_7_for_layer_8_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 60}, .tiling_dimension = {8, 320, 1, 30}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 1, 61}, .tiling_dimension = {8, 320, 1, 30}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 320, 1, 61}, .tiling_dimension = {8, 320, 1, 30}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2})
+};
+location<dma>(L2_IFM_Buffer_from_layer_7_for_layer_8_port0.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_7_spill.out[1], L2_IFM_Buffer_from_layer_7_for_layer_8_port0.in[1]);
+read_access(l2l3_7_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 30}, .offset = {0, 0, 0, 30}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 31}, .offset = {0, 0, 0, 89}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 31}, .offset = {0, 0, 0, 149}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_7_for_layer_8_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 60}, .tiling_dimension = {8, 320, 1, 30}, .offset = {0, 0, 0, 30}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 1, 61}, .tiling_dimension = {8, 320, 1, 31}, .offset = {0, 0, 0, 30}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 320, 1, 61}, .tiling_dimension = {8, 320, 1, 31}, .offset = {0, 0, 0, 30}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[3].compute_node,
+                          L2_IFM_Buffer_from_layer_7_for_layer_8_port0, tiling_params_layer_8, 0, 0);
+location<dma>(l2_8.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_8.out[0], l2l3_8_spill.in[0]);
+read_access(l2_8.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_8_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_8.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_8.out[1], l2l3_8_spill.in[1]);
+read_access(l2_8.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_8_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_8_for_layer_9_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_8_spill.out[0], L2_IFM_Buffer_from_layer_8_for_layer_9_port0.in[0]);
+read_access(l2l3_8_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_8_for_layer_9_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_8_for_layer_9_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_8_spill.out[1], L2_IFM_Buffer_from_layer_8_for_layer_9_port0.in[1]);
+read_access(l2l3_8_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_8_for_layer_9_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[4].compute_node,
+                          L2_IFM_Buffer_from_layer_8_for_layer_9_port0, tiling_params_layer_9, 0, 0);
+location<dma>(l2_9.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_9.out[0], l2l3_9_spill.in[0]);
+read_access(l2_9.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 160, 2, 46}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_9_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 46}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_9.out[1]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2_9.out[1], l2l3_9_spill.in[1]);
+read_access(l2_9.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 160, 2, 44}, .offset = {0, 0, 0, 46}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_9_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 44}, .offset = {0, 0, 0, 46}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_9_for_layer_10_port0.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_9_spill.out[0], L2_IFM_Buffer_from_layer_9_for_layer_10_port0.in[0]);
+read_access(l2l3_9_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 45, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_9_for_layer_10_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 45}, .tiling_dimension = {8, 160, 2, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_9_for_layer_10_port0.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_9_spill.out[1], L2_IFM_Buffer_from_layer_9_for_layer_10_port0.in[1]);
+read_access(l2l3_9_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { {.dimension = 3, .stride = 45, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_9_for_layer_10_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 45}, .tiling_dimension = {8, 160, 2, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[5].compute_node,
+                          L2_IFM_Buffer_from_layer_9_for_layer_10_port0, tiling_params_layer_10, 0, 0);
+location<dma>(l2_10.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_10.out[0], l2l3_10_spill.in[0]);
+read_access(l2_10.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 160, 2, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_10_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 45, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_10.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_10.out[1], l2l3_10_spill.in[1]);
+read_access(l2_10.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 160, 2, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_10_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { {.dimension = 3, .stride = 45, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_10_for_layer_11_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_10_spill.out[0], L2_IFM_Buffer_from_layer_10_for_layer_11_port0.in[0]);
+read_access(l2l3_10_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_10_for_layer_11_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_10_for_layer_11_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_10_spill.out[1], L2_IFM_Buffer_from_layer_10_for_layer_11_port0.in[1]);
+read_access(l2l3_10_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_10_for_layer_11_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[6].compute_node,
+                          L2_IFM_Buffer_from_layer_10_for_layer_11_port0, tiling_params_layer_11, 0, 0);
+location<dma>(l2_11.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_11.out[0], l2l3_11_spill.in[0]);
+read_access(l2_11.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 160, 2, 46}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_11_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 46}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_11.out[1]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2_11.out[1], l2l3_11_spill.in[1]);
+read_access(l2_11.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 160, 2, 44}, .offset = {0, 0, 0, 46}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_11_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 44}, .offset = {0, 0, 0, 46}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_8_for_layer_12_port0.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_8_spill.out[2], L2_IFM_Buffer_from_layer_8_for_layer_12_port0.in[0]);
+read_access(l2l3_8_spill.out[2]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_8_for_layer_12_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_8_for_layer_12_port0.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_8_spill.out[3], L2_IFM_Buffer_from_layer_8_for_layer_12_port0.in[1]);
+read_access(l2l3_8_spill.out[3]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_8_for_layer_12_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_11_for_layer_12_port1.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_11_spill.out[0], L2_IFM_Buffer_from_layer_11_for_layer_12_port1.in[0]);
+read_access(l2l3_11_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_11_for_layer_12_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_11_for_layer_12_port1.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_11_spill.out[1], L2_IFM_Buffer_from_layer_11_for_layer_12_port1.in[1]);
+read_access(l2l3_11_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_11_for_layer_12_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[7].compute_node,
+                          L2_IFM_Buffer_from_layer_8_for_layer_12_port0, tiling_params_layer_12, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[7].compute_node,
+                          L2_IFM_Buffer_from_layer_11_for_layer_12_port1, tiling_params_layer_12_1, 0, 2);
+location<dma>(l2_12.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_12.out[0], l2l3_12_spill.in[0]);
+read_access(l2_12.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_12_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_12.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_12.out[1], l2l3_12_spill.in[1]);
+read_access(l2_12.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_12_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_12_for_layer_13_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_12_spill.out[0], L2_IFM_Buffer_from_layer_12_for_layer_13_port0.in[0]);
+read_access(l2l3_12_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_12_for_layer_13_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_12_for_layer_13_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_12_spill.out[1], L2_IFM_Buffer_from_layer_12_for_layer_13_port0.in[1]);
+read_access(l2l3_12_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_12_for_layer_13_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[8].compute_node,
+                          L2_IFM_Buffer_from_layer_12_for_layer_13_port0, tiling_params_layer_13, 0, 0);
+location<dma>(l2_13.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_13.out[0], l2l3_13_spill.in[0]);
+read_access(l2_13.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 96}, .tiling_dimension = {8, 160, 2, 48}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_13_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 48}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_13.out[1]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2_13.out[1], l2l3_13_spill.in[1]);
+read_access(l2_13.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 96}, .tiling_dimension = {8, 160, 2, 42}, .offset = {0, 0, 0, 48}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_13_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 42}, .offset = {0, 0, 0, 48}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_12_for_layer_14_port1.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_12_spill.out[2], L2_IFM_Buffer_from_layer_12_for_layer_14_port1.in[0]);
+read_access(l2l3_12_spill.out[2]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 45, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_12_for_layer_14_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 160, 2, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_12_for_layer_14_port1.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_12_spill.out[3], L2_IFM_Buffer_from_layer_12_for_layer_14_port1.in[1]);
+read_access(l2l3_12_spill.out[3]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { {.dimension = 3, .stride = 45, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_12_for_layer_14_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 160, 2, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_13_for_layer_14_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_13_spill.out[0], L2_IFM_Buffer_from_layer_13_for_layer_14_port0.in[0]);
+read_access(l2l3_13_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 22}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_13_for_layer_14_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 45}, .tiling_dimension = {8, 160, 2, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 2, 45}, .tiling_dimension = {8, 160, 2, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1})
+};
+location<dma>(L2_IFM_Buffer_from_layer_13_for_layer_14_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_13_spill.out[1], L2_IFM_Buffer_from_layer_13_for_layer_14_port0.in[1]);
+read_access(l2l3_13_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 23}, .offset = {0, 0, 0, 67}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_13_for_layer_14_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 45}, .tiling_dimension = {8, 160, 2, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 2, 45}, .tiling_dimension = {8, 160, 2, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[9].compute_node,
+                          L2_IFM_Buffer_from_layer_13_for_layer_14_port0, tiling_params_layer_14, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[9].compute_node,
+                          L2_IFM_Buffer_from_layer_12_for_layer_14_port1, tiling_params_layer_14_1, 0, 2);
+location<dma>(l2_14.out[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2_14.out[0], l2l3_14_spill.in[0]);
+read_access(l2_14.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 160, 2, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_14_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 45, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_14.out[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2_14.out[1], l2l3_14_spill.in[1]);
+read_access(l2_14.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 160, 2, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_14_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { {.dimension = 3, .stride = 45, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_14_for_layer_15_port0.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_14_spill.out[0], L2_IFM_Buffer_from_layer_14_for_layer_15_port0.in[0]);
+read_access(l2l3_14_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 9}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 18, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_14_for_layer_15_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 18}, .tiling_dimension = {8, 160, 2, 9}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_14_for_layer_15_port0.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_14_spill.out[1], L2_IFM_Buffer_from_layer_14_for_layer_15_port0.in[1]);
+read_access(l2l3_14_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 9}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 3, .stride = 18, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_14_for_layer_15_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 18}, .tiling_dimension = {8, 160, 2, 9}, .offset = {0, 0, 0, 9}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[10].compute_node,
+                          L2_IFM_Buffer_from_layer_14_for_layer_15_port0, tiling_params_layer_15, 0, 0);
+location<dma>(l2_15.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_15.out[0], l2l3_15_spill.in[0]);
+read_access(l2_15.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 8, 18}, .tiling_dimension = {8, 160, 8, 9}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_15_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 8, 9}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 18, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_15.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_15.out[1], l2l3_15_spill.in[1]);
+read_access(l2_15.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 8, 18}, .tiling_dimension = {8, 160, 8, 9}, .offset = {0, 0, 0, 9}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_15_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 8, 9}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 3, .stride = 18, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_15_for_layer_16_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_15_spill.out[0], L2_IFM_Buffer_from_layer_15_for_layer_16_port0.in[0]);
+read_access(l2l3_15_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 8, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 8, 8}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 8, 8}, .offset = {0, 0, 0, 31}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 8, 8}, .offset = {0, 0, 0, 47}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 8, 8}, .offset = {0, 0, 0, 63}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 8, 5}, .offset = {0, 0, 0, 79}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_15_for_layer_16_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 8, 16}, .tiling_dimension = {8, 160, 8, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 17}, .tiling_dimension = {8, 160, 8, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 160, 8, 17}, .tiling_dimension = {8, 160, 8, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2}),
+  tiling({.buffer_dimension = {8, 160, 8, 17}, .tiling_dimension = {8, 160, 8, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 3}),
+  tiling({.buffer_dimension = {8, 160, 8, 17}, .tiling_dimension = {8, 160, 8, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 4}),
+  tiling({.buffer_dimension = {8, 160, 8, 11}, .tiling_dimension = {8, 160, 8, 5}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 5})
+};
+location<dma>(L2_IFM_Buffer_from_layer_15_for_layer_16_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_15_spill.out[1], L2_IFM_Buffer_from_layer_15_for_layer_16_port0.in[1]);
+read_access(l2l3_15_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 8, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 8, 9}, .offset = {0, 0, 0, 23}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 8, 9}, .offset = {0, 0, 0, 39}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 8, 9}, .offset = {0, 0, 0, 55}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 8, 9}, .offset = {0, 0, 0, 71}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 8, 6}, .offset = {0, 0, 0, 84}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_15_for_layer_16_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 8, 16}, .tiling_dimension = {8, 160, 8, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 17}, .tiling_dimension = {8, 160, 8, 9}, .offset = {0, 0, 0, 8}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 160, 8, 17}, .tiling_dimension = {8, 160, 8, 9}, .offset = {0, 0, 0, 8}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2}),
+  tiling({.buffer_dimension = {8, 160, 8, 17}, .tiling_dimension = {8, 160, 8, 9}, .offset = {0, 0, 0, 8}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 3}),
+  tiling({.buffer_dimension = {8, 160, 8, 17}, .tiling_dimension = {8, 160, 8, 9}, .offset = {0, 0, 0, 8}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 4}),
+  tiling({.buffer_dimension = {8, 160, 8, 11}, .tiling_dimension = {8, 160, 8, 6}, .offset = {0, 0, 0, 5}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 5})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[11].compute_node,
+                          L2_IFM_Buffer_from_layer_15_for_layer_16_port0, tiling_params_layer_16, 0, 0);
+location<dma>(l2_16.out[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2_16.out[0], l2l3_16_spill.in[0]);
+read_access(l2_16.out[0]) = {
+  tiling({.buffer_dimension = {8, 84, 8, 8}, .tiling_dimension = {8, 80, 8, 4}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_16_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 80, 8, 4}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_16.out[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2_16.out[1], l2l3_16_spill.in[1]);
+read_access(l2_16.out[1]) = {
+  tiling({.buffer_dimension = {8, 84, 8, 8}, .tiling_dimension = {8, 80, 8, 4}, .offset = {0, 0, 0, 4}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_16_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 80, 8, 4}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_17_for_layer_18_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_17_spill.out[0], L2_IFM_Buffer_from_layer_17_for_layer_18_port0.in[0]);
+read_access(l2l3_17_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 80, 8, 45}, .tiling_dimension = {8, 80, 8, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_17_for_layer_18_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 80, 8, 45}, .tiling_dimension = {8, 80, 8, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_17_for_layer_18_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_17_spill.out[1], L2_IFM_Buffer_from_layer_17_for_layer_18_port0.in[1]);
+read_access(l2l3_17_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 80, 8, 45}, .tiling_dimension = {8, 80, 8, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_17_for_layer_18_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 80, 8, 45}, .tiling_dimension = {8, 80, 8, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[12].compute_node,
+                          L2_IFM_Buffer_from_layer_17_for_layer_18_port0, tiling_params_layer_18, 0, 0);
+location<dma>(l2_18.out[4]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2_18.out[4], L3_OFM_Buffer_layer_TGSpilling_1818.in[0]);
+read_access(l2_18.out[4]) = {
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 80, 3, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_1818.in[0]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_18.out[5]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2_18.out[5], L3_OFM_Buffer_layer_TGSpilling_1818.in[1]);
+read_access(l2_18.out[5]) = {
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 80, 3, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_1818.in[1]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[13].compute_node,
+                          l2_18, tiling_params_layer_19, 0, 0);
+location<dma>(l2_19.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_19.out[0], l2l3_19_spill.in[0]);
+read_access(l2_19.out[0]) = {
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 80, 9, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_19_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 80, 9, 45}, .tiling_dimension = {8, 80, 9, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_19.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_19.out[1], l2l3_19_spill.in[1]);
+read_access(l2_19.out[1]) = {
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 80, 9, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_19_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 80, 9, 45}, .tiling_dimension = {8, 80, 9, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_19_for_layer_20_port0.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_19_spill.out[0], L2_IFM_Buffer_from_layer_19_for_layer_20_port0.in[0]);
+read_access(l2l3_19_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 80, 9, 45}, .tiling_dimension = {8, 80, 9, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 9, 45}, .tiling_dimension = {8, 80, 9, 11}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_19_for_layer_20_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 80, 9, 24}, .tiling_dimension = {8, 80, 9, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 9, 23}, .tiling_dimension = {8, 80, 9, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1})
+};
+location<dma>(L2_IFM_Buffer_from_layer_19_for_layer_20_port0.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_19_spill.out[1], L2_IFM_Buffer_from_layer_19_for_layer_20_port0.in[1]);
+read_access(l2l3_19_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 80, 9, 45}, .tiling_dimension = {8, 80, 9, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 9, 45}, .tiling_dimension = {8, 80, 9, 12}, .offset = {0, 0, 0, 33}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_19_for_layer_20_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 80, 9, 24}, .tiling_dimension = {8, 80, 9, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 9, 23}, .tiling_dimension = {8, 80, 9, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[14].compute_node,
+                          L2_IFM_Buffer_from_layer_19_for_layer_20_port0, tiling_params_layer_20, 0, 0);
+location<dma>(l2_20.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_20.out[0], l2l3_20_spill.in[0]);
+read_access(l2_20.out[0]) = {
+  tiling({.buffer_dimension = {8, 80, 12, 24}, .tiling_dimension = {8, 80, 9, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_20_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 80, 9, 46}, .tiling_dimension = {8, 80, 9, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 23, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_20.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_20.out[1], l2l3_20_spill.in[1]);
+read_access(l2_20.out[1]) = {
+  tiling({.buffer_dimension = {8, 80, 12, 24}, .tiling_dimension = {8, 80, 9, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_20_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 80, 9, 46}, .tiling_dimension = {8, 80, 9, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { {.dimension = 3, .stride = 23, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_1818.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L3_OFM_Buffer_layer_TGSpilling_1818.out[0], L2_OFM_Buffer_layer_TGSpilling_1818.in[0]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_1818.out[0]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_1818.in[0]) = {
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 80, 3, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_1818.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L3_OFM_Buffer_layer_TGSpilling_1818.out[1], L2_OFM_Buffer_layer_TGSpilling_1818.in[1]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_1818.out[1]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_1818.in[1]) = {
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 80, 3, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_21_for_layer_22_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_21_spill.out[0], L2_IFM_Buffer_from_layer_21_for_layer_22_port0.in[0]);
+read_access(l2l3_21_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 80, 9, 45}, .tiling_dimension = {8, 80, 9, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_21_for_layer_22_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 80, 9, 45}, .tiling_dimension = {8, 80, 9, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_21_for_layer_22_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_21_spill.out[1], L2_IFM_Buffer_from_layer_21_for_layer_22_port0.in[1]);
+read_access(l2l3_21_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 80, 9, 45}, .tiling_dimension = {8, 80, 9, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_21_for_layer_22_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 80, 9, 45}, .tiling_dimension = {8, 80, 9, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[15].compute_node,
+                          L2_IFM_Buffer_from_layer_21_for_layer_22_port0, tiling_params_layer_22, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[15].compute_node,
+                          L2_OFM_Buffer_layer_TGSpilling_1818, tiling_params_layer_22_1, 0, 2);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[16].compute_node,
+                          l2_22, tiling_params_layer_23, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[17].compute_node,
+                          l2_23, tiling_params_layer_24, 0, 0);
+location<dma>(l2_24.out[2]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_24.out[2], L3_OFM_Buffer_layer_TGSpilling_2424.in[0]);
+read_access(l2_24.out[2]) = {
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 40, 9, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_2424.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 9, 23}, .tiling_dimension = {8, 40, 9, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_24.out[3]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_24.out[3], L3_OFM_Buffer_layer_TGSpilling_2424.in[1]);
+read_access(l2_24.out[3]) = {
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 40, 9, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_2424.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 9, 23}, .tiling_dimension = {8, 40, 9, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_24.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_24.out[0], l2l3_24_spill.in[0]);
+read_access(l2_24.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 40, 9, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_24_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 9, 23}, .tiling_dimension = {8, 40, 9, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_24.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_24.out[1], l2l3_24_spill.in[1]);
+read_access(l2_24.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 40, 9, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_24_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 9, 23}, .tiling_dimension = {8, 40, 9, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_25_for_layer_26_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_25_spill.out[0], L2_IFM_Buffer_from_layer_25_for_layer_26_port0.in[0]);
+read_access(l2l3_25_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 920, 9, 1}, .tiling_dimension = {8, 920, 9, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_25_for_layer_26_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 920, 9, 1}, .tiling_dimension = {8, 920, 9, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_25_for_layer_26_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_25_spill.out[1], L2_IFM_Buffer_from_layer_25_for_layer_26_port0.in[1]);
+read_access(l2l3_25_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 920, 9, 1}, .tiling_dimension = {8, 920, 9, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_25_for_layer_26_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 920, 9, 1}, .tiling_dimension = {8, 920, 9, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[18].compute_node,
+                          L2_IFM_Buffer_from_layer_25_for_layer_26_port0, tiling_params_layer_26, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[19].compute_node,
+                          l2_26, tiling_params_layer_27, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[20].compute_node,
+                          l2_27, tiling_params_layer_28, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[21].compute_node,
+                          l2_28, tiling_params_layer_29, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[22].compute_node,
+                          l2_29, tiling_params_layer_30, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[23].compute_node,
+                          l2_30, tiling_params_layer_31, 0, 0);
+location<dma>(l2_31.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_31.out[0], l2l3_31_spill.in[0]);
+read_access(l2_31.out[0]) = {
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 9, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_31_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 1, 9, 1}, .tiling_dimension = {8, 1, 9, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_31.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_31.out[1], l2l3_31_spill.in[1]);
+read_access(l2_31.out[1]) = {
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 9, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_31_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 1, 9, 1}, .tiling_dimension = {8, 1, 9, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_32_for_layer_33_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_32_spill.out[0], L2_IFM_Buffer_from_layer_32_for_layer_33_port0.in[0]);
+read_access(l2l3_32_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 9, 23}, .tiling_dimension = {8, 40, 9, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_32_for_layer_33_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 9, 23}, .tiling_dimension = {8, 40, 9, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_32_for_layer_33_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_32_spill.out[1], L2_IFM_Buffer_from_layer_32_for_layer_33_port0.in[1]);
+read_access(l2l3_32_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 9, 23}, .tiling_dimension = {8, 40, 9, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_32_for_layer_33_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 9, 23}, .tiling_dimension = {8, 40, 9, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_2424.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L3_OFM_Buffer_layer_TGSpilling_2424.out[0], L2_OFM_Buffer_layer_TGSpilling_2424.in[0]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_2424.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 9, 23}, .tiling_dimension = {8, 40, 9, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_2424.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 40, 9, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_2424.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L3_OFM_Buffer_layer_TGSpilling_2424.out[1], L2_OFM_Buffer_layer_TGSpilling_2424.in[1]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_2424.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 9, 23}, .tiling_dimension = {8, 40, 9, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_2424.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 40, 9, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[24].compute_node,
+                          L2_IFM_Buffer_from_layer_32_for_layer_33_port0, tiling_params_layer_33, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[24].compute_node,
+                          L2_OFM_Buffer_layer_TGSpilling_2424, tiling_params_layer_33_1, 0, 2);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[25].compute_node,
+                          l2_33, tiling_params_layer_34, 0, 0);
+location<dma>(l2_34.out[4]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_34.out[4], L3_OFM_Buffer_layer_TGSpilling_3434.in[0]);
+read_access(l2_34.out[4]) = {
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_3434.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_34.out[5]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_34.out[5], L3_OFM_Buffer_layer_TGSpilling_3434.in[1]);
+read_access(l2_34.out[5]) = {
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_3434.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[26].compute_node,
+                          l2_34, tiling_params_layer_35, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[27].compute_node,
+                          l2_35, tiling_params_layer_36, 0, 0);
+location<dma>(l2_36.out[2]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_36.out[2], L3_OFM_Buffer_layer_TGSpilling_3636.in[0]);
+read_access(l2_36.out[2]) = {
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 40, 15, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_3636.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 40, 15, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_36.out[3]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_36.out[3], L3_OFM_Buffer_layer_TGSpilling_3636.in[1]);
+read_access(l2_36.out[3]) = {
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 40, 15, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_3636.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 40, 15, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_36.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_36.out[0], l2l3_36_spill.in[0]);
+read_access(l2_36.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 40, 15, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_36_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 40, 15, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_36.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_36.out[1], l2l3_36_spill.in[1]);
+read_access(l2_36.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 40, 15, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_36_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 40, 15, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_37_for_layer_38_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_37_spill.out[0], L2_IFM_Buffer_from_layer_37_for_layer_38_port0.in[0]);
+read_access(l2l3_37_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 920, 15, 1}, .tiling_dimension = {8, 920, 15, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_37_for_layer_38_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 920, 15, 1}, .tiling_dimension = {8, 920, 15, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_37_for_layer_38_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_37_spill.out[1], L2_IFM_Buffer_from_layer_37_for_layer_38_port0.in[1]);
+read_access(l2l3_37_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 920, 15, 1}, .tiling_dimension = {8, 920, 15, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_37_for_layer_38_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 920, 15, 1}, .tiling_dimension = {8, 920, 15, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[28].compute_node,
+                          L2_IFM_Buffer_from_layer_37_for_layer_38_port0, tiling_params_layer_38, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[29].compute_node,
+                          l2_38, tiling_params_layer_39, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[30].compute_node,
+                          l2_39, tiling_params_layer_40, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[31].compute_node,
+                          l2_40, tiling_params_layer_41, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[32].compute_node,
+                          l2_41, tiling_params_layer_42, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[33].compute_node,
+                          l2_42, tiling_params_layer_43, 0, 0);
+location<dma>(l2_43.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_43.out[0], l2l3_43_spill.in[0]);
+read_access(l2_43.out[0]) = {
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 15, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_43_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 1, 15, 1}, .tiling_dimension = {8, 1, 15, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_43.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_43.out[1], l2l3_43_spill.in[1]);
+read_access(l2_43.out[1]) = {
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 15, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_43_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 1, 15, 1}, .tiling_dimension = {8, 1, 15, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_44_for_layer_45_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_44_spill.out[0], L2_IFM_Buffer_from_layer_44_for_layer_45_port0.in[0]);
+read_access(l2l3_44_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 40, 15, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_44_for_layer_45_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 40, 15, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_44_for_layer_45_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_44_spill.out[1], L2_IFM_Buffer_from_layer_44_for_layer_45_port0.in[1]);
+read_access(l2l3_44_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 40, 15, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_44_for_layer_45_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 40, 15, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_3636.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L3_OFM_Buffer_layer_TGSpilling_3636.out[0], L2_OFM_Buffer_layer_TGSpilling_3636.in[0]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_3636.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 40, 15, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_3636.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 40, 15, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_3636.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L3_OFM_Buffer_layer_TGSpilling_3636.out[1], L2_OFM_Buffer_layer_TGSpilling_3636.in[1]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_3636.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 40, 15, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_3636.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 40, 15, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[34].compute_node,
+                          L2_IFM_Buffer_from_layer_44_for_layer_45_port0, tiling_params_layer_45, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[34].compute_node,
+                          L2_OFM_Buffer_layer_TGSpilling_3636, tiling_params_layer_45_1, 0, 2);
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_3434.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L3_OFM_Buffer_layer_TGSpilling_3434.out[0], L2_OFM_Buffer_layer_TGSpilling_3434.in[0]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_3434.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_3434.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_3434.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L3_OFM_Buffer_layer_TGSpilling_3434.out[1], L2_OFM_Buffer_layer_TGSpilling_3434.in[1]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_3434.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_3434.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[35].compute_node,
+                          l2_45, tiling_params_layer_46, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[35].compute_node,
+                          L2_OFM_Buffer_layer_TGSpilling_3434, tiling_params_layer_46_1, 0, 2);
+location<dma>(l2_46.out[4]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_46.out[4], L3_OFM_Buffer_layer_TGSpilling_4646.in[0]);
+read_access(l2_46.out[4]) = {
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_4646.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_46.out[5]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_46.out[5], L3_OFM_Buffer_layer_TGSpilling_4646.in[1]);
+read_access(l2_46.out[5]) = {
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_4646.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[36].compute_node,
+                          l2_46, tiling_params_layer_47, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[37].compute_node,
+                          l2_47, tiling_params_layer_48, 0, 0);
+location<dma>(l2_48.out[2]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_48.out[2], L3_OFM_Buffer_layer_TGSpilling_4848.in[0]);
+read_access(l2_48.out[2]) = {
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 40, 15, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_4848.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 40, 15, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_48.out[3]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_48.out[3], L3_OFM_Buffer_layer_TGSpilling_4848.in[1]);
+read_access(l2_48.out[3]) = {
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 40, 15, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_4848.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 40, 15, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_48.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_48.out[0], l2l3_48_spill.in[0]);
+read_access(l2_48.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 40, 15, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_48_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 40, 15, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_48.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_48.out[1], l2l3_48_spill.in[1]);
+read_access(l2_48.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 40, 15, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_48_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 40, 15, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_49_for_layer_50_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_49_spill.out[0], L2_IFM_Buffer_from_layer_49_for_layer_50_port0.in[0]);
+read_access(l2l3_49_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 920, 15, 1}, .tiling_dimension = {8, 920, 15, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_49_for_layer_50_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 920, 15, 1}, .tiling_dimension = {8, 920, 15, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_49_for_layer_50_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_49_spill.out[1], L2_IFM_Buffer_from_layer_49_for_layer_50_port0.in[1]);
+read_access(l2l3_49_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 920, 15, 1}, .tiling_dimension = {8, 920, 15, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_49_for_layer_50_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 920, 15, 1}, .tiling_dimension = {8, 920, 15, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[38].compute_node,
+                          L2_IFM_Buffer_from_layer_49_for_layer_50_port0, tiling_params_layer_50, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[39].compute_node,
+                          l2_50, tiling_params_layer_51, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[40].compute_node,
+                          l2_51, tiling_params_layer_52, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[41].compute_node,
+                          l2_52, tiling_params_layer_53, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[42].compute_node,
+                          l2_53, tiling_params_layer_54, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[43].compute_node,
+                          l2_54, tiling_params_layer_55, 0, 0);
+location<dma>(l2_55.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_55.out[0], l2l3_55_spill.in[0]);
+read_access(l2_55.out[0]) = {
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 15, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_55_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 1, 15, 1}, .tiling_dimension = {8, 1, 15, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_55.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_55.out[1], l2l3_55_spill.in[1]);
+read_access(l2_55.out[1]) = {
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 15, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_55_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 1, 15, 1}, .tiling_dimension = {8, 1, 15, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_56_for_layer_57_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_56_spill.out[0], L2_IFM_Buffer_from_layer_56_for_layer_57_port0.in[0]);
+read_access(l2l3_56_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 40, 15, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_56_for_layer_57_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 40, 15, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_56_for_layer_57_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_56_spill.out[1], L2_IFM_Buffer_from_layer_56_for_layer_57_port0.in[1]);
+read_access(l2l3_56_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 40, 15, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_56_for_layer_57_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 40, 15, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_4848.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L3_OFM_Buffer_layer_TGSpilling_4848.out[0], L2_OFM_Buffer_layer_TGSpilling_4848.in[0]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_4848.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 40, 15, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_4848.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 40, 15, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_4848.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L3_OFM_Buffer_layer_TGSpilling_4848.out[1], L2_OFM_Buffer_layer_TGSpilling_4848.in[1]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_4848.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 40, 15, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_4848.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 40, 15, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[44].compute_node,
+                          L2_IFM_Buffer_from_layer_56_for_layer_57_port0, tiling_params_layer_57, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[44].compute_node,
+                          L2_OFM_Buffer_layer_TGSpilling_4848, tiling_params_layer_57_1, 0, 2);
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_4646.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L3_OFM_Buffer_layer_TGSpilling_4646.out[0], L2_OFM_Buffer_layer_TGSpilling_4646.in[0]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_4646.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_4646.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_4646.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L3_OFM_Buffer_layer_TGSpilling_4646.out[1], L2_OFM_Buffer_layer_TGSpilling_4646.in[1]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_4646.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_4646.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[45].compute_node,
+                          l2_57, tiling_params_layer_58, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[45].compute_node,
+                          L2_OFM_Buffer_layer_TGSpilling_4646, tiling_params_layer_58_1, 0, 2);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[46].compute_node,
+                          l2_58, tiling_params_layer_59, 0, 0);
+location<dma>(l2_59.out[4]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2_59.out[4], l2l3_59_spill.in[0]);
+read_access(l2_59.out[4]) = {
+  tiling({.buffer_dimension = {8, 64, 32, 24}, .tiling_dimension = {8, 40, 30, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_59_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 30, 23}, .tiling_dimension = {8, 40, 30, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_59.out[5]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2_59.out[5], l2l3_59_spill.in[1]);
+read_access(l2_59.out[5]) = {
+  tiling({.buffer_dimension = {8, 64, 32, 24}, .tiling_dimension = {8, 40, 30, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_59_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 30, 23}, .tiling_dimension = {8, 40, 30, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[47].compute_node,
+                          l2_59, tiling_params_layer_60, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[48].compute_node,
+                          l2_60, tiling_params_layer_61, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[49].compute_node,
+                          l2_61, tiling_params_layer_62, 0, 0);
+location<dma>(l2_62.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_62.out[0], l2l3_62_spill.in[0]);
+read_access(l2_62.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 40, 30, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_62_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 30, 23}, .tiling_dimension = {8, 40, 30, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_62.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_62.out[1], l2l3_62_spill.in[1]);
+read_access(l2_62.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 40, 30, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_62_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 30, 23}, .tiling_dimension = {8, 40, 30, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_59_for_layer_63_port0.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_59_spill.out[0], L2_IFM_Buffer_from_layer_59_for_layer_63_port0.in[0]);
+read_access(l2l3_59_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 30, 23}, .tiling_dimension = {8, 40, 30, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 30, 23}, .tiling_dimension = {8, 40, 30, 5}, .offset = {0, 0, 0, 12}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_59_for_layer_63_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 30, 12}, .tiling_dimension = {8, 40, 30, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 30, 11}, .tiling_dimension = {8, 40, 30, 5}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1})
+};
+location<dma>(L2_IFM_Buffer_from_layer_59_for_layer_63_port0.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_59_spill.out[1], L2_IFM_Buffer_from_layer_59_for_layer_63_port0.in[1]);
+read_access(l2l3_59_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 30, 23}, .tiling_dimension = {8, 40, 30, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 30, 23}, .tiling_dimension = {8, 40, 30, 6}, .offset = {0, 0, 0, 17}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_59_for_layer_63_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 30, 12}, .tiling_dimension = {8, 40, 30, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 30, 11}, .tiling_dimension = {8, 40, 30, 6}, .offset = {0, 0, 0, 5}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1})
+};
+location<dma>(L2_IFM_Buffer_from_layer_62_for_layer_63_port1.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_62_spill.out[0], L2_IFM_Buffer_from_layer_62_for_layer_63_port1.in[0]);
+read_access(l2l3_62_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 30, 23}, .tiling_dimension = {8, 40, 30, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 30, 23}, .tiling_dimension = {8, 40, 30, 5}, .offset = {0, 0, 0, 12}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_62_for_layer_63_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 30, 12}, .tiling_dimension = {8, 40, 30, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 30, 11}, .tiling_dimension = {8, 40, 30, 5}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1})
+};
+location<dma>(L2_IFM_Buffer_from_layer_62_for_layer_63_port1.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_62_spill.out[1], L2_IFM_Buffer_from_layer_62_for_layer_63_port1.in[1]);
+read_access(l2l3_62_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 30, 23}, .tiling_dimension = {8, 40, 30, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 30, 23}, .tiling_dimension = {8, 40, 30, 6}, .offset = {0, 0, 0, 17}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_62_for_layer_63_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 30, 12}, .tiling_dimension = {8, 40, 30, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 30, 11}, .tiling_dimension = {8, 40, 30, 6}, .offset = {0, 0, 0, 5}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[50].compute_node,
+                          L2_IFM_Buffer_from_layer_59_for_layer_63_port0, tiling_params_layer_63, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[50].compute_node,
+                          L2_IFM_Buffer_from_layer_62_for_layer_63_port1, tiling_params_layer_63_1, 0, 2);
+location<dma>(l2_63.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_63.out[0], l2l3_63_spill.in[0]);
+read_access(l2_63.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 32, 12}, .tiling_dimension = {8, 40, 30, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_63_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 30, 24}, .tiling_dimension = {8, 40, 30, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_63.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_63.out[1], l2l3_63_spill.in[1]);
+read_access(l2_63.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 32, 12}, .tiling_dimension = {8, 40, 30, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_63_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 30, 24}, .tiling_dimension = {8, 40, 30, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_64_for_layer_65_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_64_spill.out[0], L2_IFM_Buffer_from_layer_64_for_layer_65_port0.in[0]);
+read_access(l2l3_64_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 30, 23}, .tiling_dimension = {8, 40, 30, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_64_for_layer_65_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 30, 23}, .tiling_dimension = {8, 40, 30, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_64_for_layer_65_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_64_spill.out[1], L2_IFM_Buffer_from_layer_64_for_layer_65_port0.in[1]);
+read_access(l2l3_64_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 30, 23}, .tiling_dimension = {8, 40, 30, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_64_for_layer_65_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 30, 23}, .tiling_dimension = {8, 40, 30, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[51].compute_node,
+                          L2_IFM_Buffer_from_layer_64_for_layer_65_port0, tiling_params_layer_65, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[52].compute_node,
+                          l2_65, tiling_params_layer_66, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[53].compute_node,
+                          l2_66, tiling_params_layer_67, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[54].compute_node,
+                          l2_67, tiling_params_layer_68, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[55].compute_node,
+                          l2_65, tiling_params_layer_69, 4, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[55].compute_node,
+                          l2_68, tiling_params_layer_69_1, 0, 2);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[56].compute_node,
+                          l2_69, tiling_params_layer_70, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[57].compute_node,
+                          l2_70, tiling_params_layer_71, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[58].compute_node,
+                          l2_71, tiling_params_layer_72, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[59].compute_node,
+                          l2_72, tiling_params_layer_73, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[60].compute_node,
+                          l2_73, tiling_params_layer_74, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[61].compute_node,
+                          l2_71, tiling_params_layer_75, 4, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[61].compute_node,
+                          l2_74, tiling_params_layer_75_1, 0, 2);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[62].compute_node,
+                          l2_75, tiling_params_layer_76, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[63].compute_node,
+                          l2_76, tiling_params_layer_77, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[64].compute_node,
+                          l2_77, tiling_params_layer_78, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[65].compute_node,
+                          l2_78, tiling_params_layer_79, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[66].compute_node,
+                          l2_76, tiling_params_layer_80, 4, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[66].compute_node,
+                          l2_79, tiling_params_layer_80_1, 0, 2);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[67].compute_node,
+                          l2_80, tiling_params_layer_81, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[67].compute_node,
+                          l2_70, tiling_params_layer_81_1, 4, 2);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[68].compute_node,
+                          l2_81, tiling_params_layer_82, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[69].compute_node,
+                          l2_82, tiling_params_layer_83, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[70].compute_node,
+                          l2_83, tiling_params_layer_84, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[71].compute_node,
+                          l2_84, tiling_params_layer_85, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[72].compute_node,
+                          l2_82, tiling_params_layer_86, 4, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[72].compute_node,
+                          l2_85, tiling_params_layer_86_1, 0, 2);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[73].compute_node,
+                          l2_86, tiling_params_layer_87, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[74].compute_node,
+                          l2_87, tiling_params_layer_88, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[75].compute_node,
+                          l2_88, tiling_params_layer_89, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[76].compute_node,
+                          l2_89, tiling_params_layer_90, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[77].compute_node,
+                          l2_87, tiling_params_layer_91, 4, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[77].compute_node,
+                          l2_90, tiling_params_layer_91_1, 0, 2);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[78].compute_node,
+                          l2_91, tiling_params_layer_92, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[78].compute_node,
+                          l2_81, tiling_params_layer_92_1, 4, 2);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[79].compute_node,
+                          l2_92, tiling_params_layer_93, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[80].compute_node,
+                          l2_93, tiling_params_layer_94, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[81].compute_node,
+                          l2_94, tiling_params_layer_95, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[82].compute_node,
+                          l2_95, tiling_params_layer_96, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[83].compute_node,
+                          l2_93, tiling_params_layer_97, 4, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[83].compute_node,
+                          l2_96, tiling_params_layer_97_1, 0, 2);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[84].compute_node,
+                          l2_97, tiling_params_layer_98, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[85].compute_node,
+                          l2_98, tiling_params_layer_99, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[86].compute_node,
+                          l2_99, tiling_params_layer_100, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[87].compute_node,
+                          l2_100, tiling_params_layer_101, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[88].compute_node,
+                          l2_98, tiling_params_layer_102, 4, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[88].compute_node,
+                          l2_101, tiling_params_layer_102_1, 0, 2);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[89].compute_node,
+                          l2_102, tiling_params_layer_103, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[89].compute_node,
+                          l2_92, tiling_params_layer_103_1, 4, 2);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[90].compute_node,
+                          l2_103, tiling_params_layer_104, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[91].compute_node,
+                          l2_104, tiling_params_layer_105, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[92].compute_node,
+                          l2_105, tiling_params_layer_106, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[93].compute_node,
+                          l2_106, tiling_params_layer_107, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[94].compute_node,
+                          l2_104, tiling_params_layer_108, 4, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[94].compute_node,
+                          l2_107, tiling_params_layer_108_1, 0, 2);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[95].compute_node,
+                          l2_108, tiling_params_layer_109, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[96].compute_node,
+                          l2_109, tiling_params_layer_110, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[97].compute_node,
+                          l2_110, tiling_params_layer_111, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[98].compute_node,
+                          l2_111, tiling_params_layer_112, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[99].compute_node,
+                          l2_109, tiling_params_layer_113, 4, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[99].compute_node,
+                          l2_112, tiling_params_layer_113_1, 0, 2);
+location<dma>(l2_113.out[2]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_113.out[2], L3_OFM_Buffer_layer_TGSpilling_113113.in[0]);
+read_access(l2_113.out[2]) = {
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 60, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_113113.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 60, 12}, .tiling_dimension = {8, 20, 60, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_113.out[3]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_113.out[3], L3_OFM_Buffer_layer_TGSpilling_113113.in[1]);
+read_access(l2_113.out[3]) = {
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 60, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_113113.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 60, 12}, .tiling_dimension = {8, 20, 60, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_113.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_113.out[0], l2l3_113_spill.in[0]);
+read_access(l2_113.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 60, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_113_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 60, 12}, .tiling_dimension = {8, 20, 60, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_113.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_113.out[1], l2l3_113_spill.in[1]);
+read_access(l2_113.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 60, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_113_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 60, 12}, .tiling_dimension = {8, 20, 60, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_114_for_layer_115_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_114_spill.out[0], L2_IFM_Buffer_from_layer_114_for_layer_115_port0.in[0]);
+read_access(l2l3_114_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 240, 60, 1}, .tiling_dimension = {8, 240, 60, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_114_for_layer_115_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 240, 60, 1}, .tiling_dimension = {8, 240, 60, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_114_for_layer_115_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_114_spill.out[1], L2_IFM_Buffer_from_layer_114_for_layer_115_port0.in[1]);
+read_access(l2l3_114_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 240, 60, 1}, .tiling_dimension = {8, 240, 60, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_114_for_layer_115_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 240, 60, 1}, .tiling_dimension = {8, 240, 60, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[100].compute_node,
+                          L2_IFM_Buffer_from_layer_114_for_layer_115_port0, tiling_params_layer_115, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[101].compute_node,
+                          l2_115, tiling_params_layer_116, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[102].compute_node,
+                          l2_116, tiling_params_layer_117, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[103].compute_node,
+                          l2_117, tiling_params_layer_118, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[104].compute_node,
+                          l2_118, tiling_params_layer_119, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[105].compute_node,
+                          l2_119, tiling_params_layer_120, 0, 0);
+location<dma>(l2_120.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_120.out[0], l2l3_120_spill.in[0]);
+read_access(l2_120.out[0]) = {
+  tiling({.buffer_dimension = {8, 1, 64, 16}, .tiling_dimension = {8, 1, 60, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_120_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 1, 60, 1}, .tiling_dimension = {8, 1, 60, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_120.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_120.out[1], l2l3_120_spill.in[1]);
+read_access(l2_120.out[1]) = {
+  tiling({.buffer_dimension = {8, 1, 64, 16}, .tiling_dimension = {8, 1, 60, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_120_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 1, 60, 1}, .tiling_dimension = {8, 1, 60, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_121_for_layer_122_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_121_spill.out[0], L2_IFM_Buffer_from_layer_121_for_layer_122_port0.in[0]);
+read_access(l2l3_121_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 60, 12}, .tiling_dimension = {8, 20, 60, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_121_for_layer_122_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 60, 12}, .tiling_dimension = {8, 20, 60, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_121_for_layer_122_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_121_spill.out[1], L2_IFM_Buffer_from_layer_121_for_layer_122_port0.in[1]);
+read_access(l2l3_121_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 60, 12}, .tiling_dimension = {8, 20, 60, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_121_for_layer_122_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 60, 12}, .tiling_dimension = {8, 20, 60, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_113113.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L3_OFM_Buffer_layer_TGSpilling_113113.out[0], L2_OFM_Buffer_layer_TGSpilling_113113.in[0]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_113113.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 60, 12}, .tiling_dimension = {8, 20, 60, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_113113.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 60, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_113113.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L3_OFM_Buffer_layer_TGSpilling_113113.out[1], L2_OFM_Buffer_layer_TGSpilling_113113.in[1]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_113113.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 60, 12}, .tiling_dimension = {8, 20, 60, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_113113.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 60, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[106].compute_node,
+                          L2_IFM_Buffer_from_layer_121_for_layer_122_port0, tiling_params_layer_122, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[106].compute_node,
+                          L2_OFM_Buffer_layer_TGSpilling_113113, tiling_params_layer_122_1, 0, 2);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[107].compute_node,
+                          l2_122, tiling_params_layer_123, 0, 0);
+location<dma>(l2_123.out[4]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_123.out[4], L3_OFM_Buffer_layer_TGSpilling_123123.in[0]);
+read_access(l2_123.out[4]) = {
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 20, 14, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_123123.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 14, 12}, .tiling_dimension = {8, 20, 14, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_123.out[5]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_123.out[5], L3_OFM_Buffer_layer_TGSpilling_123123.in[1]);
+read_access(l2_123.out[5]) = {
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 20, 14, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_123123.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 14, 12}, .tiling_dimension = {8, 20, 14, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[108].compute_node,
+                          l2_123, tiling_params_layer_124, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[109].compute_node,
+                          l2_124, tiling_params_layer_125, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[110].compute_node,
+                          l2_125, tiling_params_layer_126, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[111].compute_node,
+                          l2_126, tiling_params_layer_127, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[112].compute_node,
+                          l2_124, tiling_params_layer_128, 4, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[112].compute_node,
+                          l2_127, tiling_params_layer_128_1, 0, 2);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[113].compute_node,
+                          l2_128, tiling_params_layer_129, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[114].compute_node,
+                          l2_129, tiling_params_layer_130, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[115].compute_node,
+                          l2_130, tiling_params_layer_131, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[116].compute_node,
+                          l2_131, tiling_params_layer_132, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[117].compute_node,
+                          l2_129, tiling_params_layer_133, 4, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[117].compute_node,
+                          l2_132, tiling_params_layer_133_1, 0, 2);
+location<dma>(l2_133.out[2]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_133.out[2], L3_OFM_Buffer_layer_TGSpilling_133133.in[0]);
+read_access(l2_133.out[2]) = {
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_133133.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_133.out[3]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_133.out[3], L3_OFM_Buffer_layer_TGSpilling_133133.in[1]);
+read_access(l2_133.out[3]) = {
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_133133.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_133.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_133.out[0], l2l3_133_spill.in[0]);
+read_access(l2_133.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_133_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_133.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_133.out[1], l2l3_133_spill.in[1]);
+read_access(l2_133.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_133_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_134_for_layer_135_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_134_spill.out[0], L2_IFM_Buffer_from_layer_134_for_layer_135_port0.in[0]);
+read_access(l2l3_134_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 240, 84, 1}, .tiling_dimension = {8, 240, 84, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_134_for_layer_135_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 240, 84, 1}, .tiling_dimension = {8, 240, 84, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_134_for_layer_135_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_134_spill.out[1], L2_IFM_Buffer_from_layer_134_for_layer_135_port0.in[1]);
+read_access(l2l3_134_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 240, 84, 1}, .tiling_dimension = {8, 240, 84, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_134_for_layer_135_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 240, 84, 1}, .tiling_dimension = {8, 240, 84, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[118].compute_node,
+                          L2_IFM_Buffer_from_layer_134_for_layer_135_port0, tiling_params_layer_135, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[119].compute_node,
+                          l2_135, tiling_params_layer_136, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[120].compute_node,
+                          l2_136, tiling_params_layer_137, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[121].compute_node,
+                          l2_137, tiling_params_layer_138, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[122].compute_node,
+                          l2_138, tiling_params_layer_139, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[123].compute_node,
+                          l2_139, tiling_params_layer_140, 0, 0);
+location<dma>(l2_140.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_140.out[0], l2l3_140_spill.in[0]);
+read_access(l2_140.out[0]) = {
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 84, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_140_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 1, 84, 1}, .tiling_dimension = {8, 1, 84, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_140.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_140.out[1], l2l3_140_spill.in[1]);
+read_access(l2_140.out[1]) = {
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 84, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_140_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 1, 84, 1}, .tiling_dimension = {8, 1, 84, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_141_for_layer_142_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_141_spill.out[0], L2_IFM_Buffer_from_layer_141_for_layer_142_port0.in[0]);
+read_access(l2l3_141_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_141_for_layer_142_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_141_for_layer_142_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_141_spill.out[1], L2_IFM_Buffer_from_layer_141_for_layer_142_port0.in[1]);
+read_access(l2l3_141_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_141_for_layer_142_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_133133.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L3_OFM_Buffer_layer_TGSpilling_133133.out[0], L2_OFM_Buffer_layer_TGSpilling_133133.in[0]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_133133.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_133133.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_133133.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L3_OFM_Buffer_layer_TGSpilling_133133.out[1], L2_OFM_Buffer_layer_TGSpilling_133133.in[1]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_133133.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_133133.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[124].compute_node,
+                          L2_IFM_Buffer_from_layer_141_for_layer_142_port0, tiling_params_layer_142, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[124].compute_node,
+                          L2_OFM_Buffer_layer_TGSpilling_133133, tiling_params_layer_142_1, 0, 2);
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_123123.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L3_OFM_Buffer_layer_TGSpilling_123123.out[0], L2_OFM_Buffer_layer_TGSpilling_123123.in[0]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_123123.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 14, 12}, .tiling_dimension = {8, 20, 14, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_123123.in[0]) = {
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 20, 14, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_123123.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L3_OFM_Buffer_layer_TGSpilling_123123.out[1], L2_OFM_Buffer_layer_TGSpilling_123123.in[1]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_123123.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 14, 12}, .tiling_dimension = {8, 20, 14, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_123123.in[1]) = {
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 20, 14, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[125].compute_node,
+                          l2_142, tiling_params_layer_143, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[125].compute_node,
+                          L2_OFM_Buffer_layer_TGSpilling_123123, tiling_params_layer_143_1, 0, 2);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[126].compute_node,
+                          l2_143, tiling_params_layer_144, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[127].compute_node,
+                          l2_144, tiling_params_layer_145, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[128].compute_node,
+                          l2_145, tiling_params_layer_146, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[129].compute_node,
+                          l2_146, tiling_params_layer_147, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[130].compute_node,
+                          l2_144, tiling_params_layer_148, 4, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[130].compute_node,
+                          l2_147, tiling_params_layer_148_1, 0, 2);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[131].compute_node,
+                          l2_148, tiling_params_layer_149, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[132].compute_node,
+                          l2_149, tiling_params_layer_150, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[133].compute_node,
+                          l2_150, tiling_params_layer_151, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[134].compute_node,
+                          l2_151, tiling_params_layer_152, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[135].compute_node,
+                          l2_149, tiling_params_layer_153, 4, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[135].compute_node,
+                          l2_152, tiling_params_layer_153_1, 0, 2);
+location<dma>(l2_153.out[2]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_153.out[2], L3_OFM_Buffer_layer_TGSpilling_153153.in[0]);
+read_access(l2_153.out[2]) = {
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_153153.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_153.out[3]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_153.out[3], L3_OFM_Buffer_layer_TGSpilling_153153.in[1]);
+read_access(l2_153.out[3]) = {
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_153153.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_153.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_153.out[0], l2l3_153_spill.in[0]);
+read_access(l2_153.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_153_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_153.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_153.out[1], l2l3_153_spill.in[1]);
+read_access(l2_153.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_153_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_154_for_layer_155_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_154_spill.out[0], L2_IFM_Buffer_from_layer_154_for_layer_155_port0.in[0]);
+read_access(l2l3_154_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 240, 84, 1}, .tiling_dimension = {8, 240, 84, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_154_for_layer_155_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 240, 84, 1}, .tiling_dimension = {8, 240, 84, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_154_for_layer_155_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_154_spill.out[1], L2_IFM_Buffer_from_layer_154_for_layer_155_port0.in[1]);
+read_access(l2l3_154_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 240, 84, 1}, .tiling_dimension = {8, 240, 84, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_154_for_layer_155_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 240, 84, 1}, .tiling_dimension = {8, 240, 84, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[136].compute_node,
+                          L2_IFM_Buffer_from_layer_154_for_layer_155_port0, tiling_params_layer_155, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[137].compute_node,
+                          l2_155, tiling_params_layer_156, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[138].compute_node,
+                          l2_156, tiling_params_layer_157, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[139].compute_node,
+                          l2_157, tiling_params_layer_158, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[140].compute_node,
+                          l2_158, tiling_params_layer_159, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[141].compute_node,
+                          l2_159, tiling_params_layer_160, 0, 0);
+location<dma>(l2_160.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_160.out[0], l2l3_160_spill.in[0]);
+read_access(l2_160.out[0]) = {
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 84, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_160_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 1, 84, 1}, .tiling_dimension = {8, 1, 84, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_160.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_160.out[1], l2l3_160_spill.in[1]);
+read_access(l2_160.out[1]) = {
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 84, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_160_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 1, 84, 1}, .tiling_dimension = {8, 1, 84, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_161_for_layer_162_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_161_spill.out[0], L2_IFM_Buffer_from_layer_161_for_layer_162_port0.in[0]);
+read_access(l2l3_161_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_161_for_layer_162_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_161_for_layer_162_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_161_spill.out[1], L2_IFM_Buffer_from_layer_161_for_layer_162_port0.in[1]);
+read_access(l2l3_161_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_161_for_layer_162_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_153153.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L3_OFM_Buffer_layer_TGSpilling_153153.out[0], L2_OFM_Buffer_layer_TGSpilling_153153.in[0]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_153153.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_153153.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_153153.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L3_OFM_Buffer_layer_TGSpilling_153153.out[1], L2_OFM_Buffer_layer_TGSpilling_153153.in[1]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_153153.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_153153.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 84, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[142].compute_node,
+                          L2_IFM_Buffer_from_layer_161_for_layer_162_port0, tiling_params_layer_162, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[142].compute_node,
+                          L2_OFM_Buffer_layer_TGSpilling_153153, tiling_params_layer_162_1, 0, 2);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[143].compute_node,
+                          l2_162, tiling_params_layer_163, 0, 0);
+location<dma>(l2_163.out[4]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_163.out[4], L3_OFM_Buffer_layer_TGSpilling_163163.in[0]);
+read_access(l2_163.out[4]) = {
+  tiling({.buffer_dimension = {8, 32, 20, 12}, .tiling_dimension = {8, 20, 20, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_163163.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 20, 12}, .tiling_dimension = {8, 20, 20, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_163.out[5]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_163.out[5], L3_OFM_Buffer_layer_TGSpilling_163163.in[1]);
+read_access(l2_163.out[5]) = {
+  tiling({.buffer_dimension = {8, 32, 20, 12}, .tiling_dimension = {8, 20, 20, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_163163.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 20, 12}, .tiling_dimension = {8, 20, 20, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[144].compute_node,
+                          l2_163, tiling_params_layer_164, 0, 0);
+location<dma>(l2_164.out[4]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2_164.out[4], l2l3_164_spill.in[0]);
+read_access(l2_164.out[4]) = {
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_164_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_164.out[5]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2_164.out[5], l2l3_164_spill.in[1]);
+read_access(l2_164.out[5]) = {
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_164_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[145].compute_node,
+                          l2_164, tiling_params_layer_165, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[146].compute_node,
+                          l2_165, tiling_params_layer_166, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[147].compute_node,
+                          l2_166, tiling_params_layer_167, 0, 0);
+location<dma>(l2_167.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_167.out[0], l2l3_167_spill.in[0]);
+read_access(l2_167.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_167_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_167.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_167.out[1], l2l3_167_spill.in[1]);
+read_access(l2_167.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_167_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_164_for_layer_168_port0.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_164_spill.out[0], L2_IFM_Buffer_from_layer_164_for_layer_168_port0.in[0]);
+read_access(l2l3_164_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_164_for_layer_168_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_164_for_layer_168_port0.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_164_spill.out[1], L2_IFM_Buffer_from_layer_164_for_layer_168_port0.in[1]);
+read_access(l2l3_164_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_164_for_layer_168_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_167_for_layer_168_port1.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_167_spill.out[0], L2_IFM_Buffer_from_layer_167_for_layer_168_port1.in[0]);
+read_access(l2l3_167_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_167_for_layer_168_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_167_for_layer_168_port1.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_167_spill.out[1], L2_IFM_Buffer_from_layer_167_for_layer_168_port1.in[1]);
+read_access(l2l3_167_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_167_for_layer_168_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[148].compute_node,
+                          L2_IFM_Buffer_from_layer_164_for_layer_168_port0, tiling_params_layer_168, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[148].compute_node,
+                          L2_IFM_Buffer_from_layer_167_for_layer_168_port1, tiling_params_layer_168_1, 0, 2);
+location<dma>(l2_168.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_168.out[0], l2l3_168_spill.in[0]);
+read_access(l2_168.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_168_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_168.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_168.out[1], l2l3_168_spill.in[1]);
+read_access(l2_168.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_168_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_168_for_layer_169_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_168_spill.out[0], L2_IFM_Buffer_from_layer_168_for_layer_169_port0.in[0]);
+read_access(l2l3_168_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_168_for_layer_169_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_168_for_layer_169_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_168_spill.out[1], L2_IFM_Buffer_from_layer_168_for_layer_169_port0.in[1]);
+read_access(l2l3_168_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_168_for_layer_169_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[149].compute_node,
+                          L2_IFM_Buffer_from_layer_168_for_layer_169_port0, tiling_params_layer_169, 0, 0);
+location<dma>(l2_169.out[4]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2_169.out[4], l2l3_169_spill.in[0]);
+read_access(l2_169.out[4]) = {
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_169_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_169.out[5]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2_169.out[5], l2l3_169_spill.in[1]);
+read_access(l2_169.out[5]) = {
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_169_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[150].compute_node,
+                          l2_169, tiling_params_layer_170, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[151].compute_node,
+                          l2_170, tiling_params_layer_171, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[152].compute_node,
+                          l2_171, tiling_params_layer_172, 0, 0);
+location<dma>(l2_172.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_172.out[0], l2l3_172_spill.in[0]);
+read_access(l2_172.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_172_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_172.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_172.out[1], l2l3_172_spill.in[1]);
+read_access(l2_172.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_172_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_169_for_layer_173_port0.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_169_spill.out[0], L2_IFM_Buffer_from_layer_169_for_layer_173_port0.in[0]);
+read_access(l2l3_169_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_169_for_layer_173_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_169_for_layer_173_port0.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_169_spill.out[1], L2_IFM_Buffer_from_layer_169_for_layer_173_port0.in[1]);
+read_access(l2l3_169_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_169_for_layer_173_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_172_for_layer_173_port1.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_172_spill.out[0], L2_IFM_Buffer_from_layer_172_for_layer_173_port1.in[0]);
+read_access(l2l3_172_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_172_for_layer_173_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_172_for_layer_173_port1.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_172_spill.out[1], L2_IFM_Buffer_from_layer_172_for_layer_173_port1.in[1]);
+read_access(l2l3_172_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_172_for_layer_173_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[153].compute_node,
+                          L2_IFM_Buffer_from_layer_169_for_layer_173_port0, tiling_params_layer_173, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[153].compute_node,
+                          L2_IFM_Buffer_from_layer_172_for_layer_173_port1, tiling_params_layer_173_1, 0, 2);
+location<dma>(l2_173.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_173.out[0], l2l3_173_spill.in[0]);
+read_access(l2_173.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_173_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_173.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_173.out[1], l2l3_173_spill.in[1]);
+read_access(l2_173.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_173_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_174_for_layer_175_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_174_spill.out[0], L2_IFM_Buffer_from_layer_174_for_layer_175_port0.in[0]);
+read_access(l2l3_174_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 240, 120, 1}, .tiling_dimension = {8, 240, 120, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_174_for_layer_175_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 240, 120, 1}, .tiling_dimension = {8, 240, 120, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_174_for_layer_175_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_174_spill.out[1], L2_IFM_Buffer_from_layer_174_for_layer_175_port0.in[1]);
+read_access(l2l3_174_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 240, 120, 1}, .tiling_dimension = {8, 240, 120, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_174_for_layer_175_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 240, 120, 1}, .tiling_dimension = {8, 240, 120, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[154].compute_node,
+                          L2_IFM_Buffer_from_layer_174_for_layer_175_port0, tiling_params_layer_175, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[155].compute_node,
+                          l2_175, tiling_params_layer_176, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[156].compute_node,
+                          l2_176, tiling_params_layer_177, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[157].compute_node,
+                          l2_177, tiling_params_layer_178, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[158].compute_node,
+                          l2_178, tiling_params_layer_179, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[159].compute_node,
+                          l2_179, tiling_params_layer_180, 0, 0);
+location<dma>(l2_180.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_180.out[0], l2l3_180_spill.in[0]);
+read_access(l2_180.out[0]) = {
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 120, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_180_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 1, 120, 1}, .tiling_dimension = {8, 1, 120, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_180.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_180.out[1], l2l3_180_spill.in[1]);
+read_access(l2_180.out[1]) = {
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 120, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_180_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 1, 120, 1}, .tiling_dimension = {8, 1, 120, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_173_for_layer_182_port1.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_173_spill.out[1], L2_IFM_Buffer_from_layer_173_for_layer_182_port1.in[0]);
+read_access(l2l3_173_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_173_for_layer_182_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_173_for_layer_182_port1.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_173_spill.out[2], L2_IFM_Buffer_from_layer_173_for_layer_182_port1.in[1]);
+read_access(l2l3_173_spill.out[2]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_173_for_layer_182_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_181_for_layer_182_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_181_spill.out[0], L2_IFM_Buffer_from_layer_181_for_layer_182_port0.in[0]);
+read_access(l2l3_181_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_181_for_layer_182_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_181_for_layer_182_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_181_spill.out[1], L2_IFM_Buffer_from_layer_181_for_layer_182_port0.in[1]);
+read_access(l2l3_181_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_181_for_layer_182_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[160].compute_node,
+                          L2_IFM_Buffer_from_layer_181_for_layer_182_port0, tiling_params_layer_182, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[160].compute_node,
+                          L2_IFM_Buffer_from_layer_173_for_layer_182_port1, tiling_params_layer_182_1, 0, 2);
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_163163.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L3_OFM_Buffer_layer_TGSpilling_163163.out[0], L2_OFM_Buffer_layer_TGSpilling_163163.in[0]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_163163.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 20, 12}, .tiling_dimension = {8, 20, 20, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_163163.in[0]) = {
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 20, 20, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_163163.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L3_OFM_Buffer_layer_TGSpilling_163163.out[1], L2_OFM_Buffer_layer_TGSpilling_163163.in[1]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_163163.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 20, 12}, .tiling_dimension = {8, 20, 20, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_163163.in[1]) = {
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 20, 20, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[161].compute_node,
+                          l2_182, tiling_params_layer_183, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[161].compute_node,
+                          L2_OFM_Buffer_layer_TGSpilling_163163, tiling_params_layer_183_1, 0, 2);
+location<dma>(l2_183.out[4]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_183.out[4], L3_OFM_Buffer_layer_TGSpilling_183183.in[0]);
+read_access(l2_183.out[4]) = {
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 20, 20, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_183183.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 20, 12}, .tiling_dimension = {8, 20, 20, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_183.out[5]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_183.out[5], L3_OFM_Buffer_layer_TGSpilling_183183.in[1]);
+read_access(l2_183.out[5]) = {
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 20, 20, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_183183.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 20, 12}, .tiling_dimension = {8, 20, 20, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[162].compute_node,
+                          l2_183, tiling_params_layer_184, 0, 0);
+location<dma>(l2_184.out[4]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2_184.out[4], l2l3_184_spill.in[0]);
+read_access(l2_184.out[4]) = {
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_184_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_184.out[5]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2_184.out[5], l2l3_184_spill.in[1]);
+read_access(l2_184.out[5]) = {
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_184_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[163].compute_node,
+                          l2_184, tiling_params_layer_185, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[164].compute_node,
+                          l2_185, tiling_params_layer_186, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[165].compute_node,
+                          l2_186, tiling_params_layer_187, 0, 0);
+location<dma>(l2_187.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_187.out[0], l2l3_187_spill.in[0]);
+read_access(l2_187.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_187_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_187.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_187.out[1], l2l3_187_spill.in[1]);
+read_access(l2_187.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_187_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_184_for_layer_188_port0.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_184_spill.out[0], L2_IFM_Buffer_from_layer_184_for_layer_188_port0.in[0]);
+read_access(l2l3_184_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_184_for_layer_188_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_184_for_layer_188_port0.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_184_spill.out[1], L2_IFM_Buffer_from_layer_184_for_layer_188_port0.in[1]);
+read_access(l2l3_184_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_184_for_layer_188_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_187_for_layer_188_port1.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_187_spill.out[0], L2_IFM_Buffer_from_layer_187_for_layer_188_port1.in[0]);
+read_access(l2l3_187_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_187_for_layer_188_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_187_for_layer_188_port1.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_187_spill.out[1], L2_IFM_Buffer_from_layer_187_for_layer_188_port1.in[1]);
+read_access(l2l3_187_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_187_for_layer_188_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[166].compute_node,
+                          L2_IFM_Buffer_from_layer_184_for_layer_188_port0, tiling_params_layer_188, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[166].compute_node,
+                          L2_IFM_Buffer_from_layer_187_for_layer_188_port1, tiling_params_layer_188_1, 0, 2);
+location<dma>(l2_188.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_188.out[0], l2l3_188_spill.in[0]);
+read_access(l2_188.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_188_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_188.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_188.out[1], l2l3_188_spill.in[1]);
+read_access(l2_188.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_188_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_188_for_layer_189_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_188_spill.out[0], L2_IFM_Buffer_from_layer_188_for_layer_189_port0.in[0]);
+read_access(l2l3_188_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_188_for_layer_189_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_188_for_layer_189_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_188_spill.out[1], L2_IFM_Buffer_from_layer_188_for_layer_189_port0.in[1]);
+read_access(l2l3_188_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_188_for_layer_189_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[167].compute_node,
+                          L2_IFM_Buffer_from_layer_188_for_layer_189_port0, tiling_params_layer_189, 0, 0);
+location<dma>(l2_189.out[4]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2_189.out[4], l2l3_189_spill.in[0]);
+read_access(l2_189.out[4]) = {
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_189_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_189.out[5]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2_189.out[5], l2l3_189_spill.in[1]);
+read_access(l2_189.out[5]) = {
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_189_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[168].compute_node,
+                          l2_189, tiling_params_layer_190, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[169].compute_node,
+                          l2_190, tiling_params_layer_191, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[170].compute_node,
+                          l2_191, tiling_params_layer_192, 0, 0);
+location<dma>(l2_192.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_192.out[0], l2l3_192_spill.in[0]);
+read_access(l2_192.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_192_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_192.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_192.out[1], l2l3_192_spill.in[1]);
+read_access(l2_192.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_192_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_189_for_layer_193_port0.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_189_spill.out[0], L2_IFM_Buffer_from_layer_189_for_layer_193_port0.in[0]);
+read_access(l2l3_189_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_189_for_layer_193_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_189_for_layer_193_port0.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_189_spill.out[1], L2_IFM_Buffer_from_layer_189_for_layer_193_port0.in[1]);
+read_access(l2l3_189_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_189_for_layer_193_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_192_for_layer_193_port1.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_192_spill.out[0], L2_IFM_Buffer_from_layer_192_for_layer_193_port1.in[0]);
+read_access(l2l3_192_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_192_for_layer_193_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_192_for_layer_193_port1.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_192_spill.out[1], L2_IFM_Buffer_from_layer_192_for_layer_193_port1.in[1]);
+read_access(l2l3_192_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_192_for_layer_193_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[171].compute_node,
+                          L2_IFM_Buffer_from_layer_189_for_layer_193_port0, tiling_params_layer_193, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[171].compute_node,
+                          L2_IFM_Buffer_from_layer_192_for_layer_193_port1, tiling_params_layer_193_1, 0, 2);
+location<dma>(l2_193.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_193.out[0], l2l3_193_spill.in[0]);
+read_access(l2_193.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_193_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_193.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_193.out[1], l2l3_193_spill.in[1]);
+read_access(l2_193.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_193_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_194_for_layer_195_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_194_spill.out[0], L2_IFM_Buffer_from_layer_194_for_layer_195_port0.in[0]);
+read_access(l2l3_194_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 240, 120, 1}, .tiling_dimension = {8, 240, 120, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_194_for_layer_195_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 240, 120, 1}, .tiling_dimension = {8, 240, 120, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_194_for_layer_195_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_194_spill.out[1], L2_IFM_Buffer_from_layer_194_for_layer_195_port0.in[1]);
+read_access(l2l3_194_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 240, 120, 1}, .tiling_dimension = {8, 240, 120, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_194_for_layer_195_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 240, 120, 1}, .tiling_dimension = {8, 240, 120, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[172].compute_node,
+                          L2_IFM_Buffer_from_layer_194_for_layer_195_port0, tiling_params_layer_195, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[173].compute_node,
+                          l2_195, tiling_params_layer_196, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[174].compute_node,
+                          l2_196, tiling_params_layer_197, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[175].compute_node,
+                          l2_197, tiling_params_layer_198, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[176].compute_node,
+                          l2_198, tiling_params_layer_199, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[177].compute_node,
+                          l2_199, tiling_params_layer_200, 0, 0);
+location<dma>(l2_200.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_200.out[0], l2l3_200_spill.in[0]);
+read_access(l2_200.out[0]) = {
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 120, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_200_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 1, 120, 1}, .tiling_dimension = {8, 1, 120, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_200.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_200.out[1], l2l3_200_spill.in[1]);
+read_access(l2_200.out[1]) = {
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 120, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_200_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 1, 120, 1}, .tiling_dimension = {8, 1, 120, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_193_for_layer_202_port1.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_193_spill.out[1], L2_IFM_Buffer_from_layer_193_for_layer_202_port1.in[0]);
+read_access(l2l3_193_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_193_for_layer_202_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_193_for_layer_202_port1.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_193_spill.out[2], L2_IFM_Buffer_from_layer_193_for_layer_202_port1.in[1]);
+read_access(l2l3_193_spill.out[2]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_193_for_layer_202_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_201_for_layer_202_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_201_spill.out[0], L2_IFM_Buffer_from_layer_201_for_layer_202_port0.in[0]);
+read_access(l2l3_201_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_201_for_layer_202_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_201_for_layer_202_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_201_spill.out[1], L2_IFM_Buffer_from_layer_201_for_layer_202_port0.in[1]);
+read_access(l2l3_201_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_201_for_layer_202_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[178].compute_node,
+                          L2_IFM_Buffer_from_layer_201_for_layer_202_port0, tiling_params_layer_202, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[178].compute_node,
+                          L2_IFM_Buffer_from_layer_193_for_layer_202_port1, tiling_params_layer_202_1, 0, 2);
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_183183.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L3_OFM_Buffer_layer_TGSpilling_183183.out[0], L2_OFM_Buffer_layer_TGSpilling_183183.in[0]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_183183.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 20, 12}, .tiling_dimension = {8, 20, 20, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_183183.in[0]) = {
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 20, 20, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_183183.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L3_OFM_Buffer_layer_TGSpilling_183183.out[1], L2_OFM_Buffer_layer_TGSpilling_183183.in[1]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_183183.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 20, 12}, .tiling_dimension = {8, 20, 20, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_183183.in[1]) = {
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 20, 20, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[179].compute_node,
+                          l2_202, tiling_params_layer_203, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[179].compute_node,
+                          L2_OFM_Buffer_layer_TGSpilling_183183, tiling_params_layer_203_1, 0, 2);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[180].compute_node,
+                          l2_203, tiling_params_layer_204, 0, 0);
+location<dma>(l2_204.out[4]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2_204.out[4], l2l3_204_spill.in[0]);
+read_access(l2_204.out[4]) = {
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_204_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_204.out[5]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2_204.out[5], l2l3_204_spill.in[1]);
+read_access(l2_204.out[5]) = {
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_204_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[181].compute_node,
+                          l2_204, tiling_params_layer_205, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[182].compute_node,
+                          l2_205, tiling_params_layer_206, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[183].compute_node,
+                          l2_206, tiling_params_layer_207, 0, 0);
+location<dma>(l2_207.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_207.out[0], l2l3_207_spill.in[0]);
+read_access(l2_207.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_207_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_207.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_207.out[1], l2l3_207_spill.in[1]);
+read_access(l2_207.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_207_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_204_for_layer_208_port0.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_204_spill.out[0], L2_IFM_Buffer_from_layer_204_for_layer_208_port0.in[0]);
+read_access(l2l3_204_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_204_for_layer_208_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_204_for_layer_208_port0.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_204_spill.out[1], L2_IFM_Buffer_from_layer_204_for_layer_208_port0.in[1]);
+read_access(l2l3_204_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_204_for_layer_208_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_207_for_layer_208_port1.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_207_spill.out[0], L2_IFM_Buffer_from_layer_207_for_layer_208_port1.in[0]);
+read_access(l2l3_207_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_207_for_layer_208_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_207_for_layer_208_port1.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_207_spill.out[1], L2_IFM_Buffer_from_layer_207_for_layer_208_port1.in[1]);
+read_access(l2l3_207_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_207_for_layer_208_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[184].compute_node,
+                          L2_IFM_Buffer_from_layer_204_for_layer_208_port0, tiling_params_layer_208, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[184].compute_node,
+                          L2_IFM_Buffer_from_layer_207_for_layer_208_port1, tiling_params_layer_208_1, 0, 2);
+location<dma>(l2_208.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_208.out[0], l2l3_208_spill.in[0]);
+read_access(l2_208.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_208_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_208.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_208.out[1], l2l3_208_spill.in[1]);
+read_access(l2_208.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_208_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 6, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_209_for_layer_210_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_209_spill.out[0], L2_IFM_Buffer_from_layer_209_for_layer_210_port0.in[0]);
+read_access(l2l3_209_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 240, 120, 1}, .tiling_dimension = {8, 240, 120, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_209_for_layer_210_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 240, 120, 1}, .tiling_dimension = {8, 240, 120, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_209_for_layer_210_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_209_spill.out[1], L2_IFM_Buffer_from_layer_209_for_layer_210_port0.in[1]);
+read_access(l2l3_209_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 240, 120, 1}, .tiling_dimension = {8, 240, 120, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_209_for_layer_210_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 240, 120, 1}, .tiling_dimension = {8, 240, 120, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[185].compute_node,
+                          L2_IFM_Buffer_from_layer_209_for_layer_210_port0, tiling_params_layer_210, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[186].compute_node,
+                          l2_210, tiling_params_layer_211, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[187].compute_node,
+                          l2_211, tiling_params_layer_212, 0, 0);
+location<dma>(l2_212.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_212.out[0], l2l3_212_spill.in[0]);
+read_access(l2_212.out[0]) = {
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 16, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_212_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 1, 16, 1}, .tiling_dimension = {8, 1, 16, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_212.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_212.out[1], l2l3_212_spill.in[1]);
+read_access(l2_212.out[1]) = {
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 16, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_212_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 1, 16, 1}, .tiling_dimension = {8, 1, 16, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_208_for_layer_214_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_208_spill.out[1], L2_IFM_Buffer_from_layer_208_for_layer_214_port0.in[0]);
+read_access(l2l3_208_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_208_for_layer_214_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_208_for_layer_214_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_208_spill.out[2], L2_IFM_Buffer_from_layer_208_for_layer_214_port0.in[1]);
+read_access(l2l3_208_spill.out[2]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_208_for_layer_214_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 120, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_213_for_layer_214_port1.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_213_spill.out[0], L2_IFM_Buffer_from_layer_213_for_layer_214_port1.in[0]);
+read_access(l2l3_213_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 16, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_213_for_layer_214_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 20, 16, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_213_for_layer_214_port1.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_213_spill.out[1], L2_IFM_Buffer_from_layer_213_for_layer_214_port1.in[1]);
+read_access(l2l3_213_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 16, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_213_for_layer_214_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 20, 16, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[188].compute_node,
+                          L2_IFM_Buffer_from_layer_208_for_layer_214_port0, tiling_params_layer_214, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[188].compute_node,
+                          L2_IFM_Buffer_from_layer_213_for_layer_214_port1, tiling_params_layer_214_1, 0, 2);
+location<dma>(l2_214.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_214.out[0], l2l3_214_spill.in[0]);
+read_access(l2_214.out[0]) = {
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 20, 16, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_214_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 16, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_214.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_214.out[1], l2l3_214_spill.in[1]);
+read_access(l2_214.out[1]) = {
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 20, 16, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_214_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 16, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_216_for_layer_217_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_216_spill.out[0], L2_IFM_Buffer_from_layer_216_for_layer_217_port0.in[0]);
+read_access(l2l3_216_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_216_for_layer_217_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_216_for_layer_217_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_216_spill.out[1], L2_IFM_Buffer_from_layer_216_for_layer_217_port0.in[1]);
+read_access(l2l3_216_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_216_for_layer_217_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_for_input4_0_port1.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(ifm_ddr_4.out[0], L2_IFM_Buffer_for_input4_0_port1.in[0]);
+read_access(ifm_ddr_4.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_for_input4_0_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_for_input4_0_port1.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(ifm_ddr_4.out[1], L2_IFM_Buffer_for_input4_0_port1.in[1]);
+read_access(ifm_ddr_4.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_for_input4_0_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_216_for_layer_217_port0.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L2_IFM_Buffer_from_layer_216_for_layer_217_port0.out[0], spill_L3_Concat_Buffer_layer_217.in[0]);
+read_access(L2_IFM_Buffer_from_layer_216_for_layer_217_port0.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_217.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_216_for_layer_217_port0.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L2_IFM_Buffer_from_layer_216_for_layer_217_port0.out[1], spill_L3_Concat_Buffer_layer_217.in[1]);
+read_access(L2_IFM_Buffer_from_layer_216_for_layer_217_port0.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_217.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_for_input4_0_port1.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L2_IFM_Buffer_for_input4_0_port1.out[0], spill_L3_Concat_Buffer_layer_217.in[2]);
+read_access(L2_IFM_Buffer_for_input4_0_port1.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_217.in[2]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 8, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_for_input4_0_port1.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L2_IFM_Buffer_for_input4_0_port1.out[1], spill_L3_Concat_Buffer_layer_217.in[3]);
+read_access(L2_IFM_Buffer_for_input4_0_port1.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_217.in[3]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 8, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_217_for_layer_218_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(spill_L3_Concat_Buffer_layer_217.out[0], L2_IFM_Buffer_from_layer_217_for_layer_218_port0.in[0]);
+read_access(spill_L3_Concat_Buffer_layer_217.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 16, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_217_for_layer_218_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 16, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_217_for_layer_218_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(spill_L3_Concat_Buffer_layer_217.out[1], L2_IFM_Buffer_from_layer_217_for_layer_218_port0.in[1]);
+read_access(spill_L3_Concat_Buffer_layer_217.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 16, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_217_for_layer_218_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 16, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[189].compute_node,
+                          L2_IFM_Buffer_from_layer_217_for_layer_218_port0, tiling_params_layer_218, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[190].compute_node,
+                          l2_218, tiling_params_layer_219, 0, 0);
+location<dma>(l2_219.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_219.out[0], l2l3_219_spill.in[0]);
+read_access(l2_219.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 16, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_219_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 16, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_219.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_219.out[1], l2l3_219_spill.in[1]);
+read_access(l2_219.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 16, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_219_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 16, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_CONST_IFM_Buffer_for_input3_0_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(const_ifm_ddr_3.out[0], L2_CONST_IFM_Buffer_for_input3_0_port0.in[0]);
+read_access(const_ifm_ddr_3.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_CONST_IFM_Buffer_for_input3_0_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_CONST_IFM_Buffer_for_input3_0_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(const_ifm_ddr_3.out[1], L2_CONST_IFM_Buffer_for_input3_0_port0.in[1]);
+read_access(const_ifm_ddr_3.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_CONST_IFM_Buffer_for_input3_0_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_220_for_layer_221_port1.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_220_spill.out[0], L2_IFM_Buffer_from_layer_220_for_layer_221_port1.in[0]);
+read_access(l2l3_220_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_220_for_layer_221_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_220_for_layer_221_port1.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_220_spill.out[1], L2_IFM_Buffer_from_layer_220_for_layer_221_port1.in[1]);
+read_access(l2l3_220_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_220_for_layer_221_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[191].compute_node,
+                          L2_CONST_IFM_Buffer_for_input3_0_port0, tiling_params_layer_221, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[191].compute_node,
+                          L2_IFM_Buffer_from_layer_220_for_layer_221_port1, tiling_params_layer_221_1, 0, 2);
+location<dma>(L2_IFM_Buffer_for_input4_1_port1.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(ifm_ddr_4.out[2], L2_IFM_Buffer_for_input4_1_port1.in[0]);
+read_access(ifm_ddr_4.out[2]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_for_input4_1_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_for_input4_1_port1.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(ifm_ddr_4.out[3], L2_IFM_Buffer_for_input4_1_port1.in[1]);
+read_access(ifm_ddr_4.out[3]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_for_input4_1_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[192].compute_node,
+                          l2_221, tiling_params_layer_222, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[192].compute_node,
+                          L2_IFM_Buffer_for_input4_1_port1, tiling_params_layer_222_1, 0, 2);
+location<dma>(l2_222.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_222.out[0], L3_OFM_Buffer_layer_TGSpilling_222222.in[0]);
+read_access(l2_222.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_222222.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_222.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_222.out[1], L3_OFM_Buffer_layer_TGSpilling_222222.in[1]);
+read_access(l2_222.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_222222.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_for_input4_2_port1.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(ifm_ddr_4.out[4], L2_IFM_Buffer_for_input4_2_port1.in[0]);
+read_access(ifm_ddr_4.out[4]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_for_input4_2_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_for_input4_2_port1.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(ifm_ddr_4.out[5], L2_IFM_Buffer_for_input4_2_port1.in[1]);
+read_access(ifm_ddr_4.out[5]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_for_input4_2_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_223_for_layer_224_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_223_spill.out[0], L2_IFM_Buffer_from_layer_223_for_layer_224_port0.in[0]);
+read_access(l2l3_223_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_223_for_layer_224_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_223_for_layer_224_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_223_spill.out[1], L2_IFM_Buffer_from_layer_223_for_layer_224_port0.in[1]);
+read_access(l2l3_223_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_223_for_layer_224_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[193].compute_node,
+                          L2_IFM_Buffer_from_layer_223_for_layer_224_port0, tiling_params_layer_224, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[193].compute_node,
+                          L2_IFM_Buffer_for_input4_2_port1, tiling_params_layer_224_1, 0, 2);
+location<dma>(L2_IFM_Buffer_from_layer_216_for_layer_225_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_216_spill.out[2], L2_IFM_Buffer_from_layer_216_for_layer_225_port0.in[0]);
+read_access(l2l3_216_spill.out[2]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_216_for_layer_225_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_216_for_layer_225_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_216_spill.out[3], L2_IFM_Buffer_from_layer_216_for_layer_225_port0.in[1]);
+read_access(l2l3_216_spill.out[3]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_216_for_layer_225_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_216_for_layer_225_port0.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L2_IFM_Buffer_from_layer_216_for_layer_225_port0.out[0], spill_L3_Concat_Buffer_layer_225.in[0]);
+read_access(L2_IFM_Buffer_from_layer_216_for_layer_225_port0.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_225.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_216_for_layer_225_port0.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L2_IFM_Buffer_from_layer_216_for_layer_225_port0.out[1], spill_L3_Concat_Buffer_layer_225.in[1]);
+read_access(L2_IFM_Buffer_from_layer_216_for_layer_225_port0.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_225.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_224.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_224.out[0], spill_L3_Concat_Buffer_layer_225.in[2]);
+read_access(l2_224.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_225.in[2]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 8, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_224.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_224.out[1], spill_L3_Concat_Buffer_layer_225.in[3]);
+read_access(l2_224.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_225.in[3]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 8, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_225_for_layer_226_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(spill_L3_Concat_Buffer_layer_225.out[0], L2_IFM_Buffer_from_layer_225_for_layer_226_port0.in[0]);
+read_access(spill_L3_Concat_Buffer_layer_225.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 16, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_225_for_layer_226_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 16, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_225_for_layer_226_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(spill_L3_Concat_Buffer_layer_225.out[1], L2_IFM_Buffer_from_layer_225_for_layer_226_port0.in[1]);
+read_access(spill_L3_Concat_Buffer_layer_225.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 16, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_225_for_layer_226_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 16, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[194].compute_node,
+                          L2_IFM_Buffer_from_layer_225_for_layer_226_port0, tiling_params_layer_226, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[195].compute_node,
+                          l2_226, tiling_params_layer_227, 0, 0);
+location<dma>(L2_IFM_Buffer_from_layer_220_for_layer_228_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_220_spill.out[2], L2_IFM_Buffer_from_layer_220_for_layer_228_port0.in[0]);
+read_access(l2l3_220_spill.out[2]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_220_for_layer_228_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_220_for_layer_228_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_220_spill.out[3], L2_IFM_Buffer_from_layer_220_for_layer_228_port0.in[1]);
+read_access(l2l3_220_spill.out[3]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_220_for_layer_228_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[196].compute_node,
+                          L2_IFM_Buffer_from_layer_220_for_layer_228_port0, tiling_params_layer_228, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[196].compute_node,
+                          l2_227, tiling_params_layer_228_1, 0, 2);
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_222222.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L3_OFM_Buffer_layer_TGSpilling_222222.out[0], L2_OFM_Buffer_layer_TGSpilling_222222.in[0]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_222222.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_222222.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_222222.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L3_OFM_Buffer_layer_TGSpilling_222222.out[1], L2_OFM_Buffer_layer_TGSpilling_222222.in[1]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_222222.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_222222.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[197].compute_node,
+                          L2_OFM_Buffer_layer_TGSpilling_222222, tiling_params_layer_229, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[197].compute_node,
+                          l2_228, tiling_params_layer_229_1, 0, 2);
+location<dma>(l2_229.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_229.out[0], ofm_ddr_0_l2l3_229_spill.in[0]);
+read_access(l2_229.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(ofm_ddr_0_l2l3_229_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_229.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_229.out[1], ofm_ddr_0_l2l3_229_spill.in[1]);
+read_access(l2_229.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(ofm_ddr_0_l2l3_229_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_215_for_layer_230_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_215_spill.out[0], L2_IFM_Buffer_from_layer_215_for_layer_230_port0.in[0]);
+read_access(l2l3_215_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_215_for_layer_230_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_215_for_layer_230_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_215_spill.out[1], L2_IFM_Buffer_from_layer_215_for_layer_230_port0.in[1]);
+read_access(l2l3_215_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_215_for_layer_230_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_215_for_layer_230_port0.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L2_IFM_Buffer_from_layer_215_for_layer_230_port0.out[0], spill_L3_Concat_Buffer_layer_230.in[0]);
+read_access(L2_IFM_Buffer_from_layer_215_for_layer_230_port0.out[0]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_230.in[0]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_215_for_layer_230_port0.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L2_IFM_Buffer_from_layer_215_for_layer_230_port0.out[1], spill_L3_Concat_Buffer_layer_230.in[1]);
+read_access(L2_IFM_Buffer_from_layer_215_for_layer_230_port0.out[1]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_230.in[1]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_229.out[2]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_229.out[2], spill_L3_Concat_Buffer_layer_230.in[2]);
+read_access(l2_229.out[2]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_230.in[2]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 8, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_229.out[3]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_229.out[3], spill_L3_Concat_Buffer_layer_230.in[3]);
+read_access(l2_229.out[3]) = {
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_230.in[3]) = {
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 8, 6}, .offset = {0, 0, 8, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_232_for_layer_236_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_232_spill.out[0], L2_IFM_Buffer_from_layer_232_for_layer_236_port0.in[0]);
+read_access(l2l3_232_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 16, 23}, .tiling_dimension = {8, 40, 16, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_232_for_layer_236_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 16, 23}, .tiling_dimension = {8, 40, 16, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_232_for_layer_236_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_232_spill.out[1], L2_IFM_Buffer_from_layer_232_for_layer_236_port0.in[1]);
+read_access(l2l3_232_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 16, 23}, .tiling_dimension = {8, 40, 16, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_232_for_layer_236_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 16, 23}, .tiling_dimension = {8, 40, 16, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_5_for_layer_233_port0.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_5_spill.out[2], L2_IFM_Buffer_from_layer_5_for_layer_233_port0.in[0]);
+read_access(l2l3_5_spill.out[2]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 30}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 60, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_5_for_layer_233_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 60}, .tiling_dimension = {8, 320, 1, 30}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_5_for_layer_233_port0.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_5_spill.out[3], L2_IFM_Buffer_from_layer_5_for_layer_233_port0.in[1]);
+read_access(l2l3_5_spill.out[3]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 30}, .offset = {0, 0, 0, 30}, .tile_traversal = { {.dimension = 3, .stride = 60, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_5_for_layer_233_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 60}, .tiling_dimension = {8, 320, 1, 30}, .offset = {0, 0, 0, 30}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[198].compute_node,
+                          L2_IFM_Buffer_from_layer_5_for_layer_233_port0, tiling_params_layer_233, 0, 0);
+location<dma>(l2_233.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_233.out[0], l2l3_233_spill.in[0]);
+read_access(l2_233.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 1, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_233_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 1, 90}, .tiling_dimension = {8, 160, 1, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_233.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_233.out[1], l2l3_233_spill.in[1]);
+read_access(l2_233.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 1, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_233_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 1, 90}, .tiling_dimension = {8, 160, 1, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_233_for_layer_234_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_233_spill.out[0], L2_IFM_Buffer_from_layer_233_for_layer_234_port0.in[0]);
+read_access(l2l3_233_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 1, 90}, .tiling_dimension = {8, 160, 1, 45}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_233_for_layer_234_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 1, 90}, .tiling_dimension = {8, 160, 1, 45}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_233_for_layer_234_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_233_spill.out[1], L2_IFM_Buffer_from_layer_233_for_layer_234_port0.in[1]);
+read_access(l2l3_233_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 1, 90}, .tiling_dimension = {8, 160, 1, 45}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_233_for_layer_234_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 1, 90}, .tiling_dimension = {8, 160, 1, 45}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[199].compute_node,
+                          L2_IFM_Buffer_from_layer_233_for_layer_234_port0, tiling_params_layer_234, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[200].compute_node,
+                          l2_234, tiling_params_layer_235, 0, 0);
+location<dma>(L2_IFM_Buffer_from_layer_232_for_layer_236_port0.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L2_IFM_Buffer_from_layer_232_for_layer_236_port0.out[0], spill_L3_Concat_Buffer_layer_236.in[0]);
+read_access(L2_IFM_Buffer_from_layer_232_for_layer_236_port0.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 16, 23}, .tiling_dimension = {8, 40, 16, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_236.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 22, 23}, .tiling_dimension = {8, 40, 16, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_232_for_layer_236_port0.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L2_IFM_Buffer_from_layer_232_for_layer_236_port0.out[1], spill_L3_Concat_Buffer_layer_236.in[1]);
+read_access(L2_IFM_Buffer_from_layer_232_for_layer_236_port0.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 16, 23}, .tiling_dimension = {8, 40, 16, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_236.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 22, 23}, .tiling_dimension = {8, 40, 16, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_58.out[4]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_58.out[4], spill_L3_Concat_Buffer_layer_236.in[2]);
+read_access(l2_58.out[4]) = {
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_236.in[2]) = {
+  tiling({.buffer_dimension = {8, 40, 22, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 16, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_58.out[5]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_58.out[5], spill_L3_Concat_Buffer_layer_236.in[3]);
+read_access(l2_58.out[5]) = {
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_236.in[3]) = {
+  tiling({.buffer_dimension = {8, 40, 22, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 16, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_235.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_235.out[0], spill_L3_Concat_Buffer_layer_236.in[4]);
+read_access(l2_235.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 4, 24}, .tiling_dimension = {8, 40, 1, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_236.in[4]) = {
+  tiling({.buffer_dimension = {8, 40, 22, 23}, .tiling_dimension = {8, 40, 1, 11}, .offset = {0, 0, 21, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_235.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_235.out[1], spill_L3_Concat_Buffer_layer_236.in[5]);
+read_access(l2_235.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 4, 24}, .tiling_dimension = {8, 40, 1, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_236.in[5]) = {
+  tiling({.buffer_dimension = {8, 40, 22, 23}, .tiling_dimension = {8, 40, 1, 12}, .offset = {0, 0, 21, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_236_for_layer_237_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(spill_L3_Concat_Buffer_layer_236.out[0], L2_IFM_Buffer_from_layer_236_for_layer_237_port0.in[0]);
+read_access(spill_L3_Concat_Buffer_layer_236.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 22, 23}, .tiling_dimension = {8, 40, 22, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_236_for_layer_237_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 22, 23}, .tiling_dimension = {8, 40, 22, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_236_for_layer_237_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(spill_L3_Concat_Buffer_layer_236.out[1], L2_IFM_Buffer_from_layer_236_for_layer_237_port0.in[1]);
+read_access(spill_L3_Concat_Buffer_layer_236.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 22, 23}, .tiling_dimension = {8, 40, 22, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_236_for_layer_237_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 22, 23}, .tiling_dimension = {8, 40, 22, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[201].compute_node,
+                          L2_IFM_Buffer_from_layer_236_for_layer_237_port0, tiling_params_layer_237, 0, 0);
+location<dma>(l2_237.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_237.out[0], l2l3_237_spill.in[0]);
+read_access(l2_237.out[0]) = {
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 40, 10, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_237_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 40, 10, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_237.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_237.out[1], l2l3_237_spill.in[1]);
+read_access(l2_237.out[1]) = {
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 40, 10, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_237_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 40, 10, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_239_for_layer_240_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_239_spill.out[0], L2_IFM_Buffer_from_layer_239_for_layer_240_port0.in[0]);
+read_access(l2l3_239_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_239_for_layer_240_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_239_for_layer_240_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_239_spill.out[1], L2_IFM_Buffer_from_layer_239_for_layer_240_port0.in[1]);
+read_access(l2l3_239_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_239_for_layer_240_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_for_input3_0_port1.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(ifm_ddr_3.out[0], L2_IFM_Buffer_for_input3_0_port1.in[0]);
+read_access(ifm_ddr_3.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_for_input3_0_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_for_input3_0_port1.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(ifm_ddr_3.out[1], L2_IFM_Buffer_for_input3_0_port1.in[1]);
+read_access(ifm_ddr_3.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_for_input3_0_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_239_for_layer_240_port0.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L2_IFM_Buffer_from_layer_239_for_layer_240_port0.out[0], spill_L3_Concat_Buffer_layer_240.in[0]);
+read_access(L2_IFM_Buffer_from_layer_239_for_layer_240_port0.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_240.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_239_for_layer_240_port0.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L2_IFM_Buffer_from_layer_239_for_layer_240_port0.out[1], spill_L3_Concat_Buffer_layer_240.in[1]);
+read_access(L2_IFM_Buffer_from_layer_239_for_layer_240_port0.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_240.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_for_input3_0_port1.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L2_IFM_Buffer_for_input3_0_port1.out[0], spill_L3_Concat_Buffer_layer_240.in[2]);
+read_access(L2_IFM_Buffer_for_input3_0_port1.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_240.in[2]) = {
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 5, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_for_input3_0_port1.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L2_IFM_Buffer_for_input3_0_port1.out[1], spill_L3_Concat_Buffer_layer_240.in[3]);
+read_access(L2_IFM_Buffer_for_input3_0_port1.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_240.in[3]) = {
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 5, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_240_for_layer_241_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(spill_L3_Concat_Buffer_layer_240.out[0], L2_IFM_Buffer_from_layer_240_for_layer_241_port0.in[0]);
+read_access(spill_L3_Concat_Buffer_layer_240.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 40, 10, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_240_for_layer_241_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 40, 10, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_240_for_layer_241_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(spill_L3_Concat_Buffer_layer_240.out[1], L2_IFM_Buffer_from_layer_240_for_layer_241_port0.in[1]);
+read_access(spill_L3_Concat_Buffer_layer_240.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 40, 10, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_240_for_layer_241_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 40, 10, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[202].compute_node,
+                          L2_IFM_Buffer_from_layer_240_for_layer_241_port0, tiling_params_layer_241, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[203].compute_node,
+                          l2_241, tiling_params_layer_242, 0, 0);
+location<dma>(l2_242.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_242.out[0], l2l3_242_spill.in[0]);
+read_access(l2_242.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 40, 10, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_242_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 40, 10, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_242.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_242.out[1], l2l3_242_spill.in[1]);
+read_access(l2_242.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 40, 10, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_242_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 40, 10, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_CONST_IFM_Buffer_for_input2_0_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(const_ifm_ddr_2.out[0], L2_CONST_IFM_Buffer_for_input2_0_port0.in[0]);
+read_access(const_ifm_ddr_2.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_CONST_IFM_Buffer_for_input2_0_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_CONST_IFM_Buffer_for_input2_0_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(const_ifm_ddr_2.out[1], L2_CONST_IFM_Buffer_for_input2_0_port0.in[1]);
+read_access(const_ifm_ddr_2.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_CONST_IFM_Buffer_for_input2_0_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_243_for_layer_244_port1.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_243_spill.out[0], L2_IFM_Buffer_from_layer_243_for_layer_244_port1.in[0]);
+read_access(l2l3_243_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_243_for_layer_244_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_243_for_layer_244_port1.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_243_spill.out[1], L2_IFM_Buffer_from_layer_243_for_layer_244_port1.in[1]);
+read_access(l2l3_243_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_243_for_layer_244_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[204].compute_node,
+                          L2_CONST_IFM_Buffer_for_input2_0_port0, tiling_params_layer_244, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[204].compute_node,
+                          L2_IFM_Buffer_from_layer_243_for_layer_244_port1, tiling_params_layer_244_1, 0, 2);
+location<dma>(L2_IFM_Buffer_for_input3_1_port1.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(ifm_ddr_3.out[2], L2_IFM_Buffer_for_input3_1_port1.in[0]);
+read_access(ifm_ddr_3.out[2]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_for_input3_1_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_for_input3_1_port1.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(ifm_ddr_3.out[3], L2_IFM_Buffer_for_input3_1_port1.in[1]);
+read_access(ifm_ddr_3.out[3]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_for_input3_1_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[205].compute_node,
+                          l2_244, tiling_params_layer_245, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[205].compute_node,
+                          L2_IFM_Buffer_for_input3_1_port1, tiling_params_layer_245_1, 0, 2);
+location<dma>(l2_245.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_245.out[0], L3_OFM_Buffer_layer_TGSpilling_245245.in[0]);
+read_access(l2_245.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_245245.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_245.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_245.out[1], L3_OFM_Buffer_layer_TGSpilling_245245.in[1]);
+read_access(l2_245.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_245245.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_for_input3_2_port1.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(ifm_ddr_3.out[4], L2_IFM_Buffer_for_input3_2_port1.in[0]);
+read_access(ifm_ddr_3.out[4]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_for_input3_2_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_for_input3_2_port1.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(ifm_ddr_3.out[5], L2_IFM_Buffer_for_input3_2_port1.in[1]);
+read_access(ifm_ddr_3.out[5]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_for_input3_2_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_246_for_layer_247_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_246_spill.out[0], L2_IFM_Buffer_from_layer_246_for_layer_247_port0.in[0]);
+read_access(l2l3_246_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_246_for_layer_247_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_246_for_layer_247_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_246_spill.out[1], L2_IFM_Buffer_from_layer_246_for_layer_247_port0.in[1]);
+read_access(l2l3_246_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_246_for_layer_247_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[206].compute_node,
+                          L2_IFM_Buffer_from_layer_246_for_layer_247_port0, tiling_params_layer_247, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[206].compute_node,
+                          L2_IFM_Buffer_for_input3_2_port1, tiling_params_layer_247_1, 0, 2);
+location<dma>(L2_IFM_Buffer_from_layer_239_for_layer_248_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_239_spill.out[2], L2_IFM_Buffer_from_layer_239_for_layer_248_port0.in[0]);
+read_access(l2l3_239_spill.out[2]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_239_for_layer_248_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_239_for_layer_248_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_239_spill.out[3], L2_IFM_Buffer_from_layer_239_for_layer_248_port0.in[1]);
+read_access(l2l3_239_spill.out[3]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_239_for_layer_248_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_239_for_layer_248_port0.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L2_IFM_Buffer_from_layer_239_for_layer_248_port0.out[0], spill_L3_Concat_Buffer_layer_248.in[0]);
+read_access(L2_IFM_Buffer_from_layer_239_for_layer_248_port0.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_248.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_239_for_layer_248_port0.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L2_IFM_Buffer_from_layer_239_for_layer_248_port0.out[1], spill_L3_Concat_Buffer_layer_248.in[1]);
+read_access(L2_IFM_Buffer_from_layer_239_for_layer_248_port0.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_248.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_247.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_247.out[0], spill_L3_Concat_Buffer_layer_248.in[2]);
+read_access(l2_247.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_248.in[2]) = {
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 5, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_247.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_247.out[1], spill_L3_Concat_Buffer_layer_248.in[3]);
+read_access(l2_247.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_248.in[3]) = {
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 5, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_248_for_layer_249_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(spill_L3_Concat_Buffer_layer_248.out[0], L2_IFM_Buffer_from_layer_248_for_layer_249_port0.in[0]);
+read_access(spill_L3_Concat_Buffer_layer_248.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 40, 10, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_248_for_layer_249_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 40, 10, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_248_for_layer_249_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(spill_L3_Concat_Buffer_layer_248.out[1], L2_IFM_Buffer_from_layer_248_for_layer_249_port0.in[1]);
+read_access(spill_L3_Concat_Buffer_layer_248.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 40, 10, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_248_for_layer_249_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 40, 10, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[207].compute_node,
+                          L2_IFM_Buffer_from_layer_248_for_layer_249_port0, tiling_params_layer_249, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[208].compute_node,
+                          l2_249, tiling_params_layer_250, 0, 0);
+location<dma>(L2_IFM_Buffer_from_layer_243_for_layer_251_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_243_spill.out[2], L2_IFM_Buffer_from_layer_243_for_layer_251_port0.in[0]);
+read_access(l2l3_243_spill.out[2]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_243_for_layer_251_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_243_for_layer_251_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_243_spill.out[3], L2_IFM_Buffer_from_layer_243_for_layer_251_port0.in[1]);
+read_access(l2l3_243_spill.out[3]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_243_for_layer_251_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[209].compute_node,
+                          L2_IFM_Buffer_from_layer_243_for_layer_251_port0, tiling_params_layer_251, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[209].compute_node,
+                          l2_250, tiling_params_layer_251_1, 0, 2);
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_245245.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L3_OFM_Buffer_layer_TGSpilling_245245.out[0], L2_OFM_Buffer_layer_TGSpilling_245245.in[0]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_245245.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_245245.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_245245.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L3_OFM_Buffer_layer_TGSpilling_245245.out[1], L2_OFM_Buffer_layer_TGSpilling_245245.in[1]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_245245.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_245245.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[210].compute_node,
+                          L2_OFM_Buffer_layer_TGSpilling_245245, tiling_params_layer_252, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[210].compute_node,
+                          l2_251, tiling_params_layer_252_1, 0, 2);
+location<dma>(l2_252.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_252.out[0], ofm_ddr_1_l2l3_252_spill.in[0]);
+read_access(l2_252.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(ofm_ddr_1_l2l3_252_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_252.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_252.out[1], ofm_ddr_1_l2l3_252_spill.in[1]);
+read_access(l2_252.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(ofm_ddr_1_l2l3_252_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_238_for_layer_253_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_238_spill.out[0], L2_IFM_Buffer_from_layer_238_for_layer_253_port0.in[0]);
+read_access(l2l3_238_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_238_for_layer_253_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_238_for_layer_253_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_238_spill.out[1], L2_IFM_Buffer_from_layer_238_for_layer_253_port0.in[1]);
+read_access(l2l3_238_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_238_for_layer_253_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_238_for_layer_253_port0.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L2_IFM_Buffer_from_layer_238_for_layer_253_port0.out[0], spill_L3_Concat_Buffer_layer_253.in[0]);
+read_access(L2_IFM_Buffer_from_layer_238_for_layer_253_port0.out[0]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_253.in[0]) = {
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_238_for_layer_253_port0.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L2_IFM_Buffer_from_layer_238_for_layer_253_port0.out[1], spill_L3_Concat_Buffer_layer_253.in[1]);
+read_access(L2_IFM_Buffer_from_layer_238_for_layer_253_port0.out[1]) = {
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_253.in[1]) = {
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_252.out[2]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_252.out[2], spill_L3_Concat_Buffer_layer_253.in[2]);
+read_access(l2_252.out[2]) = {
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_253.in[2]) = {
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 40, 5, 11}, .offset = {0, 0, 5, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_252.out[3]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_252.out[3], spill_L3_Concat_Buffer_layer_253.in[3]);
+read_access(l2_252.out[3]) = {
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_253.in[3]) = {
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 40, 5, 12}, .offset = {0, 0, 5, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_255_for_layer_256_port0.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_255_spill.out[0], L2_IFM_Buffer_from_layer_255_for_layer_256_port0.in[0]);
+read_access(l2l3_255_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 80, 10, 45}, .tiling_dimension = {8, 80, 10, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_255_for_layer_256_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 80, 10, 45}, .tiling_dimension = {8, 80, 10, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_255_for_layer_256_port0.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_255_spill.out[1], L2_IFM_Buffer_from_layer_255_for_layer_256_port0.in[1]);
+read_access(l2l3_255_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 80, 10, 45}, .tiling_dimension = {8, 80, 10, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_255_for_layer_256_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 80, 10, 45}, .tiling_dimension = {8, 80, 10, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_255_for_layer_256_port0.out[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(L2_IFM_Buffer_from_layer_255_for_layer_256_port0.out[0], spill_L3_Concat_Buffer_layer_256.in[0]);
+read_access(L2_IFM_Buffer_from_layer_255_for_layer_256_port0.out[0]) = {
+  tiling({.buffer_dimension = {8, 80, 10, 45}, .tiling_dimension = {8, 80, 10, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_256.in[0]) = {
+  tiling({.buffer_dimension = {8, 80, 14, 45}, .tiling_dimension = {8, 80, 10, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_255_for_layer_256_port0.out[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(L2_IFM_Buffer_from_layer_255_for_layer_256_port0.out[1], spill_L3_Concat_Buffer_layer_256.in[1]);
+read_access(L2_IFM_Buffer_from_layer_255_for_layer_256_port0.out[1]) = {
+  tiling({.buffer_dimension = {8, 80, 10, 45}, .tiling_dimension = {8, 80, 10, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_256.in[1]) = {
+  tiling({.buffer_dimension = {8, 80, 14, 45}, .tiling_dimension = {8, 80, 10, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_22.out[4]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_22.out[4], spill_L3_Concat_Buffer_layer_256.in[2]);
+read_access(l2_22.out[4]) = {
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 80, 3, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_256.in[2]) = {
+  tiling({.buffer_dimension = {8, 80, 14, 45}, .tiling_dimension = {8, 80, 3, 22}, .offset = {0, 0, 10, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_22.out[5]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_22.out[5], spill_L3_Concat_Buffer_layer_256.in[3]);
+read_access(l2_22.out[5]) = {
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 80, 3, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_256.in[3]) = {
+  tiling({.buffer_dimension = {8, 80, 14, 45}, .tiling_dimension = {8, 80, 3, 23}, .offset = {0, 0, 10, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_234.out[4]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2_234.out[4], spill_L3_Concat_Buffer_layer_256.in[4]);
+read_access(l2_234.out[4]) = {
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 80, 1, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_256.in[4]) = {
+  tiling({.buffer_dimension = {8, 80, 14, 45}, .tiling_dimension = {8, 80, 1, 22}, .offset = {0, 0, 13, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_234.out[5]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2_234.out[5], spill_L3_Concat_Buffer_layer_256.in[5]);
+read_access(l2_234.out[5]) = {
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 80, 1, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_256.in[5]) = {
+  tiling({.buffer_dimension = {8, 80, 14, 45}, .tiling_dimension = {8, 80, 1, 23}, .offset = {0, 0, 13, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_256_for_layer_257_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(spill_L3_Concat_Buffer_layer_256.out[0], L2_IFM_Buffer_from_layer_256_for_layer_257_port0.in[0]);
+read_access(spill_L3_Concat_Buffer_layer_256.out[0]) = {
+  tiling({.buffer_dimension = {8, 80, 14, 45}, .tiling_dimension = {8, 80, 14, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_256_for_layer_257_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 80, 14, 45}, .tiling_dimension = {8, 80, 14, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_256_for_layer_257_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(spill_L3_Concat_Buffer_layer_256.out[1], L2_IFM_Buffer_from_layer_256_for_layer_257_port0.in[1]);
+read_access(spill_L3_Concat_Buffer_layer_256.out[1]) = {
+  tiling({.buffer_dimension = {8, 80, 14, 45}, .tiling_dimension = {8, 80, 14, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_256_for_layer_257_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 80, 14, 45}, .tiling_dimension = {8, 80, 14, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[211].compute_node,
+                          L2_IFM_Buffer_from_layer_256_for_layer_257_port0, tiling_params_layer_257, 0, 0);
+location<dma>(l2_257.out[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2_257.out[0], l2l3_257_spill.in[0]);
+read_access(l2_257.out[0]) = {
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 80, 5, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_257_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 80, 5, 45}, .tiling_dimension = {8, 80, 5, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_257.out[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2_257.out[1], l2l3_257_spill.in[1]);
+read_access(l2_257.out[1]) = {
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 80, 5, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_257_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 80, 5, 45}, .tiling_dimension = {8, 80, 5, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_260_for_layer_261_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_260_spill.out[0], L2_IFM_Buffer_from_layer_260_for_layer_261_port0.in[0]);
+read_access(l2l3_260_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 80, 5, 45}, .tiling_dimension = {8, 80, 5, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_260_for_layer_261_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 80, 5, 45}, .tiling_dimension = {8, 80, 5, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_260_for_layer_261_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_260_spill.out[1], L2_IFM_Buffer_from_layer_260_for_layer_261_port0.in[1]);
+read_access(l2l3_260_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 80, 5, 45}, .tiling_dimension = {8, 80, 5, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_260_for_layer_261_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 80, 5, 45}, .tiling_dimension = {8, 80, 5, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[212].compute_node,
+                          L2_IFM_Buffer_from_layer_260_for_layer_261_port0, tiling_params_layer_261, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[213].compute_node,
+                          l2_261, tiling_params_layer_262, 0, 0);
+location<dma>(l2_262.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_262.out[0], l2l3_262_spill.in[0]);
+read_access(l2_262.out[0]) = {
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 80, 5, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_262_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 80, 5, 45}, .tiling_dimension = {8, 80, 5, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_262.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_262.out[1], l2l3_262_spill.in[1]);
+read_access(l2_262.out[1]) = {
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 80, 5, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_262_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 80, 5, 45}, .tiling_dimension = {8, 80, 5, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_CONST_IFM_Buffer_for_input1_0_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(const_ifm_ddr_1.out[0], L2_CONST_IFM_Buffer_for_input1_0_port0.in[0]);
+read_access(const_ifm_ddr_1.out[0]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_CONST_IFM_Buffer_for_input1_0_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_CONST_IFM_Buffer_for_input1_0_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(const_ifm_ddr_1.out[1], L2_CONST_IFM_Buffer_for_input1_0_port0.in[1]);
+read_access(const_ifm_ddr_1.out[1]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_CONST_IFM_Buffer_for_input1_0_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_263_for_layer_264_port1.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_263_spill.out[0], L2_IFM_Buffer_from_layer_263_for_layer_264_port1.in[0]);
+read_access(l2l3_263_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_263_for_layer_264_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_263_for_layer_264_port1.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_263_spill.out[1], L2_IFM_Buffer_from_layer_263_for_layer_264_port1.in[1]);
+read_access(l2l3_263_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_263_for_layer_264_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[214].compute_node,
+                          L2_CONST_IFM_Buffer_for_input1_0_port0, tiling_params_layer_264, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[214].compute_node,
+                          L2_IFM_Buffer_from_layer_263_for_layer_264_port1, tiling_params_layer_264_1, 0, 2);
+location<dma>(L2_IFM_Buffer_for_input2_1_port1.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(ifm_ddr_2.out[1], L2_IFM_Buffer_for_input2_1_port1.in[0]);
+read_access(ifm_ddr_2.out[1]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_for_input2_1_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_for_input2_1_port1.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(ifm_ddr_2.out[2], L2_IFM_Buffer_for_input2_1_port1.in[1]);
+read_access(ifm_ddr_2.out[2]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_for_input2_1_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[215].compute_node,
+                          l2_264, tiling_params_layer_265, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[215].compute_node,
+                          L2_IFM_Buffer_for_input2_1_port1, tiling_params_layer_265_1, 0, 2);
+location<dma>(l2_265.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_265.out[0], L3_OFM_Buffer_layer_TGSpilling_265265.in[0]);
+read_access(l2_265.out[0]) = {
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 80, 3, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_265265.in[0]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_265.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_265.out[1], L3_OFM_Buffer_layer_TGSpilling_265265.in[1]);
+read_access(l2_265.out[1]) = {
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 80, 3, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L3_OFM_Buffer_layer_TGSpilling_265265.in[1]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_for_input2_2_port1.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(ifm_ddr_2.out[3], L2_IFM_Buffer_for_input2_2_port1.in[0]);
+read_access(ifm_ddr_2.out[3]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_for_input2_2_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_for_input2_2_port1.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(ifm_ddr_2.out[4], L2_IFM_Buffer_for_input2_2_port1.in[1]);
+read_access(ifm_ddr_2.out[4]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_for_input2_2_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_266_for_layer_267_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_266_spill.out[0], L2_IFM_Buffer_from_layer_266_for_layer_267_port0.in[0]);
+read_access(l2l3_266_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_266_for_layer_267_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_266_for_layer_267_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_266_spill.out[1], L2_IFM_Buffer_from_layer_266_for_layer_267_port0.in[1]);
+read_access(l2l3_266_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_266_for_layer_267_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[216].compute_node,
+                          L2_IFM_Buffer_from_layer_266_for_layer_267_port0, tiling_params_layer_267, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[216].compute_node,
+                          L2_IFM_Buffer_for_input2_2_port1, tiling_params_layer_267_1, 0, 2);
+location<dma>(l2_267.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_267.out[0], l2l3_267_spill.in[0]);
+read_access(l2_267.out[0]) = {
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 80, 3, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_267_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_267.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_267.out[1], l2l3_267_spill.in[1]);
+read_access(l2_267.out[1]) = {
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 80, 3, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_267_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_268_for_layer_269_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_268_spill.out[0], L2_IFM_Buffer_from_layer_268_for_layer_269_port0.in[0]);
+read_access(l2l3_268_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 80, 5, 45}, .tiling_dimension = {8, 80, 5, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_268_for_layer_269_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 80, 5, 45}, .tiling_dimension = {8, 80, 5, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_268_for_layer_269_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_268_spill.out[1], L2_IFM_Buffer_from_layer_268_for_layer_269_port0.in[1]);
+read_access(l2l3_268_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 80, 5, 45}, .tiling_dimension = {8, 80, 5, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_268_for_layer_269_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 80, 5, 45}, .tiling_dimension = {8, 80, 5, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[217].compute_node,
+                          L2_IFM_Buffer_from_layer_268_for_layer_269_port0, tiling_params_layer_269, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[218].compute_node,
+                          l2_269, tiling_params_layer_270, 0, 0);
+location<dma>(L2_IFM_Buffer_from_layer_263_for_layer_271_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_263_spill.out[2], L2_IFM_Buffer_from_layer_263_for_layer_271_port0.in[0]);
+read_access(l2l3_263_spill.out[2]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_263_for_layer_271_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_263_for_layer_271_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_263_spill.out[3], L2_IFM_Buffer_from_layer_263_for_layer_271_port0.in[1]);
+read_access(l2l3_263_spill.out[3]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_263_for_layer_271_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[219].compute_node,
+                          L2_IFM_Buffer_from_layer_263_for_layer_271_port0, tiling_params_layer_271, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[219].compute_node,
+                          l2_270, tiling_params_layer_271_1, 0, 2);
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_265265.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L3_OFM_Buffer_layer_TGSpilling_265265.out[0], L2_OFM_Buffer_layer_TGSpilling_265265.in[0]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_265265.out[0]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_265265.in[0]) = {
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 80, 3, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_OFM_Buffer_layer_TGSpilling_265265.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L3_OFM_Buffer_layer_TGSpilling_265265.out[1], L2_OFM_Buffer_layer_TGSpilling_265265.in[1]);
+read_access(L3_OFM_Buffer_layer_TGSpilling_265265.out[1]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_OFM_Buffer_layer_TGSpilling_265265.in[1]) = {
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 80, 3, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[220].compute_node,
+                          L2_OFM_Buffer_layer_TGSpilling_265265, tiling_params_layer_272, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[220].compute_node,
+                          l2_271, tiling_params_layer_272_1, 0, 2);
+location<dma>(l2_272.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_272.out[0], ofm_ddr_2_l2l3_272_spill.in[0]);
+read_access(l2_272.out[0]) = {
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 80, 3, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(ofm_ddr_2_l2l3_272_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_272.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_272.out[1], ofm_ddr_2_l2l3_272_spill.in[1]);
+read_access(l2_272.out[1]) = {
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 80, 3, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(ofm_ddr_2_l2l3_272_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 80, 3, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_14.out[2]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2_14.out[2], spill_L3_Concat_Buffer_layer_275.in[2]);
+read_access(l2_14.out[2]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 160, 2, 22}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_275.in[2]) = {
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 2, 22}, .offset = {0, 0, 5, 0}, .tile_traversal = { {.dimension = 3, .stride = 45, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_14.out[3]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2_14.out[3], spill_L3_Concat_Buffer_layer_275.in[3]);
+read_access(l2_14.out[3]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 160, 2, 23}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_275.in[3]) = {
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 2, 23}, .offset = {0, 0, 5, 22}, .tile_traversal = { {.dimension = 3, .stride = 45, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_233.out[2]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_233.out[2], spill_L3_Concat_Buffer_layer_275.in[4]);
+read_access(l2_233.out[2]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 1, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_275.in[4]) = {
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 1, 15}, .offset = {0, 0, 7, 0}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_233.out[3]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_233.out[3], spill_L3_Concat_Buffer_layer_275.in[5]);
+read_access(l2_233.out[3]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 1, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_275.in[5]) = {
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 1, 15}, .offset = {0, 0, 7, 15}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_275_for_layer_276_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(spill_L3_Concat_Buffer_layer_275.out[0], L2_IFM_Buffer_from_layer_275_for_layer_276_port0.in[0]);
+read_access(spill_L3_Concat_Buffer_layer_275.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 8, 9}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 8, 10}, .offset = {0, 0, 0, 17}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 8, 10}, .offset = {0, 0, 0, 35}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 8, 10}, .offset = {0, 0, 0, 53}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 8, 9}, .offset = {0, 0, 0, 71}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_275_for_layer_276_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 8, 19}, .tiling_dimension = {8, 160, 8, 9}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 20}, .tiling_dimension = {8, 160, 8, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 160, 8, 20}, .tiling_dimension = {8, 160, 8, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2}),
+  tiling({.buffer_dimension = {8, 160, 8, 20}, .tiling_dimension = {8, 160, 8, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 3}),
+  tiling({.buffer_dimension = {8, 160, 8, 19}, .tiling_dimension = {8, 160, 8, 9}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 4})
+};
+location<dma>(L2_IFM_Buffer_from_layer_275_for_layer_276_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(spill_L3_Concat_Buffer_layer_275.out[1], L2_IFM_Buffer_from_layer_275_for_layer_276_port0.in[1]);
+read_access(spill_L3_Concat_Buffer_layer_275.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 8, 10}, .offset = {0, 0, 0, 9}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 8, 10}, .offset = {0, 0, 0, 27}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 8, 10}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 8, 10}, .offset = {0, 0, 0, 63}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 90}, .tiling_dimension = {8, 160, 8, 10}, .offset = {0, 0, 0, 80}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_275_for_layer_276_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 8, 19}, .tiling_dimension = {8, 160, 8, 10}, .offset = {0, 0, 0, 9}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 20}, .tiling_dimension = {8, 160, 8, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 160, 8, 20}, .tiling_dimension = {8, 160, 8, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2}),
+  tiling({.buffer_dimension = {8, 160, 8, 20}, .tiling_dimension = {8, 160, 8, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 3}),
+  tiling({.buffer_dimension = {8, 160, 8, 19}, .tiling_dimension = {8, 160, 8, 10}, .offset = {0, 0, 0, 9}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 4})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[221].compute_node,
+                          L2_IFM_Buffer_from_layer_275_for_layer_276_port0, tiling_params_layer_276, 0, 0);
+location<dma>(l2_276.out[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2_276.out[0], l2l3_276_spill.in[0]);
+read_access(l2_276.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 20}, .tiling_dimension = {8, 160, 4, 9}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_276_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 4, 9}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 18, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_276.out[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2_276.out[1], l2l3_276_spill.in[1]);
+read_access(l2_276.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 20}, .tiling_dimension = {8, 160, 4, 9}, .offset = {0, 0, 0, 9}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_276_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 4, 9}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 3, .stride = 18, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_278_for_layer_279_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_278_spill.out[0], L2_IFM_Buffer_from_layer_278_for_layer_279_port0.in[0]);
+read_access(l2l3_278_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_278_for_layer_279_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_278_for_layer_279_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_278_spill.out[1], L2_IFM_Buffer_from_layer_278_for_layer_279_port0.in[1]);
+read_access(l2l3_278_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_278_for_layer_279_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_for_input1_0_port1.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(ifm_ddr_1.out[0], L2_IFM_Buffer_for_input1_0_port1.in[0]);
+read_access(ifm_ddr_1.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_for_input1_0_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_for_input1_0_port1.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(ifm_ddr_1.out[1], L2_IFM_Buffer_for_input1_0_port1.in[1]);
+read_access(ifm_ddr_1.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_for_input1_0_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_278_for_layer_279_port0.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L2_IFM_Buffer_from_layer_278_for_layer_279_port0.out[0], spill_L3_Concat_Buffer_layer_279.in[0]);
+read_access(L2_IFM_Buffer_from_layer_278_for_layer_279_port0.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_279.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_278_for_layer_279_port0.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L2_IFM_Buffer_from_layer_278_for_layer_279_port0.out[1], spill_L3_Concat_Buffer_layer_279.in[1]);
+read_access(L2_IFM_Buffer_from_layer_278_for_layer_279_port0.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_279.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_for_input1_0_port1.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L2_IFM_Buffer_for_input1_0_port1.out[0], spill_L3_Concat_Buffer_layer_279.in[2]);
+read_access(L2_IFM_Buffer_for_input1_0_port1.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_279.in[2]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 2, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_for_input1_0_port1.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L2_IFM_Buffer_for_input1_0_port1.out[1], spill_L3_Concat_Buffer_layer_279.in[3]);
+read_access(L2_IFM_Buffer_for_input1_0_port1.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_279.in[3]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 2, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_279_for_layer_280_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(spill_L3_Concat_Buffer_layer_279.out[0], L2_IFM_Buffer_from_layer_279_for_layer_280_port0.in[0]);
+read_access(spill_L3_Concat_Buffer_layer_279.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 4, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 4, 16}, .offset = {0, 0, 0, 29}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 4, 15}, .offset = {0, 0, 0, 59}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_279_for_layer_280_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 31}, .tiling_dimension = {8, 160, 4, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 4, 16}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 160, 4, 31}, .tiling_dimension = {8, 160, 4, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2})
+};
+location<dma>(L2_IFM_Buffer_from_layer_279_for_layer_280_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(spill_L3_Concat_Buffer_layer_279.out[1], L2_IFM_Buffer_from_layer_279_for_layer_280_port0.in[1]);
+read_access(spill_L3_Concat_Buffer_layer_279.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 4, 16}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 4, 16}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 4, 16}, .offset = {0, 0, 0, 74}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_279_for_layer_280_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 31}, .tiling_dimension = {8, 160, 4, 16}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 4, 16}, .offset = {0, 0, 0, 16}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 160, 4, 31}, .tiling_dimension = {8, 160, 4, 16}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[222].compute_node,
+                          L2_IFM_Buffer_from_layer_279_for_layer_280_port0, tiling_params_layer_280, 0, 0);
+location<dma>(l2_280.out[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2_280.out[0], l2l3_280_spill.in[0]);
+read_access(l2_280.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 4, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_280_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 4, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_280.out[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2_280.out[1], l2l3_280_spill.in[1]);
+read_access(l2_280.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 4, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_280_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 4, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_280_for_layer_281_port0.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_280_spill.out[0], L2_IFM_Buffer_from_layer_280_for_layer_281_port0.in[0]);
+read_access(l2l3_280_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 4, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_280_for_layer_281_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 30}, .tiling_dimension = {8, 160, 4, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_280_for_layer_281_port0.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_280_spill.out[1], L2_IFM_Buffer_from_layer_280_for_layer_281_port0.in[1]);
+read_access(l2l3_280_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 4, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_280_for_layer_281_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 30}, .tiling_dimension = {8, 160, 4, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[223].compute_node,
+                          L2_IFM_Buffer_from_layer_280_for_layer_281_port0, tiling_params_layer_281, 0, 0);
+location<dma>(l2_281.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_281.out[0], l2l3_281_spill.in[0]);
+read_access(l2_281.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 4, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_281_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 4, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_281.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_281.out[1], l2l3_281_spill.in[1]);
+read_access(l2_281.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 4, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_281_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 4, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_CONST_IFM_Buffer_for_input0_0_port0.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(const_ifm_ddr.out[0], L2_CONST_IFM_Buffer_for_input0_0_port0.in[0]);
+read_access(const_ifm_ddr.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_CONST_IFM_Buffer_for_input0_0_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_CONST_IFM_Buffer_for_input0_0_port0.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(const_ifm_ddr.out[1], L2_CONST_IFM_Buffer_for_input0_0_port0.in[1]);
+read_access(const_ifm_ddr.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_CONST_IFM_Buffer_for_input0_0_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_282_for_layer_283_port1.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_282_spill.out[0], L2_IFM_Buffer_from_layer_282_for_layer_283_port1.in[0]);
+read_access(l2l3_282_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_282_for_layer_283_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_282_for_layer_283_port1.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_282_spill.out[1], L2_IFM_Buffer_from_layer_282_for_layer_283_port1.in[1]);
+read_access(l2l3_282_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_282_for_layer_283_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[224].compute_node,
+                          L2_CONST_IFM_Buffer_for_input0_0_port0, tiling_params_layer_283, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[224].compute_node,
+                          L2_IFM_Buffer_from_layer_282_for_layer_283_port1, tiling_params_layer_283_1, 0, 2);
+location<dma>(l2_283.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_283.out[0], l2l3_283_spill.in[0]);
+read_access(l2_283.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_283_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_283.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_283.out[1], l2l3_283_spill.in[1]);
+read_access(l2_283.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_283_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_for_input1_1_port1.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(ifm_ddr_1.out[2], L2_IFM_Buffer_for_input1_1_port1.in[0]);
+read_access(ifm_ddr_1.out[2]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_for_input1_1_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_for_input1_1_port1.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(ifm_ddr_1.out[3], L2_IFM_Buffer_for_input1_1_port1.in[1]);
+read_access(ifm_ddr_1.out[3]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_for_input1_1_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_283_for_layer_284_port0.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_283_spill.out[0], L2_IFM_Buffer_from_layer_283_for_layer_284_port0.in[0]);
+read_access(l2l3_283_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_283_for_layer_284_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_283_for_layer_284_port0.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_283_spill.out[1], L2_IFM_Buffer_from_layer_283_for_layer_284_port0.in[1]);
+read_access(l2l3_283_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_283_for_layer_284_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[225].compute_node,
+                          L2_IFM_Buffer_from_layer_283_for_layer_284_port0, tiling_params_layer_284, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[225].compute_node,
+                          L2_IFM_Buffer_for_input1_1_port1, tiling_params_layer_284_1, 0, 2);
+location<dma>(l2_284.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_284.out[0], l2l3_284_spill.in[0]);
+read_access(l2_284.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_284_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_284.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_284.out[1], l2l3_284_spill.in[1]);
+read_access(l2_284.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_284_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_for_input1_2_port1.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(ifm_ddr_1.out[4], L2_IFM_Buffer_for_input1_2_port1.in[0]);
+read_access(ifm_ddr_1.out[4]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_for_input1_2_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_for_input1_2_port1.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(ifm_ddr_1.out[5], L2_IFM_Buffer_for_input1_2_port1.in[1]);
+read_access(ifm_ddr_1.out[5]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_for_input1_2_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_285_for_layer_286_port0.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_285_spill.out[0], L2_IFM_Buffer_from_layer_285_for_layer_286_port0.in[0]);
+read_access(l2l3_285_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_285_for_layer_286_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_285_for_layer_286_port0.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_285_spill.out[1], L2_IFM_Buffer_from_layer_285_for_layer_286_port0.in[1]);
+read_access(l2l3_285_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_285_for_layer_286_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[226].compute_node,
+                          L2_IFM_Buffer_from_layer_285_for_layer_286_port0, tiling_params_layer_286, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[226].compute_node,
+                          L2_IFM_Buffer_for_input1_2_port1, tiling_params_layer_286_1, 0, 2);
+location<dma>(L2_IFM_Buffer_from_layer_278_for_layer_287_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_278_spill.out[2], L2_IFM_Buffer_from_layer_278_for_layer_287_port0.in[0]);
+read_access(l2l3_278_spill.out[2]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_278_for_layer_287_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_278_for_layer_287_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_278_spill.out[3], L2_IFM_Buffer_from_layer_278_for_layer_287_port0.in[1]);
+read_access(l2l3_278_spill.out[3]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_278_for_layer_287_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_278_for_layer_287_port0.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L2_IFM_Buffer_from_layer_278_for_layer_287_port0.out[0], spill_L3_Concat_Buffer_layer_287.in[0]);
+read_access(L2_IFM_Buffer_from_layer_278_for_layer_287_port0.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_287.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_278_for_layer_287_port0.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L2_IFM_Buffer_from_layer_278_for_layer_287_port0.out[1], spill_L3_Concat_Buffer_layer_287.in[1]);
+read_access(L2_IFM_Buffer_from_layer_278_for_layer_287_port0.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_287.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_286.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_286.out[0], spill_L3_Concat_Buffer_layer_287.in[2]);
+read_access(l2_286.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_287.in[2]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_286.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_286.out[1], spill_L3_Concat_Buffer_layer_287.in[3]);
+read_access(l2_286.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_287.in[3]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 2, 15}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_287_for_layer_288_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(spill_L3_Concat_Buffer_layer_287.out[0], L2_IFM_Buffer_from_layer_287_for_layer_288_port0.in[0]);
+read_access(spill_L3_Concat_Buffer_layer_287.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 4, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 4, 16}, .offset = {0, 0, 0, 29}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 4, 15}, .offset = {0, 0, 0, 59}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_287_for_layer_288_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 31}, .tiling_dimension = {8, 160, 4, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 4, 16}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 160, 4, 31}, .tiling_dimension = {8, 160, 4, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2})
+};
+location<dma>(L2_IFM_Buffer_from_layer_287_for_layer_288_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(spill_L3_Concat_Buffer_layer_287.out[1], L2_IFM_Buffer_from_layer_287_for_layer_288_port0.in[1]);
+read_access(spill_L3_Concat_Buffer_layer_287.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 4, 16}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 4, 16}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 4, 16}, .offset = {0, 0, 0, 74}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_287_for_layer_288_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 31}, .tiling_dimension = {8, 160, 4, 16}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 4, 16}, .offset = {0, 0, 0, 16}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 160, 4, 31}, .tiling_dimension = {8, 160, 4, 16}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[227].compute_node,
+                          L2_IFM_Buffer_from_layer_287_for_layer_288_port0, tiling_params_layer_288, 0, 0);
+location<dma>(l2_288.out[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2_288.out[0], l2l3_288_spill.in[0]);
+read_access(l2_288.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_288_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_288.out[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2_288.out[1], l2l3_288_spill.in[1]);
+read_access(l2_288.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_288_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_288_for_layer_289_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_288_spill.out[0], L2_IFM_Buffer_from_layer_288_for_layer_289_port0.in[0]);
+read_access(l2l3_288_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_288_for_layer_289_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_288_for_layer_289_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_288_spill.out[1], L2_IFM_Buffer_from_layer_288_for_layer_289_port0.in[1]);
+read_access(l2l3_288_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_288_for_layer_289_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[228].compute_node,
+                          L2_IFM_Buffer_from_layer_288_for_layer_289_port0, tiling_params_layer_289, 0, 0);
+location<dma>(l2_289.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_289.out[0], l2l3_289_spill.in[0]);
+read_access(l2_289.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 160, 2, 46}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_289_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 46}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_289.out[1]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2_289.out[1], l2l3_289_spill.in[1]);
+read_access(l2_289.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 160, 2, 44}, .offset = {0, 0, 0, 46}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_289_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 44}, .offset = {0, 0, 0, 46}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_282_for_layer_290_port0.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_282_spill.out[2], L2_IFM_Buffer_from_layer_282_for_layer_290_port0.in[0]);
+read_access(l2l3_282_spill.out[2]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_282_for_layer_290_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_282_for_layer_290_port0.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_282_spill.out[3], L2_IFM_Buffer_from_layer_282_for_layer_290_port0.in[1]);
+read_access(l2l3_282_spill.out[3]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_282_for_layer_290_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_289_for_layer_290_port1.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_289_spill.out[0], L2_IFM_Buffer_from_layer_289_for_layer_290_port1.in[0]);
+read_access(l2l3_289_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_289_for_layer_290_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_289_for_layer_290_port1.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_289_spill.out[1], L2_IFM_Buffer_from_layer_289_for_layer_290_port1.in[1]);
+read_access(l2l3_289_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_289_for_layer_290_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[229].compute_node,
+                          L2_IFM_Buffer_from_layer_282_for_layer_290_port0, tiling_params_layer_290, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[229].compute_node,
+                          L2_IFM_Buffer_from_layer_289_for_layer_290_port1, tiling_params_layer_290_1, 0, 2);
+location<dma>(l2_290.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_290.out[0], l2l3_290_spill.in[0]);
+read_access(l2_290.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_290_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_290.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_290.out[1], l2l3_290_spill.in[1]);
+read_access(l2_290.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_290_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_284_for_layer_291_port0.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_284_spill.out[0], L2_IFM_Buffer_from_layer_284_for_layer_291_port0.in[0]);
+read_access(l2l3_284_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_284_for_layer_291_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_284_for_layer_291_port0.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_284_spill.out[1], L2_IFM_Buffer_from_layer_284_for_layer_291_port0.in[1]);
+read_access(l2l3_284_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_284_for_layer_291_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_290_for_layer_291_port1.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_290_spill.out[0], L2_IFM_Buffer_from_layer_290_for_layer_291_port1.in[0]);
+read_access(l2l3_290_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_290_for_layer_291_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_290_for_layer_291_port1.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_290_spill.out[1], L2_IFM_Buffer_from_layer_290_for_layer_291_port1.in[1]);
+read_access(l2l3_290_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_290_for_layer_291_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[230].compute_node,
+                          L2_IFM_Buffer_from_layer_284_for_layer_291_port0, tiling_params_layer_291, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[230].compute_node,
+                          L2_IFM_Buffer_from_layer_290_for_layer_291_port1, tiling_params_layer_291_1, 0, 2);
+location<dma>(l2_291.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_291.out[0], ofm_ddr_3_l2l3_291_spill.in[0]);
+read_access(l2_291.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(ofm_ddr_3_l2l3_291_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_291.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_291.out[1], ofm_ddr_3_l2l3_291_spill.in[1]);
+read_access(l2_291.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(ofm_ddr_3_l2l3_291_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_277_for_layer_292_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2l3_277_spill.out[0], L2_IFM_Buffer_from_layer_277_for_layer_292_port0.in[0]);
+read_access(l2l3_277_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_277_for_layer_292_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_277_for_layer_292_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2l3_277_spill.out[1], L2_IFM_Buffer_from_layer_277_for_layer_292_port0.in[1]);
+read_access(l2l3_277_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_277_for_layer_292_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_277_for_layer_292_port0.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L2_IFM_Buffer_from_layer_277_for_layer_292_port0.out[0], spill_L3_Concat_Buffer_layer_292.in[0]);
+read_access(L2_IFM_Buffer_from_layer_277_for_layer_292_port0.out[0]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_292.in[0]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_277_for_layer_292_port0.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L2_IFM_Buffer_from_layer_277_for_layer_292_port0.out[1], spill_L3_Concat_Buffer_layer_292.in[1]);
+read_access(L2_IFM_Buffer_from_layer_277_for_layer_292_port0.out[1]) = {
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_292.in[1]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 2, 45}, .offset = {0, 0, 0, 45}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_291.out[2]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_291.out[2], spill_L3_Concat_Buffer_layer_292.in[2]);
+read_access(l2_291.out[2]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_292.in[2]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_291.out[3]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_291.out[3], spill_L3_Concat_Buffer_layer_292.in[3]);
+read_access(l2_291.out[3]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 0, 15}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_292.in[3]) = {
+  tiling({.buffer_dimension = {8, 160, 4, 90}, .tiling_dimension = {8, 160, 2, 15}, .offset = {0, 0, 2, 15}, .tile_traversal = { {.dimension = 3, .stride = 30, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_5_for_layer_294_port1.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_5_spill.out[4], L2_IFM_Buffer_from_layer_5_for_layer_294_port1.in[0]);
+read_access(l2l3_5_spill.out[4]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 90}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_5_for_layer_294_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 90}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_5_for_layer_294_port1.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_5_spill.out[5], L2_IFM_Buffer_from_layer_5_for_layer_294_port1.in[1]);
+read_access(l2l3_5_spill.out[5]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 90}, .offset = {0, 0, 0, 90}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_5_for_layer_294_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 90}, .offset = {0, 0, 0, 90}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_5_for_layer_294_port1.out[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(L2_IFM_Buffer_from_layer_5_for_layer_294_port1.out[0], spill_L3_Concat_Buffer_layer_294.in[2]);
+read_access(L2_IFM_Buffer_from_layer_5_for_layer_294_port1.out[0]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 90}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_294.in[2]) = {
+  tiling({.buffer_dimension = {8, 320, 5, 180}, .tiling_dimension = {8, 320, 1, 90}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_5_for_layer_294_port1.out[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(L2_IFM_Buffer_from_layer_5_for_layer_294_port1.out[1], spill_L3_Concat_Buffer_layer_294.in[3]);
+read_access(L2_IFM_Buffer_from_layer_5_for_layer_294_port1.out[1]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 90}, .offset = {0, 0, 0, 90}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(spill_L3_Concat_Buffer_layer_294.in[3]) = {
+  tiling({.buffer_dimension = {8, 320, 5, 180}, .tiling_dimension = {8, 320, 1, 90}, .offset = {0, 0, 4, 90}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_294_for_layer_295_port0.in[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(spill_L3_Concat_Buffer_layer_294.out[0], L2_IFM_Buffer_from_layer_294_for_layer_295_port0.in[0]);
+read_access(spill_L3_Concat_Buffer_layer_294.out[0]) = {
+  tiling({.buffer_dimension = {8, 320, 5, 180}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 180}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 14}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 180}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 29}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 180}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 44}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 180}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 59}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 180}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 74}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 180}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 89}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 180}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 104}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 180}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 119}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 180}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 134}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 180}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 149}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 180}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 164}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_294_for_layer_295_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 320, 5, 16}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 3}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 4}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 5}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 6}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 7}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 8}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 9}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 10}),
+  tiling({.buffer_dimension = {8, 320, 5, 16}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 11})
+};
+location<dma>(L2_IFM_Buffer_from_layer_294_for_layer_295_port0.in[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(spill_L3_Concat_Buffer_layer_294.out[1], L2_IFM_Buffer_from_layer_294_for_layer_295_port0.in[1]);
+read_access(spill_L3_Concat_Buffer_layer_294.out[1]) = {
+  tiling({.buffer_dimension = {8, 320, 5, 180}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 180}, .tiling_dimension = {8, 320, 5, 9}, .offset = {0, 0, 0, 22}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 180}, .tiling_dimension = {8, 320, 5, 9}, .offset = {0, 0, 0, 37}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 180}, .tiling_dimension = {8, 320, 5, 9}, .offset = {0, 0, 0, 52}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 180}, .tiling_dimension = {8, 320, 5, 9}, .offset = {0, 0, 0, 67}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 180}, .tiling_dimension = {8, 320, 5, 9}, .offset = {0, 0, 0, 82}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 180}, .tiling_dimension = {8, 320, 5, 9}, .offset = {0, 0, 0, 97}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 180}, .tiling_dimension = {8, 320, 5, 9}, .offset = {0, 0, 0, 112}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 180}, .tiling_dimension = {8, 320, 5, 9}, .offset = {0, 0, 0, 127}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 180}, .tiling_dimension = {8, 320, 5, 9}, .offset = {0, 0, 0, 142}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 180}, .tiling_dimension = {8, 320, 5, 9}, .offset = {0, 0, 0, 157}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 180}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 172}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_294_for_layer_295_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 320, 5, 16}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 320, 5, 9}, .offset = {0, 0, 0, 8}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 320, 5, 9}, .offset = {0, 0, 0, 8}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 320, 5, 9}, .offset = {0, 0, 0, 8}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 3}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 320, 5, 9}, .offset = {0, 0, 0, 8}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 4}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 320, 5, 9}, .offset = {0, 0, 0, 8}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 5}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 320, 5, 9}, .offset = {0, 0, 0, 8}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 6}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 320, 5, 9}, .offset = {0, 0, 0, 8}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 7}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 320, 5, 9}, .offset = {0, 0, 0, 8}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 8}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 320, 5, 9}, .offset = {0, 0, 0, 8}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 9}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 320, 5, 9}, .offset = {0, 0, 0, 8}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 10}),
+  tiling({.buffer_dimension = {8, 320, 5, 16}, .tiling_dimension = {8, 320, 5, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 11})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[231].compute_node,
+                          L2_IFM_Buffer_from_layer_294_for_layer_295_port0, tiling_params_layer_295, 0, 0);
+location<dma>(l2_295.out[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2_295.out[0], l2l3_295_spill.in[0]);
+read_access(l2_295.out[0]) = {
+  tiling({.buffer_dimension = {8, 320, 4, 16}, .tiling_dimension = {8, 320, 2, 7}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_295_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 320, 2, 180}, .tiling_dimension = {8, 320, 2, 7}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 15, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_295.out[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2_295.out[1], l2l3_295_spill.in[1]);
+read_access(l2_295.out[1]) = {
+  tiling({.buffer_dimension = {8, 320, 4, 16}, .tiling_dimension = {8, 320, 2, 8}, .offset = {0, 0, 0, 7}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_295_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 320, 2, 180}, .tiling_dimension = {8, 320, 2, 8}, .offset = {0, 0, 0, 7}, .tile_traversal = { {.dimension = 3, .stride = 15, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_295_for_layer_296_port0.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_295_spill.out[0], L2_IFM_Buffer_from_layer_295_for_layer_296_port0.in[0]);
+read_access(l2l3_295_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 320, 2, 180}, .tiling_dimension = {8, 320, 2, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 2, 180}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 19}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 2, 180}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 39}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 2, 180}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 59}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 2, 180}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 79}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 2, 180}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 99}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 2, 180}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 119}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 2, 180}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 139}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 2, 180}, .tiling_dimension = {8, 320, 2, 10}, .offset = {0, 0, 0, 159}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_295_for_layer_296_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 320, 2, 21}, .tiling_dimension = {8, 320, 2, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 3}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 4}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 5}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 6}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 7}),
+  tiling({.buffer_dimension = {8, 320, 2, 21}, .tiling_dimension = {8, 320, 2, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 8})
+};
+location<dma>(L2_IFM_Buffer_from_layer_295_for_layer_296_port0.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_295_spill.out[1], L2_IFM_Buffer_from_layer_295_for_layer_296_port0.in[1]);
+read_access(l2l3_295_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 320, 2, 180}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 10}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 2, 180}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 30}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 2, 180}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 50}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 2, 180}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 70}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 2, 180}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 90}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 2, 180}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 110}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 2, 180}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 130}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 2, 180}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 150}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 2, 180}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 169}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_295_for_layer_296_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 320, 2, 21}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 10}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 3}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 4}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 5}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 6}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 7}),
+  tiling({.buffer_dimension = {8, 320, 2, 21}, .tiling_dimension = {8, 320, 2, 11}, .offset = {0, 0, 0, 10}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 8})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[232].compute_node,
+                          L2_IFM_Buffer_from_layer_295_for_layer_296_port0, tiling_params_layer_296, 0, 0);
+location<dma>(l2_296.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_296.out[0], l2l3_296_spill.in[0]);
+read_access(l2_296.out[0]) = {
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 320, 2, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_296_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 320, 2, 180}, .tiling_dimension = {8, 320, 2, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_296.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_296.out[1], l2l3_296_spill.in[1]);
+read_access(l2_296.out[1]) = {
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 320, 2, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_296_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 320, 2, 180}, .tiling_dimension = {8, 320, 2, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_296_for_layer_297_port0.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_296_spill.out[0], L2_IFM_Buffer_from_layer_296_for_layer_297_port0.in[0]);
+read_access(l2l3_296_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 320, 2, 180}, .tiling_dimension = {8, 320, 2, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_296_for_layer_297_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 320, 2, 20}, .tiling_dimension = {8, 320, 2, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_296_for_layer_297_port0.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_296_spill.out[1], L2_IFM_Buffer_from_layer_296_for_layer_297_port0.in[1]);
+read_access(l2l3_296_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 320, 2, 180}, .tiling_dimension = {8, 320, 2, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_296_for_layer_297_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 320, 2, 20}, .tiling_dimension = {8, 320, 2, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[233].compute_node,
+                          L2_IFM_Buffer_from_layer_296_for_layer_297_port0, tiling_params_layer_297, 0, 0);
+location<dma>(l2_297.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_297.out[0], l2l3_297_spill.in[0]);
+read_access(l2_297.out[0]) = {
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_297_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_297.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_297.out[1], l2l3_297_spill.in[1]);
+read_access(l2_297.out[1]) = {
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_297_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_298_for_layer_299_port0.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_298_spill.out[0], L2_IFM_Buffer_from_layer_298_for_layer_299_port0.in[0]);
+read_access(l2l3_298_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_298_for_layer_299_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_298_for_layer_299_port0.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_298_spill.out[1], L2_IFM_Buffer_from_layer_298_for_layer_299_port0.in[1]);
+read_access(l2l3_298_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_298_for_layer_299_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[234].compute_node,
+                          L2_IFM_Buffer_from_layer_298_for_layer_299_port0, tiling_params_layer_299, 0, 0);
+location<dma>(L2_OFM_Buffer_layer_299.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L2_OFM_Buffer_layer_299.out[0], ofm_ddr_4.in[0]);
+read_access(L2_OFM_Buffer_layer_299.out[0]) = {
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(ofm_ddr_4.in[0]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_OFM_Buffer_layer_299.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L2_OFM_Buffer_layer_299.out[1], ofm_ddr_4.in[1]);
+read_access(L2_OFM_Buffer_layer_299.out[1]) = {
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(ofm_ddr_4.in[1]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_5_for_layer_301_port1.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_5_spill.out[6], L2_IFM_Buffer_from_layer_5_for_layer_301_port1.in[0]);
+read_access(l2l3_5_spill.out[6]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_5_for_layer_301_port1.in[0]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_5_for_layer_301_port1.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_5_spill.out[7], L2_IFM_Buffer_from_layer_5_for_layer_301_port1.in[1]);
+read_access(l2l3_5_spill.out[7]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_5_for_layer_301_port1.in[1]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_300_for_layer_301_port0.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_300_spill.out[0], L2_IFM_Buffer_from_layer_300_for_layer_301_port0.in[0]);
+read_access(l2l3_300_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_300_for_layer_301_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_300_for_layer_301_port0.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_300_spill.out[1], L2_IFM_Buffer_from_layer_300_for_layer_301_port0.in[1]);
+read_access(l2l3_300_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_300_for_layer_301_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[235].compute_node,
+                          L2_IFM_Buffer_from_layer_300_for_layer_301_port0, tiling_params_layer_301, 0, 0);
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[235].compute_node,
+                          L2_IFM_Buffer_from_layer_5_for_layer_301_port1, tiling_params_layer_301_1, 0, 2);
+location<dma>(l2_301.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(l2_301.out[0], l2l3_301_spill.in[0]);
+read_access(l2_301.out[0]) = {
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_301_spill.in[0]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(l2_301.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(l2_301.out[1], l2l3_301_spill.in[1]);
+read_access(l2_301.out[1]) = {
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(l2l3_301_spill.in[1]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_301_for_layer_302_port0.in[0]) = dma_channel(memory_tile, 2, 0, 0);
+connect(l2l3_301_spill.out[0], L2_IFM_Buffer_from_layer_301_for_layer_302_port0.in[0]);
+read_access(l2l3_301_spill.out[0]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_301_for_layer_302_port0.in[0]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_IFM_Buffer_from_layer_301_for_layer_302_port0.in[1]) = dma_channel(memory_tile, 2, 0, 1);
+connect(l2l3_301_spill.out[1], L2_IFM_Buffer_from_layer_301_for_layer_302_port0.in[1]);
+read_access(l2l3_301_spill.out[1]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(L2_IFM_Buffer_from_layer_301_for_layer_302_port0.in[1]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+ml_adf_overlay_4x4::connect_ifm<bfloat16>(flexml_layers[236].compute_node,
+                          L2_IFM_Buffer_from_layer_301_for_layer_302_port0, tiling_params_layer_302, 0, 0);
+location<dma>(L2_OFM_Buffer_layer_302.out[0]) = dma_channel(memory_tile, 0, 0, 0);
+connect(L2_OFM_Buffer_layer_302.out[0], ofm_ddr_5.in[0]);
+read_access(L2_OFM_Buffer_layer_302.out[0]) = {
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(ofm_ddr_5.in[0]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+location<dma>(L2_OFM_Buffer_layer_302.out[1]) = dma_channel(memory_tile, 0, 0, 1);
+connect(L2_OFM_Buffer_layer_302.out[1], ofm_ddr_5.in[1]);
+read_access(L2_OFM_Buffer_layer_302.out[1]) = {
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+write_access(ofm_ddr_5.in[1]) = {
+  tiling({.buffer_dimension = {8, 320, 1, 180}, .tiling_dimension = {8, 320, 1, 10}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 3, .stride = 20, .wrap = 9} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+};
+//Shimtile DMA co-location constraints
+location<dma>(l2l3_1_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_2_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_scratch_0_3_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_3_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_4_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_scratch_0_5_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_8_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_10_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_12_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_12_spill.out[2]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_13_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_15_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_16_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_scratch_0_17_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_17_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_20_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_scratch_0_21_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_1818.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_21_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_24_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_25_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_31_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_scratch_0_32_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_scratch_1_32_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_32_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_2424.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_36_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_37_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_43_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_scratch_0_44_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_scratch_1_44_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_44_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_3636.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_3434.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_48_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_49_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_55_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_scratch_0_56_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_scratch_1_56_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_56_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_4848.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_4646.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_63_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_scratch_0_64_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_64_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_113_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_114_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_120_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_scratch_0_121_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_scratch_1_121_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_121_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_113113.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_133_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_134_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_140_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_scratch_0_141_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_scratch_1_141_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_141_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_133133.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_123123.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_153_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_154_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_160_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_scratch_0_161_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_scratch_1_161_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_161_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_153153.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_168_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_173_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_174_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_180_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_scratch_0_181_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_scratch_1_181_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_173_spill.out[1]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_181_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_163163.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_188_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_193_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_194_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_200_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_scratch_0_201_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_scratch_1_201_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_193_spill.out[1]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_201_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_183183.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_208_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_209_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_212_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_scratch_0_213_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_scratch_1_213_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_208_spill.out[1]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_213_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_214_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_214_spill.out[2]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_216_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(ifm_ddr_4.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_217.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_219_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(const_ifm_ddr_3.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_220_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(ifm_ddr_4.out[2]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_219_spill.out[2]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(ifm_ddr_4.out[4]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_223_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_216_spill.out[2]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_225.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_220_spill.out[2]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_222222.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_215_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_230.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_231_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_232_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_233_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_236.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_237_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_237_spill.out[2]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_239_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(ifm_ddr_3.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_240.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_242_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(const_ifm_ddr_2.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_243_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(ifm_ddr_3.out[2]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_242_spill.out[2]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(ifm_ddr_3.out[4]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_246_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_239_spill.out[2]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_248.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_243_spill.out[2]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_245245.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_238_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_253.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_254_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_256.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_257_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_257_spill.out[2]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_259_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_260_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_262_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(const_ifm_ddr_1.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_263_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(ifm_ddr_2.out[1]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_262_spill.out[2]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(ifm_ddr_2.out[3]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_266_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_259_spill.out[1]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_268_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_263_spill.out[2]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_265265.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_258_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_273_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_275.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_276_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_276_spill.out[2]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_278_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(ifm_ddr_1.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_279.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_281_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_281_spill.out[2]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_278_spill.out[2]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_287.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_288_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_277_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_292.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_294.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_297_spill.out[0]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_297_spill.out[2]) = location<dma>(ifm_ddr.out[0]);
+location<dma>(l2l3_1_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_8_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_10_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_12_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_12_spill.out[3]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_13_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_15_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_17_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_1818.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_21_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_25_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_32_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_2424.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_37_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_44_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_3636.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_3434.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_49_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_56_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_4848.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_4646.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_64_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_114_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_121_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_113113.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_134_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_141_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_133133.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_123123.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_154_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_161_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_153153.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_168_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_174_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_173_spill.out[2]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_181_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_163163.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_188_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_194_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_193_spill.out[2]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_201_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_183183.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_209_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_208_spill.out[2]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_213_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_214_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_214_spill.out[3]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_216_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(ifm_ddr_4.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_217.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_219_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(const_ifm_ddr_3.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_220_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(ifm_ddr_4.out[3]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_219_spill.out[3]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(ifm_ddr_4.out[5]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_223_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_216_spill.out[3]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_225.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_220_spill.out[3]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_222222.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_215_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_230.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_231_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_232_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_233_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_236.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_237_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_237_spill.out[3]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_239_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(ifm_ddr_3.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_240.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_242_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(const_ifm_ddr_2.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_243_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(ifm_ddr_3.out[3]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_242_spill.out[3]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(ifm_ddr_3.out[5]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_246_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_239_spill.out[3]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_248.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_243_spill.out[3]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_245245.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_238_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_253.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_254_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_256.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_257_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_257_spill.out[3]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_260_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_262_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(const_ifm_ddr_1.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_263_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(ifm_ddr_2.out[2]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_262_spill.out[3]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(ifm_ddr_2.out[4]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_266_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_268_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_263_spill.out[3]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_265265.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_273_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_275.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_276_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_276_spill.out[3]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_278_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(ifm_ddr_1.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_279.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_281_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_281_spill.out[3]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_278_spill.out[3]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_287.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_288_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_277_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_292.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_294.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_297_spill.out[1]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_297_spill.out[3]) = location<dma>(ifm_ddr.out[1]);
+location<dma>(l2l3_5_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(const_ifm_ddr_4.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_6_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_7_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_9_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_8_spill.out[2]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_11_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_14_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_19_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_59_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_62_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_164_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_167_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_169_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_172_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_184_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_187_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_189_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_192_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_204_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_207_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_5_spill.out[2]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_255_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_280_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(const_ifm_ddr.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_282_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(ifm_ddr_1.out[2]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_283_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(ifm_ddr_1.out[4]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_285_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_282_spill.out[2]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_289_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_284_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_290_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_5_spill.out[4]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_295_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_296_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_298_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_5_spill.out[6]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_300_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_301_spill.out[0]) = location<dma>(const_ifm_ddr_5.out[0]);
+location<dma>(l2l3_5_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(const_ifm_ddr_4.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_6_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_7_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_9_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_8_spill.out[3]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_11_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_14_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_19_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_59_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_62_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_164_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_167_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_169_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_172_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_184_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_187_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_189_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_192_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_204_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_207_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_5_spill.out[3]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_255_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_280_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(const_ifm_ddr.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_282_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(ifm_ddr_1.out[3]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_283_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(ifm_ddr_1.out[5]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_285_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_282_spill.out[3]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_289_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_284_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_290_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_5_spill.out[5]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_295_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_296_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_298_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_5_spill.out[7]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_300_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_301_spill.out[1]) = location<dma>(const_ifm_ddr_5.out[1]);
+location<dma>(l2l3_6_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_7_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_8_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_9_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_10_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_11_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_12_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_13_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_15_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_19_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_20_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_2424.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_24_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_31_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_3434.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_3636.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_36_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_43_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_4646.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_4848.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_48_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_55_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_62_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_63_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_113113.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_113_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_120_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_123123.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_133133.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_133_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_140_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_153153.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_153_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_160_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_163163.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_167_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_168_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_172_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_173_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_180_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_183183.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_187_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_188_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_192_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_193_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_200_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_207_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_208_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_212_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_214_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_217.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_217.in[2]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_219_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_222222.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_225.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_225.in[2]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(ofm_ddr_0_l2l3_229_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_230.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_230.in[2]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_233_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_236.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_236.in[2]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_236.in[4]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_237_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_240.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_240.in[2]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_242_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_245245.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_248.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_248.in[2]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(ofm_ddr_1_l2l3_252_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_253.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_253.in[2]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_256.in[2]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_262_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_265265.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_267_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(ofm_ddr_2_l2l3_272_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_275.in[4]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_279.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_279.in[2]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_281_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_283_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_284_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_287.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_287.in[2]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_289_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_290_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(ofm_ddr_3_l2l3_291_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_292.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_292.in[2]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_296_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_297_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(ofm_ddr_4.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_301_spill.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(ofm_ddr_5.in[0]) = location<dma>(l2l3_1_spill.in[0]);
+location<dma>(l2l3_6_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_7_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_8_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_10_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_12_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_15_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_19_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_20_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_2424.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_24_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_31_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_3434.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_3636.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_36_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_43_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_4646.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_4848.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_48_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_55_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_62_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_63_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_113113.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_113_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_120_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_123123.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_133133.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_133_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_140_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_153153.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_153_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_160_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_163163.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_167_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_168_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_172_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_173_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_180_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_183183.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_187_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_188_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_192_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_193_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_200_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_207_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_208_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_212_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_214_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_217.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_217.in[3]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_219_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_222222.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_225.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_225.in[3]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(ofm_ddr_0_l2l3_229_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_230.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_230.in[3]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_233_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_236.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_236.in[3]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_236.in[5]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_237_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_240.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_240.in[3]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_242_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_245245.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_248.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_248.in[3]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(ofm_ddr_1_l2l3_252_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_253.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_253.in[3]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_256.in[3]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_262_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_265265.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_267_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(ofm_ddr_2_l2l3_272_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_275.in[5]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_279.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_279.in[3]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_281_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_283_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_284_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_287.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_287.in[3]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_290_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(ofm_ddr_3_l2l3_291_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_292.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_292.in[3]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_296_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_297_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(ofm_ddr_4.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_301_spill.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(ofm_ddr_5.in[1]) = location<dma>(l2l3_1_spill.in[1]);
+location<dma>(l2l3_3_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_scratch_0_3_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_4_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_5_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_scratch_0_5_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_9_spill.in[1]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_11_spill.in[1]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_13_spill.in[1]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_14_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_16_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_17_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_scratch_0_17_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_1818.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_21_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_scratch_0_21_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_25_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_32_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_scratch_0_32_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_scratch_1_32_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_37_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_44_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_scratch_0_44_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_scratch_1_44_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_49_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_56_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_scratch_0_56_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_scratch_1_56_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_59_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_64_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_scratch_0_64_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_114_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_121_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_scratch_0_121_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_scratch_1_121_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_134_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_141_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_scratch_0_141_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_scratch_1_141_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_154_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_161_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_scratch_0_161_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_scratch_1_161_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_164_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_169_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_174_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_181_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_scratch_0_181_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_scratch_1_181_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_184_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_189_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_194_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_201_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_scratch_0_201_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_scratch_1_201_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_204_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_209_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_213_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_scratch_0_213_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_scratch_1_213_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_215_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_216_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_220_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_223_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_231_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_232_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_238_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_239_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_243_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_246_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_254_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_255_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_256.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_256.in[4]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_257_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_258_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_259_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_260_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_263_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_266_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_268_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_273_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_275.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_275.in[2]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_276_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_277_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_278_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_280_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_282_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_285_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_288_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_289_spill.in[1]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_294.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(spill_L3_Concat_Buffer_layer_294.in[2]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_295_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_298_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_300_spill.in[0]) = location<dma>(l2l3_2_spill.in[0]);
+location<dma>(l2l3_14_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_16_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(L3_OFM_Buffer_layer_TGSpilling_1818.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_59_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_164_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_169_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_184_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_189_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_204_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_215_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_216_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_220_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_223_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_231_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_232_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_238_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_239_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_243_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_246_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_254_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_255_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_256.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_256.in[5]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_257_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_258_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_259_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_263_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_266_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_275.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_275.in[3]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_276_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_277_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_278_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_280_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_282_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_285_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_288_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_294.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(spill_L3_Concat_Buffer_layer_294.in[3]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_295_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_298_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+location<dma>(l2l3_300_spill.in[1]) = location<dma>(l2l3_2_spill.in[1]);
+//WTS shimtile DMA co-location constraints
+location<dma>(Layer_13_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_14_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_15_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_16_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_18_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_19_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_20_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_22_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_23_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_24_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_27_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_28_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_34_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_35_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_36_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_39_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_40_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_46_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_47_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_48_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_51_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_52_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_58_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_59_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_65_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_70_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_71_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_76_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_81_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_82_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_87_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_92_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_93_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_98_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_103_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_104_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_109_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_116_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_117_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_123_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_124_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_129_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_136_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_137_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_143_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_144_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_149_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_156_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_157_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_163_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_164_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_169_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_176_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_177_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_183_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_184_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_189_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_196_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_197_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_203_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_204_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_211_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_214_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_218_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_226_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_237_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_241_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_249_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_257_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(ifm_ddr_2.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_261_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(l2l3_267_spill.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_269_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(ofm_ddr_2_l2l3_272_spill.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_276_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_280_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_288_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_295_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_296_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_297_wts_ddr.out[0]) = location<dma>(Layer_8_wts_ddr.out[0]);
+location<dma>(Layer_13_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_14_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_15_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_16_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_18_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_19_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_20_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_22_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_23_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_24_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_27_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_28_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_34_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_35_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_36_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_39_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_40_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_46_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_47_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_48_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_51_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_52_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_58_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_59_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_65_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_70_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_71_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_76_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_81_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_82_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_87_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_92_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_93_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_98_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_103_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_104_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_109_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_116_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_117_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_123_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_124_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_129_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_136_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_137_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_143_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_144_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_149_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_156_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_157_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_163_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_164_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_169_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_176_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_177_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_183_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_184_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_189_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_196_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_197_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_203_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_204_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_211_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_214_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_218_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_226_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_237_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_241_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_249_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_257_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_261_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_269_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_276_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_280_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_288_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_295_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_296_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+location<dma>(Layer_297_wts_ddr.out[1]) = location<dma>(Layer_8_wts_ddr.out[1]);
+execution_order({&(l2_1.in[0])}, {&(l2l3_1_spill.out[0])});
+execution_order({&(l2l3_2_spill.in[0])}, {&(l2l3_2_spill.out[0])});
+execution_order({&(l2l3_2_spill.in[0])}, {&(l2l3_scratch_0_3_spill.out[0])});
+execution_order({&(l2l3_3_spill.in[0])}, {&(l2l3_3_spill.out[0])});
+execution_order({&(l2l3_4_spill.in[0])}, {&(l2l3_4_spill.out[0])});
+execution_order({&(l2l3_4_spill.in[0])}, {&(l2l3_scratch_0_5_spill.out[0])});
+execution_order({&(l2l3_5_spill.in[0])}, {&(const_ifm_ddr_5.out[0])});
+execution_order({&(l2_16.in[0])}, {&(l2l3_16_spill.out[0])});
+execution_order({&(l2_16.in[0])}, {&(l2l3_scratch_0_17_spill.out[0])});
+execution_order({&(l2l3_17_spill.in[0])}, {&(l2l3_17_spill.out[0])});
+execution_order({&(l2_20.in[0])}, {&(l2l3_20_spill.out[0])});
+execution_order({&(l2_20.in[0])}, {&(l2l3_scratch_0_21_spill.out[0])});
+execution_order({&(l2l3_21_spill.in[0])}, {&(L3_OFM_Buffer_layer_TGSpilling_1818.out[0])});
+execution_order({&(l2_24.in[0])}, {&(l2l3_24_spill.out[0])});
+execution_order({&(l2l3_25_spill.in[0])}, {&(l2l3_25_spill.out[0])});
+execution_order({&(l2_31.in[0])}, {&(l2l3_31_spill.out[0])});
+execution_order({&(l2_31.in[0])}, {&(l2l3_scratch_0_32_spill.out[0])});
+execution_order({&(l2_31.in[0])}, {&(l2l3_scratch_1_32_spill.out[0])});
+execution_order({&(l2l3_32_spill.in[0])}, {&(L3_OFM_Buffer_layer_TGSpilling_2424.out[0])});
+execution_order({&(l2_36.in[0])}, {&(l2l3_36_spill.out[0])});
+execution_order({&(l2l3_37_spill.in[0])}, {&(l2l3_37_spill.out[0])});
+execution_order({&(l2_43.in[0])}, {&(l2l3_43_spill.out[0])});
+execution_order({&(l2_43.in[0])}, {&(l2l3_scratch_0_44_spill.out[0])});
+execution_order({&(l2_43.in[0])}, {&(l2l3_scratch_1_44_spill.out[0])});
+execution_order({&(l2l3_44_spill.in[0])}, {&(L3_OFM_Buffer_layer_TGSpilling_3636.out[0])});
+execution_order({&(l2_48.in[0])}, {&(l2l3_48_spill.out[0])});
+execution_order({&(l2l3_49_spill.in[0])}, {&(l2l3_49_spill.out[0])});
+execution_order({&(l2_55.in[0])}, {&(l2l3_55_spill.out[0])});
+execution_order({&(l2_55.in[0])}, {&(l2l3_scratch_0_56_spill.out[0])});
+execution_order({&(l2_55.in[0])}, {&(l2l3_scratch_1_56_spill.out[0])});
+execution_order({&(l2l3_56_spill.in[0])}, {&(L3_OFM_Buffer_layer_TGSpilling_4848.out[0])});
+execution_order({&(l2_63.in[0])}, {&(l2l3_63_spill.out[0])});
+execution_order({&(l2_63.in[0])}, {&(l2l3_scratch_0_64_spill.out[0])});
+execution_order({&(l2l3_64_spill.in[0])}, {&(l2l3_64_spill.out[0])});
+execution_order({&(l2_113.in[0])}, {&(l2l3_113_spill.out[0])});
+execution_order({&(l2l3_114_spill.in[0])}, {&(l2l3_114_spill.out[0])});
+execution_order({&(l2_120.in[0])}, {&(l2l3_120_spill.out[0])});
+execution_order({&(l2_120.in[0])}, {&(l2l3_scratch_0_121_spill.out[0])});
+execution_order({&(l2_120.in[0])}, {&(l2l3_scratch_1_121_spill.out[0])});
+execution_order({&(l2l3_121_spill.in[0])}, {&(L3_OFM_Buffer_layer_TGSpilling_113113.out[0])});
+execution_order({&(l2_133.in[0])}, {&(l2l3_133_spill.out[0])});
+execution_order({&(l2l3_134_spill.in[0])}, {&(l2l3_134_spill.out[0])});
+execution_order({&(l2_140.in[0])}, {&(l2l3_140_spill.out[0])});
+execution_order({&(l2_140.in[0])}, {&(l2l3_scratch_0_141_spill.out[0])});
+execution_order({&(l2_140.in[0])}, {&(l2l3_scratch_1_141_spill.out[0])});
+execution_order({&(l2l3_141_spill.in[0])}, {&(L3_OFM_Buffer_layer_TGSpilling_133133.out[0])});
+execution_order({&(l2_153.in[0])}, {&(l2l3_153_spill.out[0])});
+execution_order({&(l2l3_154_spill.in[0])}, {&(l2l3_154_spill.out[0])});
+execution_order({&(l2_160.in[0])}, {&(l2l3_160_spill.out[0])});
+execution_order({&(l2_160.in[0])}, {&(l2l3_scratch_0_161_spill.out[0])});
+execution_order({&(l2_160.in[0])}, {&(l2l3_scratch_1_161_spill.out[0])});
+execution_order({&(l2l3_161_spill.in[0])}, {&(L3_OFM_Buffer_layer_TGSpilling_153153.out[0])});
+execution_order({&(l2_173.in[0])}, {&(l2l3_173_spill.out[0])});
+execution_order({&(l2l3_174_spill.in[0])}, {&(l2l3_174_spill.out[0])});
+execution_order({&(l2_180.in[0])}, {&(l2l3_180_spill.out[0])});
+execution_order({&(l2_180.in[0])}, {&(l2l3_scratch_0_181_spill.out[0])});
+execution_order({&(l2_180.in[0])}, {&(l2l3_scratch_1_181_spill.out[0])});
+execution_order({&(l2l3_181_spill.in[0])}, {&(l2l3_173_spill.out[1])});
+execution_order({&(l2_193.in[0])}, {&(l2l3_193_spill.out[0])});
+execution_order({&(l2l3_194_spill.in[0])}, {&(l2l3_194_spill.out[0])});
+execution_order({&(l2_200.in[0])}, {&(l2l3_200_spill.out[0])});
+execution_order({&(l2_200.in[0])}, {&(l2l3_scratch_0_201_spill.out[0])});
+execution_order({&(l2_200.in[0])}, {&(l2l3_scratch_1_201_spill.out[0])});
+execution_order({&(l2l3_201_spill.in[0])}, {&(l2l3_193_spill.out[1])});
+execution_order({&(l2_208.in[0])}, {&(l2l3_208_spill.out[0])});
+execution_order({&(l2l3_209_spill.in[0])}, {&(l2l3_209_spill.out[0])});
+execution_order({&(l2_212.in[0])}, {&(l2l3_212_spill.out[0])});
+execution_order({&(l2_212.in[0])}, {&(l2l3_scratch_0_213_spill.out[0])});
+execution_order({&(l2_212.in[0])}, {&(l2l3_scratch_1_213_spill.out[0])});
+execution_order({&(l2l3_213_spill.in[0])}, {&(l2l3_213_spill.out[0])});
+execution_order({&(l2_214.in[0])}, {&(l2l3_214_spill.out[0])});
+execution_order({&(l2l3_215_spill.in[0])}, {&(l2l3_214_spill.out[2])});
+execution_order({&(l2l3_216_spill.in[0])}, {&(spill_L3_Concat_Buffer_layer_217.out[0])});
+execution_order({&(l2_219.in[0])}, {&(l2l3_219_spill.out[0])});
+execution_order({&(l2l3_220_spill.in[0])}, {&(l2l3_220_spill.out[0])});
+execution_order({&(l2_222.in[0])}, {&(l2l3_219_spill.out[2])});
+execution_order({&(l2l3_223_spill.in[0])}, {&(ifm_ddr_4.out[4])});
+execution_order({&(l2_229.in[0])}, {&(spill_L3_Concat_Buffer_layer_230.out[0])});
+execution_order({&(l2l3_231_spill.in[0])}, {&(l2l3_231_spill.out[0])});
+execution_order({&(l2l3_232_spill.in[0])}, {&(l2l3_5_spill.out[2])});
+execution_order({&(l2_237.in[0])}, {&(l2l3_237_spill.out[0])});
+execution_order({&(l2l3_238_spill.in[0])}, {&(l2l3_237_spill.out[2])});
+execution_order({&(l2l3_239_spill.in[0])}, {&(spill_L3_Concat_Buffer_layer_240.out[0])});
+execution_order({&(l2_242.in[0])}, {&(l2l3_242_spill.out[0])});
+execution_order({&(l2l3_243_spill.in[0])}, {&(l2l3_243_spill.out[0])});
+execution_order({&(l2_245.in[0])}, {&(l2l3_242_spill.out[2])});
+execution_order({&(l2l3_246_spill.in[0])}, {&(ifm_ddr_3.out[4])});
+execution_order({&(l2_252.in[0])}, {&(spill_L3_Concat_Buffer_layer_253.out[0])});
+execution_order({&(l2l3_254_spill.in[0])}, {&(l2l3_254_spill.out[0])});
+execution_order({&(l2l3_255_spill.in[0])}, {&(spill_L3_Concat_Buffer_layer_256.out[0])});
+execution_order({&(l2_257.in[0])}, {&(l2l3_257_spill.out[0])});
+execution_order({&(l2l3_258_spill.in[0])}, {&(l2l3_257_spill.out[2])});
+execution_order({&(l2l3_259_spill.in[0])}, {&(l2l3_259_spill.out[0])});
+execution_order({&(l2l3_259_spill.in[0])}, {&(ifm_ddr_2.out[0])});
+execution_order({&(l2l3_260_spill.in[0])}, {&(l2l3_260_spill.out[0])});
+execution_order({&(l2_262.in[0])}, {&(l2l3_262_spill.out[0])});
+execution_order({&(l2l3_263_spill.in[0])}, {&(l2l3_263_spill.out[0])});
+execution_order({&(l2_265.in[0])}, {&(l2l3_262_spill.out[2])});
+execution_order({&(l2l3_266_spill.in[0])}, {&(ifm_ddr_2.out[3])});
+execution_order({&(l2_267.in[0])}, {&(l2l3_259_spill.out[1])});
+execution_order({&(l2_267.in[0])}, {&(l2l3_267_spill.out[0])});
+execution_order({&(l2l3_268_spill.in[0])}, {&(l2l3_268_spill.out[0])});
+execution_order({&(l2_272.in[0])}, {&(l2l3_258_spill.out[0])});
+execution_order({&(l2_272.in[0])}, {&(ofm_ddr_2_l2l3_272_spill.out[0])});
+execution_order({&(l2l3_273_spill.in[0])}, {&(l2l3_273_spill.out[0])});
+execution_order({&(spill_L3_Concat_Buffer_layer_275.in[0])}, {&(spill_L3_Concat_Buffer_layer_275.out[0])});
+execution_order({&(l2_276.in[0])}, {&(l2l3_276_spill.out[0])});
+execution_order({&(l2l3_277_spill.in[0])}, {&(l2l3_276_spill.out[2])});
+execution_order({&(l2l3_278_spill.in[0])}, {&(spill_L3_Concat_Buffer_layer_279.out[0])});
+execution_order({&(l2_281.in[0])}, {&(l2l3_281_spill.out[0])});
+execution_order({&(l2l3_282_spill.in[0])}, {&(l2l3_282_spill.out[0])});
+execution_order({&(l2_284.in[0])}, {&(l2l3_281_spill.out[2])});
+execution_order({&(l2l3_285_spill.in[0])}, {&(ifm_ddr_1.out[4])});
+execution_order({&(l2_291.in[0])}, {&(spill_L3_Concat_Buffer_layer_292.out[0])});
+execution_order({&(spill_L3_Concat_Buffer_layer_294.in[0])}, {&(spill_L3_Concat_Buffer_layer_294.out[0])});
+execution_order({&(l2_297.in[0])}, {&(l2l3_297_spill.out[0])});
+execution_order({&(l2l3_298_spill.in[0])}, {&(l2l3_298_spill.out[0])});
+execution_order({&(L2_OFM_Buffer_layer_299.in[0])}, {&(l2l3_297_spill.out[2])});
+execution_order({&(l2l3_300_spill.in[0])}, {&(l2l3_5_spill.out[6])});
+
+//Layer execution ordering constraints
+for(int col = 0; col < 4; col++){
+  for(int row = 0; row < 4; row++){
+    execution_order(flexml_layers[1].compute_node[col][row],flexml_layers[2].compute_node[col][row]);
+    execution_order(flexml_layers[2].compute_node[col][row],flexml_layers[3].compute_node[col][row]);
+    execution_order(flexml_layers[3].compute_node[col][row],flexml_layers[4].compute_node[col][row]);
+    execution_order(flexml_layers[4].compute_node[col][row],flexml_layers[5].compute_node[col][row]);
+    execution_order(flexml_layers[5].compute_node[col][row],flexml_layers[6].compute_node[col][row]);
+    execution_order(flexml_layers[6].compute_node[col][row],flexml_layers[7].compute_node[col][row]);
+    execution_order(flexml_layers[7].compute_node[col][row],flexml_layers[8].compute_node[col][row]);
+    execution_order(flexml_layers[8].compute_node[col][row],flexml_layers[9].compute_node[col][row]);
+    execution_order(flexml_layers[9].compute_node[col][row],flexml_layers[10].compute_node[col][row]);
+    execution_order(flexml_layers[10].compute_node[col][row],flexml_layers[11].compute_node[col][row]);
+    execution_order(flexml_layers[12].compute_node[col][row],flexml_layers[13].compute_node[col][row]);
+    execution_order(flexml_layers[13].compute_node[col][row],flexml_layers[14].compute_node[col][row]);
+    execution_order(flexml_layers[15].compute_node[col][row],flexml_layers[16].compute_node[col][row]);
+    execution_order(flexml_layers[16].compute_node[col][row],flexml_layers[17].compute_node[col][row]);
+    execution_order(flexml_layers[18].compute_node[col][row],flexml_layers[19].compute_node[col][row]);
+    execution_order(flexml_layers[19].compute_node[col][row],flexml_layers[20].compute_node[col][row]);
+    execution_order(flexml_layers[20].compute_node[col][row],flexml_layers[21].compute_node[col][row]);
+    execution_order(flexml_layers[21].compute_node[col][row],flexml_layers[22].compute_node[col][row]);
+    execution_order(flexml_layers[22].compute_node[col][row],flexml_layers[23].compute_node[col][row]);
+    execution_order(flexml_layers[24].compute_node[col][row],flexml_layers[25].compute_node[col][row]);
+    execution_order(flexml_layers[25].compute_node[col][row],flexml_layers[26].compute_node[col][row]);
+    execution_order(flexml_layers[26].compute_node[col][row],flexml_layers[27].compute_node[col][row]);
+    execution_order(flexml_layers[28].compute_node[col][row],flexml_layers[29].compute_node[col][row]);
+    execution_order(flexml_layers[29].compute_node[col][row],flexml_layers[30].compute_node[col][row]);
+    execution_order(flexml_layers[30].compute_node[col][row],flexml_layers[31].compute_node[col][row]);
+    execution_order(flexml_layers[31].compute_node[col][row],flexml_layers[32].compute_node[col][row]);
+    execution_order(flexml_layers[32].compute_node[col][row],flexml_layers[33].compute_node[col][row]);
+    execution_order(flexml_layers[34].compute_node[col][row],flexml_layers[35].compute_node[col][row]);
+    execution_order(flexml_layers[35].compute_node[col][row],flexml_layers[36].compute_node[col][row]);
+    execution_order(flexml_layers[36].compute_node[col][row],flexml_layers[37].compute_node[col][row]);
+    execution_order(flexml_layers[38].compute_node[col][row],flexml_layers[39].compute_node[col][row]);
+    execution_order(flexml_layers[39].compute_node[col][row],flexml_layers[40].compute_node[col][row]);
+    execution_order(flexml_layers[40].compute_node[col][row],flexml_layers[41].compute_node[col][row]);
+    execution_order(flexml_layers[41].compute_node[col][row],flexml_layers[42].compute_node[col][row]);
+    execution_order(flexml_layers[42].compute_node[col][row],flexml_layers[43].compute_node[col][row]);
+    execution_order(flexml_layers[44].compute_node[col][row],flexml_layers[45].compute_node[col][row]);
+    execution_order(flexml_layers[45].compute_node[col][row],flexml_layers[46].compute_node[col][row]);
+    execution_order(flexml_layers[46].compute_node[col][row],flexml_layers[47].compute_node[col][row]);
+    execution_order(flexml_layers[47].compute_node[col][row],flexml_layers[48].compute_node[col][row]);
+    execution_order(flexml_layers[48].compute_node[col][row],flexml_layers[49].compute_node[col][row]);
+    execution_order(flexml_layers[49].compute_node[col][row],flexml_layers[50].compute_node[col][row]);
+    execution_order(flexml_layers[51].compute_node[col][row],flexml_layers[52].compute_node[col][row]);
+    execution_order(flexml_layers[52].compute_node[col][row],flexml_layers[53].compute_node[col][row]);
+    execution_order(flexml_layers[53].compute_node[col][row],flexml_layers[54].compute_node[col][row]);
+    execution_order(flexml_layers[54].compute_node[col][row],flexml_layers[55].compute_node[col][row]);
+    execution_order(flexml_layers[55].compute_node[col][row],flexml_layers[56].compute_node[col][row]);
+    execution_order(flexml_layers[56].compute_node[col][row],flexml_layers[57].compute_node[col][row]);
+    execution_order(flexml_layers[57].compute_node[col][row],flexml_layers[58].compute_node[col][row]);
+    execution_order(flexml_layers[58].compute_node[col][row],flexml_layers[59].compute_node[col][row]);
+    execution_order(flexml_layers[59].compute_node[col][row],flexml_layers[60].compute_node[col][row]);
+    execution_order(flexml_layers[60].compute_node[col][row],flexml_layers[61].compute_node[col][row]);
+    execution_order(flexml_layers[61].compute_node[col][row],flexml_layers[62].compute_node[col][row]);
+    execution_order(flexml_layers[62].compute_node[col][row],flexml_layers[63].compute_node[col][row]);
+    execution_order(flexml_layers[63].compute_node[col][row],flexml_layers[64].compute_node[col][row]);
+    execution_order(flexml_layers[64].compute_node[col][row],flexml_layers[65].compute_node[col][row]);
+    execution_order(flexml_layers[65].compute_node[col][row],flexml_layers[66].compute_node[col][row]);
+    execution_order(flexml_layers[66].compute_node[col][row],flexml_layers[67].compute_node[col][row]);
+    execution_order(flexml_layers[67].compute_node[col][row],flexml_layers[68].compute_node[col][row]);
+    execution_order(flexml_layers[68].compute_node[col][row],flexml_layers[69].compute_node[col][row]);
+    execution_order(flexml_layers[69].compute_node[col][row],flexml_layers[70].compute_node[col][row]);
+    execution_order(flexml_layers[70].compute_node[col][row],flexml_layers[71].compute_node[col][row]);
+    execution_order(flexml_layers[71].compute_node[col][row],flexml_layers[72].compute_node[col][row]);
+    execution_order(flexml_layers[72].compute_node[col][row],flexml_layers[73].compute_node[col][row]);
+    execution_order(flexml_layers[73].compute_node[col][row],flexml_layers[74].compute_node[col][row]);
+    execution_order(flexml_layers[74].compute_node[col][row],flexml_layers[75].compute_node[col][row]);
+    execution_order(flexml_layers[75].compute_node[col][row],flexml_layers[76].compute_node[col][row]);
+    execution_order(flexml_layers[76].compute_node[col][row],flexml_layers[77].compute_node[col][row]);
+    execution_order(flexml_layers[77].compute_node[col][row],flexml_layers[78].compute_node[col][row]);
+    execution_order(flexml_layers[78].compute_node[col][row],flexml_layers[79].compute_node[col][row]);
+    execution_order(flexml_layers[79].compute_node[col][row],flexml_layers[80].compute_node[col][row]);
+    execution_order(flexml_layers[80].compute_node[col][row],flexml_layers[81].compute_node[col][row]);
+    execution_order(flexml_layers[81].compute_node[col][row],flexml_layers[82].compute_node[col][row]);
+    execution_order(flexml_layers[82].compute_node[col][row],flexml_layers[83].compute_node[col][row]);
+    execution_order(flexml_layers[83].compute_node[col][row],flexml_layers[84].compute_node[col][row]);
+    execution_order(flexml_layers[84].compute_node[col][row],flexml_layers[85].compute_node[col][row]);
+    execution_order(flexml_layers[85].compute_node[col][row],flexml_layers[86].compute_node[col][row]);
+    execution_order(flexml_layers[86].compute_node[col][row],flexml_layers[87].compute_node[col][row]);
+    execution_order(flexml_layers[87].compute_node[col][row],flexml_layers[88].compute_node[col][row]);
+    execution_order(flexml_layers[88].compute_node[col][row],flexml_layers[89].compute_node[col][row]);
+    execution_order(flexml_layers[89].compute_node[col][row],flexml_layers[90].compute_node[col][row]);
+    execution_order(flexml_layers[90].compute_node[col][row],flexml_layers[91].compute_node[col][row]);
+    execution_order(flexml_layers[91].compute_node[col][row],flexml_layers[92].compute_node[col][row]);
+    execution_order(flexml_layers[92].compute_node[col][row],flexml_layers[93].compute_node[col][row]);
+    execution_order(flexml_layers[93].compute_node[col][row],flexml_layers[94].compute_node[col][row]);
+    execution_order(flexml_layers[94].compute_node[col][row],flexml_layers[95].compute_node[col][row]);
+    execution_order(flexml_layers[95].compute_node[col][row],flexml_layers[96].compute_node[col][row]);
+    execution_order(flexml_layers[96].compute_node[col][row],flexml_layers[97].compute_node[col][row]);
+    execution_order(flexml_layers[97].compute_node[col][row],flexml_layers[98].compute_node[col][row]);
+    execution_order(flexml_layers[98].compute_node[col][row],flexml_layers[99].compute_node[col][row]);
+    execution_order(flexml_layers[100].compute_node[col][row],flexml_layers[101].compute_node[col][row]);
+    execution_order(flexml_layers[101].compute_node[col][row],flexml_layers[102].compute_node[col][row]);
+    execution_order(flexml_layers[102].compute_node[col][row],flexml_layers[103].compute_node[col][row]);
+    execution_order(flexml_layers[103].compute_node[col][row],flexml_layers[104].compute_node[col][row]);
+    execution_order(flexml_layers[104].compute_node[col][row],flexml_layers[105].compute_node[col][row]);
+    execution_order(flexml_layers[106].compute_node[col][row],flexml_layers[107].compute_node[col][row]);
+    execution_order(flexml_layers[107].compute_node[col][row],flexml_layers[108].compute_node[col][row]);
+    execution_order(flexml_layers[108].compute_node[col][row],flexml_layers[109].compute_node[col][row]);
+    execution_order(flexml_layers[109].compute_node[col][row],flexml_layers[110].compute_node[col][row]);
+    execution_order(flexml_layers[110].compute_node[col][row],flexml_layers[111].compute_node[col][row]);
+    execution_order(flexml_layers[111].compute_node[col][row],flexml_layers[112].compute_node[col][row]);
+    execution_order(flexml_layers[112].compute_node[col][row],flexml_layers[113].compute_node[col][row]);
+    execution_order(flexml_layers[113].compute_node[col][row],flexml_layers[114].compute_node[col][row]);
+    execution_order(flexml_layers[114].compute_node[col][row],flexml_layers[115].compute_node[col][row]);
+    execution_order(flexml_layers[115].compute_node[col][row],flexml_layers[116].compute_node[col][row]);
+    execution_order(flexml_layers[116].compute_node[col][row],flexml_layers[117].compute_node[col][row]);
+    execution_order(flexml_layers[118].compute_node[col][row],flexml_layers[119].compute_node[col][row]);
+    execution_order(flexml_layers[119].compute_node[col][row],flexml_layers[120].compute_node[col][row]);
+    execution_order(flexml_layers[120].compute_node[col][row],flexml_layers[121].compute_node[col][row]);
+    execution_order(flexml_layers[121].compute_node[col][row],flexml_layers[122].compute_node[col][row]);
+    execution_order(flexml_layers[122].compute_node[col][row],flexml_layers[123].compute_node[col][row]);
+    execution_order(flexml_layers[124].compute_node[col][row],flexml_layers[125].compute_node[col][row]);
+    execution_order(flexml_layers[125].compute_node[col][row],flexml_layers[126].compute_node[col][row]);
+    execution_order(flexml_layers[126].compute_node[col][row],flexml_layers[127].compute_node[col][row]);
+    execution_order(flexml_layers[127].compute_node[col][row],flexml_layers[128].compute_node[col][row]);
+    execution_order(flexml_layers[128].compute_node[col][row],flexml_layers[129].compute_node[col][row]);
+    execution_order(flexml_layers[129].compute_node[col][row],flexml_layers[130].compute_node[col][row]);
+    execution_order(flexml_layers[130].compute_node[col][row],flexml_layers[131].compute_node[col][row]);
+    execution_order(flexml_layers[131].compute_node[col][row],flexml_layers[132].compute_node[col][row]);
+    execution_order(flexml_layers[132].compute_node[col][row],flexml_layers[133].compute_node[col][row]);
+    execution_order(flexml_layers[133].compute_node[col][row],flexml_layers[134].compute_node[col][row]);
+    execution_order(flexml_layers[134].compute_node[col][row],flexml_layers[135].compute_node[col][row]);
+    execution_order(flexml_layers[136].compute_node[col][row],flexml_layers[137].compute_node[col][row]);
+    execution_order(flexml_layers[137].compute_node[col][row],flexml_layers[138].compute_node[col][row]);
+    execution_order(flexml_layers[138].compute_node[col][row],flexml_layers[139].compute_node[col][row]);
+    execution_order(flexml_layers[139].compute_node[col][row],flexml_layers[140].compute_node[col][row]);
+    execution_order(flexml_layers[140].compute_node[col][row],flexml_layers[141].compute_node[col][row]);
+    execution_order(flexml_layers[142].compute_node[col][row],flexml_layers[143].compute_node[col][row]);
+    execution_order(flexml_layers[143].compute_node[col][row],flexml_layers[144].compute_node[col][row]);
+    execution_order(flexml_layers[144].compute_node[col][row],flexml_layers[145].compute_node[col][row]);
+    execution_order(flexml_layers[145].compute_node[col][row],flexml_layers[146].compute_node[col][row]);
+    execution_order(flexml_layers[146].compute_node[col][row],flexml_layers[147].compute_node[col][row]);
+    execution_order(flexml_layers[147].compute_node[col][row],flexml_layers[148].compute_node[col][row]);
+    execution_order(flexml_layers[148].compute_node[col][row],flexml_layers[149].compute_node[col][row]);
+    execution_order(flexml_layers[149].compute_node[col][row],flexml_layers[150].compute_node[col][row]);
+    execution_order(flexml_layers[150].compute_node[col][row],flexml_layers[151].compute_node[col][row]);
+    execution_order(flexml_layers[151].compute_node[col][row],flexml_layers[152].compute_node[col][row]);
+    execution_order(flexml_layers[152].compute_node[col][row],flexml_layers[153].compute_node[col][row]);
+    execution_order(flexml_layers[154].compute_node[col][row],flexml_layers[155].compute_node[col][row]);
+    execution_order(flexml_layers[155].compute_node[col][row],flexml_layers[156].compute_node[col][row]);
+    execution_order(flexml_layers[156].compute_node[col][row],flexml_layers[157].compute_node[col][row]);
+    execution_order(flexml_layers[157].compute_node[col][row],flexml_layers[158].compute_node[col][row]);
+    execution_order(flexml_layers[158].compute_node[col][row],flexml_layers[159].compute_node[col][row]);
+    execution_order(flexml_layers[160].compute_node[col][row],flexml_layers[161].compute_node[col][row]);
+    execution_order(flexml_layers[161].compute_node[col][row],flexml_layers[162].compute_node[col][row]);
+    execution_order(flexml_layers[162].compute_node[col][row],flexml_layers[163].compute_node[col][row]);
+    execution_order(flexml_layers[163].compute_node[col][row],flexml_layers[164].compute_node[col][row]);
+    execution_order(flexml_layers[164].compute_node[col][row],flexml_layers[165].compute_node[col][row]);
+    execution_order(flexml_layers[165].compute_node[col][row],flexml_layers[166].compute_node[col][row]);
+    execution_order(flexml_layers[166].compute_node[col][row],flexml_layers[167].compute_node[col][row]);
+    execution_order(flexml_layers[167].compute_node[col][row],flexml_layers[168].compute_node[col][row]);
+    execution_order(flexml_layers[168].compute_node[col][row],flexml_layers[169].compute_node[col][row]);
+    execution_order(flexml_layers[169].compute_node[col][row],flexml_layers[170].compute_node[col][row]);
+    execution_order(flexml_layers[170].compute_node[col][row],flexml_layers[171].compute_node[col][row]);
+    execution_order(flexml_layers[172].compute_node[col][row],flexml_layers[173].compute_node[col][row]);
+    execution_order(flexml_layers[173].compute_node[col][row],flexml_layers[174].compute_node[col][row]);
+    execution_order(flexml_layers[174].compute_node[col][row],flexml_layers[175].compute_node[col][row]);
+    execution_order(flexml_layers[175].compute_node[col][row],flexml_layers[176].compute_node[col][row]);
+    execution_order(flexml_layers[176].compute_node[col][row],flexml_layers[177].compute_node[col][row]);
+    execution_order(flexml_layers[178].compute_node[col][row],flexml_layers[179].compute_node[col][row]);
+    execution_order(flexml_layers[179].compute_node[col][row],flexml_layers[180].compute_node[col][row]);
+    execution_order(flexml_layers[180].compute_node[col][row],flexml_layers[181].compute_node[col][row]);
+    execution_order(flexml_layers[181].compute_node[col][row],flexml_layers[182].compute_node[col][row]);
+    execution_order(flexml_layers[182].compute_node[col][row],flexml_layers[183].compute_node[col][row]);
+    execution_order(flexml_layers[183].compute_node[col][row],flexml_layers[184].compute_node[col][row]);
+    execution_order(flexml_layers[185].compute_node[col][row],flexml_layers[186].compute_node[col][row]);
+    execution_order(flexml_layers[186].compute_node[col][row],flexml_layers[187].compute_node[col][row]);
+    execution_order(flexml_layers[189].compute_node[col][row],flexml_layers[190].compute_node[col][row]);
+    execution_order(flexml_layers[191].compute_node[col][row],flexml_layers[192].compute_node[col][row]);
+    execution_order(flexml_layers[193].compute_node[col][row],flexml_layers[194].compute_node[col][row]);
+    execution_order(flexml_layers[194].compute_node[col][row],flexml_layers[195].compute_node[col][row]);
+    execution_order(flexml_layers[195].compute_node[col][row],flexml_layers[196].compute_node[col][row]);
+    execution_order(flexml_layers[196].compute_node[col][row],flexml_layers[197].compute_node[col][row]);
+    execution_order(flexml_layers[198].compute_node[col][row],flexml_layers[199].compute_node[col][row]);
+    execution_order(flexml_layers[199].compute_node[col][row],flexml_layers[200].compute_node[col][row]);
+    execution_order(flexml_layers[200].compute_node[col][row],flexml_layers[201].compute_node[col][row]);
+    execution_order(flexml_layers[202].compute_node[col][row],flexml_layers[203].compute_node[col][row]);
+    execution_order(flexml_layers[204].compute_node[col][row],flexml_layers[205].compute_node[col][row]);
+    execution_order(flexml_layers[206].compute_node[col][row],flexml_layers[207].compute_node[col][row]);
+    execution_order(flexml_layers[207].compute_node[col][row],flexml_layers[208].compute_node[col][row]);
+    execution_order(flexml_layers[208].compute_node[col][row],flexml_layers[209].compute_node[col][row]);
+    execution_order(flexml_layers[209].compute_node[col][row],flexml_layers[210].compute_node[col][row]);
+    execution_order(flexml_layers[212].compute_node[col][row],flexml_layers[213].compute_node[col][row]);
+    execution_order(flexml_layers[214].compute_node[col][row],flexml_layers[215].compute_node[col][row]);
+    execution_order(flexml_layers[217].compute_node[col][row],flexml_layers[218].compute_node[col][row]);
+    execution_order(flexml_layers[218].compute_node[col][row],flexml_layers[219].compute_node[col][row]);
+    execution_order(flexml_layers[219].compute_node[col][row],flexml_layers[220].compute_node[col][row]);
+    execution_order(flexml_layers[222].compute_node[col][row],flexml_layers[223].compute_node[col][row]);
+    execution_order(flexml_layers[224].compute_node[col][row],flexml_layers[225].compute_node[col][row]);
+    execution_order(flexml_layers[226].compute_node[col][row],flexml_layers[227].compute_node[col][row]);
+    execution_order(flexml_layers[227].compute_node[col][row],flexml_layers[228].compute_node[col][row]);
+    execution_order(flexml_layers[228].compute_node[col][row],flexml_layers[229].compute_node[col][row]);
+    execution_order(flexml_layers[229].compute_node[col][row],flexml_layers[230].compute_node[col][row]);
+    execution_order(flexml_layers[231].compute_node[col][row],flexml_layers[232].compute_node[col][row]);
+    execution_order(flexml_layers[232].compute_node[col][row],flexml_layers[233].compute_node[col][row]);
+    execution_order(flexml_layers[235].compute_node[col][row],flexml_layers[236].compute_node[col][row]);
+  }
+}
+
+//TG spilling execution ordering constraints
+execution_order({&(L3_OFM_Buffer_layer_TGSpilling_1818.in[0])}, {&(l2l3_20_spill.out[0])});
+
+//TG spilling execution ordering constraints
+execution_order({&(L3_OFM_Buffer_layer_TGSpilling_2424.in[0])}, {&(l2l3_24_spill.out[0])});
+
+//TG spilling execution ordering constraints
+execution_order({&(L3_OFM_Buffer_layer_TGSpilling_3434.in[0])}, {&(l2l3_36_spill.out[0])});
+
+//TG spilling execution ordering constraints
+execution_order({&(L3_OFM_Buffer_layer_TGSpilling_3636.in[0])}, {&(l2l3_36_spill.out[0])});
+
+//TG spilling execution ordering constraints
+execution_order({&(L3_OFM_Buffer_layer_TGSpilling_4646.in[0])}, {&(l2l3_48_spill.out[0])});
+
+//TG spilling execution ordering constraints
+execution_order({&(L3_OFM_Buffer_layer_TGSpilling_4848.in[0])}, {&(l2l3_48_spill.out[0])});
+
+//TG spilling execution ordering constraints
+execution_order({&(L3_OFM_Buffer_layer_TGSpilling_113113.in[0])}, {&(l2l3_113_spill.out[0])});
+
+//TG spilling execution ordering constraints
+execution_order({&(L3_OFM_Buffer_layer_TGSpilling_123123.in[0])}, {&(l2l3_133_spill.out[0])});
+
+//TG spilling execution ordering constraints
+execution_order({&(L3_OFM_Buffer_layer_TGSpilling_133133.in[0])}, {&(l2l3_133_spill.out[0])});
+
+//TG spilling execution ordering constraints
+execution_order({&(L3_OFM_Buffer_layer_TGSpilling_153153.in[0])}, {&(l2l3_153_spill.out[0])});
+
+//TG spilling execution ordering constraints
+execution_order({&(L3_OFM_Buffer_layer_TGSpilling_163163.in[0])}, {&(l2l3_173_spill.out[0])});
+
+//TG spilling execution ordering constraints
+execution_order({&(L3_OFM_Buffer_layer_TGSpilling_183183.in[0])}, {&(l2l3_193_spill.out[0])});
+
+//TG spilling execution ordering constraints
+execution_order({&(L3_OFM_Buffer_layer_TGSpilling_222222.in[0])}, {&(l2l3_219_spill.out[2])});
+
+//TG spilling execution ordering constraints
+execution_order({&(L3_OFM_Buffer_layer_TGSpilling_245245.in[0])}, {&(l2l3_242_spill.out[2])});
+
+//TG spilling execution ordering constraints
+execution_order({&(L3_OFM_Buffer_layer_TGSpilling_265265.in[0])}, {&(l2l3_262_spill.out[2])});
+
+} //end of constructor
+}; //end of class;
diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/rtp.json b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/rtp.json
new file mode 100644
index 0000000000000000000000000000000000000000..fc870f264b64931bbb5213554d0097d3829359ed
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/rtp.json
@@ -0,0 +1,18016 @@
+{
+  "__VERSION__": 1,
+  "Div_2": {
+    "MulAttributeBroadcastingBf16": {
+      "000": {
+        "datatype": "uint32",
+        "index": 0,
+        "name": "ifmsv_size",
+        "value": 1920
+      },
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+        "index": 4,
+        "name": "ifm_shift",
+        "value": 0
+      },
+      "005": {
+        "datatype": "uint8",
+        "index": 5,
+        "name": "ifm_shift_biased",
+        "value": 0
+      },
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+        "datatype": "int8",
+        "index": 6,
+        "name": "scalar_shift",
+        "value": 0
+      },
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+        "index": 7,
+        "name": "scalar_shift_biased",
+        "value": 0
+      },
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+        "datatype": "int8",
+        "index": 8,
+        "name": "ofm_shift",
+        "value": 0
+      },
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+        "datatype": "int8",
+        "index": 9,
+        "name": "ofm_shift_biased",
+        "value": 0
+      },
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+        "datatype": "uint16",
+        "index": 10,
+        "name": "num_kernel_iters",
+        "value": 8
+      },
+      "012": {
+        "datatype": "uint8",
+        "index": 12,
+        "name": "scalar_position",
+        "value": 1
+      },
+      "014": {
+        "datatype": "bfloat16",
+        "index": 14,
+        "name": "scalar",
+        "value": 15232
+      }
+    },
+    "layer_order": 1
+  },
+  "Sub_14": {
+    "AddBf16": {
+      "000": {
+        "datatype": "uint32",
+        "index": 0,
+        "name": "ifmsv_size",
+        "value": 640
+      },
+      "004": {
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+        "name": "ifm1_shift",
+        "value": 0
+      },
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+        "name": "ifm1_shift_biased",
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+      },
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+        "name": "ifm2_shift",
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+      },
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+        "name": "ifm2_shift_biased",
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+      },
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+      },
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+        "name": "num_kernel_iters",
+        "value": 180
+      },
+      "013": {
+        "datatype": "uint8",
+        "index": 13,
+        "name": "act",
+        "value": 0
+      }
+    },
+    "layer_order": 6
+  },
+  "Div_16": {
+    "MulBf16": {
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+        "datatype": "uint32",
+        "index": 0,
+        "name": "ifmsv_size",
+        "value": 640
+      },
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+        "name": "ifm1_shift",
+        "value": 0
+      },
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+        "index": 10,
+        "name": "num_kernel_iters",
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+      }
+    },
+    "layer_order": 7
+  },
+  "Conv_17": {
+    "Conv2DBf16": {
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+        "index": 0,
+        "name": "ifm_sv_width",
+        "value": 66
+      },
+      "001": {
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+        "index": 1,
+        "name": "ifm_sv_height",
+        "value": 10
+      },
+      "002": {
+        "datatype": "uint16",
+        "index": 2,
+        "name": "ifm_sv_depth",
+        "value": 8
+      },
+      "004": {
+        "datatype": "uint16",
+        "index": 4,
+        "name": "ofm_sv_depth",
+        "value": 8
+      },
+      "006": {
+        "datatype": "uint8",
+        "index": 6,
+        "name": "ksize.width",
+        "value": 3
+      },
+      "007": {
+        "datatype": "uint8",
+        "index": 7,
+        "name": "ksize.height",
+        "value": 3
+      },
+      "008": {
+        "datatype": "uint8",
+        "index": 8,
+        "name": "out_mode",
+        "value": 0
+      },
+      "009": {
+        "datatype": "uint4",
+        "index": 9,
+        "name": "stride_log2.stride_log2_width",
+        "value": 1
+      },
+      "010": {
+        "datatype": "uint8",
+        "index": 10,
+        "name": "psum_buff_offset_scaled",
+        "value": 2
+      },
+      "011": {
+        "datatype": "uint8",
+        "index": 11,
+        "name": "num_ifm_depth_iters",
+        "value": 1
+      },
+      "012": {
+        "datatype": "bfloat16",
+        "index": 12,
+        "name": "lrelu_alpha_kernel",
+        "value": 16256
+      },
+      "014": {
+        "datatype": "uint8",
+        "index": 14,
+        "name": "ofm_width_pad",
+        "value": 0
+      },
+      "015": {
+        "datatype": "uint8",
+        "index": 15,
+        "name": "act",
+        "value": 0
+      },
+      "016": {
+        "datatype": "uint8",
+        "index": 16,
+        "name": "conv_type",
+        "value": 64
+      },
+      "017": {
+        "datatype": "uint4",
+        "index": 17,
+        "name": "ofm_offset_packed.left",
+        "value": 0
+      },
+      "018": {
+        "datatype": "uint16",
+        "index": 18,
+        "name": "num_ifm_width_iters",
+        "value": 5
+      },
+      "020": {
+        "datatype": "uint16",
+        "index": 20,
+        "name": "num_ifm_height_iters",
+        "value": 6
+      },
+      "022": {
+        "datatype": "uint16",
+        "index": 22,
+        "name": "num_ofm_depth_iters",
+        "value": 1
+      }
+    },
+    "layer_order": 8
+  },
+  "Add_19": {
+    "AddAttributeBroadcastingBf16": {
+      "000": {
+        "datatype": "uint32",
+        "index": 0,
+        "name": "ifmsv_size",
+        "value": 1472
+      },
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+        "value": 0
+      },
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+        "index": 5,
+        "name": "ifm_shift_biased",
+        "value": 0
+      },
+      "006": {
+        "datatype": "int8",
+        "index": 6,
+        "name": "scalar_shift",
+        "value": 0
+      },
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+        "name": "scalar_shift_biased",
+        "value": 0
+      },
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+        "name": "ofm_shift",
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+      },
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+        "name": "ofm_shift_biased",
+        "value": 0
+      },
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+        "index": 10,
+        "name": "num_kernel_iters",
+        "value": 20
+      },
+      "012": {
+        "datatype": "uint8",
+        "index": 12,
+        "name": "scalar_position",
+        "value": 1
+      },
+      "014": {
+        "datatype": "bfloat16",
+        "index": 14,
+        "name": "scalar",
+        "value": 16448
+      }
+    },
+    "layer_order": 9
+  },
+  "Clip_22": {
+    "ClipBf16": {
+      "000": {
+        "datatype": "uint32",
+        "index": 0,
+        "name": "ifmsv_size",
+        "value": 1920
+      },
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+        "name": "ifm_shift",
+        "value": 0
+      },
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+        "name": "num_kernel_iters",
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+      },
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+        "index": 32,
+        "name": "clamp_min",
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+      },
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+        "datatype": "bfloat16",
+        "index": 36,
+        "name": "clamp_max",
+        "value": 16576
+      }
+    },
+    "layer_order": 10
+  },
+  "Div_24": {
+    "MulAttributeBroadcastingBf16": {
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+      },
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+        "name": "num_kernel_iters",
+        "value": 20
+      },
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+        "name": "scalar_position",
+        "value": 1
+      },
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+        "name": "scalar",
+        "value": 15914
+      }
+    },
+    "layer_order": 11
+  },
+  "Mul_25": {
+    "MulBf16": {
+      "000": {
+        "datatype": "uint32",
+        "index": 0,
+        "name": "ifmsv_size",
+        "value": 1024
+      },
+      "004": {
+        "datatype": "int8",
+        "index": 4,
+        "name": "ifm1_shift",
+        "value": 0
+      },
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+        "datatype": "uint8",
+        "index": 5,
+        "name": "ifm1_shift_biased",
+        "value": 0
+      },
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+        "datatype": "int8",
+        "index": 6,
+        "name": "ifm2_shift",
+        "value": 0
+      },
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+        "name": "ifm2_shift_biased",
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+      },
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+      },
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+        "name": "ofm_shift_biased",
+        "value": 0
+      },
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+        "index": 10,
+        "name": "num_kernel_iters",
+        "value": 30
+      }
+    },
+    "layer_order": 12
+  },
+  "Conv_26": {
+    "DepthwiseConv2dBf16": {
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+        "datatype": "uint8",
+        "index": 0,
+        "name": "ifm_sv_width",
+        "value": 18
+      },
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+        "index": 1,
+        "name": "ifm_sv_height",
+        "value": 8
+      },
+      "002": {
+        "datatype": "uint8",
+        "index": 2,
+        "name": "ifm_sv_depth",
+        "value": 8
+      },
+      "003": {
+        "datatype": "uint8",
+        "index": 3,
+        "name": "stride",
+        "value": 1
+      },
+      "004": {
+        "datatype": "uint8",
+        "index": 4,
+        "name": "kernel_height",
+        "value": 3
+      },
+      "005": {
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+        "index": 5,
+        "name": "kernel_width",
+        "value": 3
+      },
+      "006": {
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+        "index": 6,
+        "name": "act",
+        "value": 1
+      },
+      "008": {
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+        "index": 8,
+        "name": "ifmsv_size",
+        "value": 1280
+      },
+      "012": {
+        "datatype": "uint32",
+        "index": 12,
+        "name": "ofm_len",
+        "value": 40
+      }
+    },
+    "layer_order": 13
+  },
+  "Conv_28": {
+    "AddBf16": {
+      "032": {
+        "datatype": "uint32",
+        "index": 0,
+        "name": "ifmsv_size",
+        "value": 512
+      },
+      "036": {
+        "datatype": "int8",
+        "index": 4,
+        "name": "ifm1_shift",
+        "value": 0
+      },
+      "037": {
+        "datatype": "uint8",
+        "index": 5,
+        "name": "ifm1_shift_biased",
+        "value": 0
+      },
+      "038": {
+        "datatype": "int8",
+        "index": 6,
+        "name": "ifm2_shift",
+        "value": 0
+      },
+      "039": {
+        "datatype": "uint8",
+        "index": 7,
+        "name": "ifm2_shift_biased",
+        "value": 0
+      },
+      "040": {
+        "datatype": "int8",
+        "index": 8,
+        "name": "ofm_shift",
+        "value": 0
+      },
+      "041": {
+        "datatype": "int8",
+        "index": 9,
+        "name": "ofm_shift_biased",
+        "value": 0
+      },
+      "042": {
+        "datatype": "uint16",
+        "index": 10,
+        "name": "num_kernel_iters",
+        "value": 60
+      },
+      "045": {
+        "datatype": "uint8",
+        "index": 13,
+        "name": "act",
+        "value": 0
+      }
+    },
+    "Conv2DBf16": {
+      "000": {
+        "datatype": "uint8",
+        "index": 0,
+        "name": "ifm_sv_width",
+        "value": 32
+      },
+      "001": {
+        "datatype": "uint8",
+        "index": 1,
+        "name": "ifm_sv_height",
+        "value": 2
+      },
+      "002": {
+        "datatype": "uint16",
+        "index": 2,
+        "name": "ifm_sv_depth",
+        "value": 64
+      },
+      "004": {
+        "datatype": "uint16",
+        "index": 4,
+        "name": "ofm_sv_depth",
+        "value": 8
+      },
+      "006": {
+        "datatype": "uint8",
+        "index": 6,
+        "name": "ksize.width",
+        "value": 1
+      },
+      "007": {
+        "datatype": "uint8",
+        "index": 7,
+        "name": "ksize.height",
+        "value": 1
+      },
+      "008": {
+        "datatype": "uint8",
+        "index": 8,
+        "name": "out_mode",
+        "value": 0
+      },
+      "009": {
+        "datatype": "uint4",
+        "index": 9,
+        "name": "stride_log2.stride_log2_width",
+        "value": 0
+      },
+      "010": {
+        "datatype": "uint8",
+        "index": 10,
+        "name": "psum_buff_offset_scaled",
+        "value": 2
+      },
+      "011": {
+        "datatype": "uint8",
+        "index": 11,
+        "name": "num_ifm_depth_iters",
+        "value": 1
+      },
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+        "name": "ksize.width",
+        "value": 3
+      },
+      "007": {
+        "datatype": "uint8",
+        "index": 7,
+        "name": "ksize.height",
+        "value": 3
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+      "008": {
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+        "index": 8,
+        "name": "out_mode",
+        "value": 0
+      },
+      "009": {
+        "datatype": "uint4",
+        "index": 9,
+        "name": "stride_log2.stride_log2_width",
+        "value": 0
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+      "010": {
+        "datatype": "uint8",
+        "index": 10,
+        "name": "psum_buff_offset_scaled",
+        "value": 2
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+      "011": {
+        "datatype": "uint8",
+        "index": 11,
+        "name": "num_ifm_depth_iters",
+        "value": 2
+      },
+      "012": {
+        "datatype": "bfloat16",
+        "index": 12,
+        "name": "lrelu_alpha_kernel",
+        "value": 16256
+      },
+      "014": {
+        "datatype": "uint8",
+        "index": 14,
+        "name": "ofm_width_pad",
+        "value": 0
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+      "015": {
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+        "index": 15,
+        "name": "act",
+        "value": 0
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+        "name": "conv_type",
+        "value": 64
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+        "index": 17,
+        "name": "ofm_offset_packed.left",
+        "value": 0
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+      "018": {
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+        "index": 18,
+        "name": "num_ifm_width_iters",
+        "value": 5
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+      "020": {
+        "datatype": "uint16",
+        "index": 20,
+        "name": "num_ifm_height_iters",
+        "value": 6
+      },
+      "022": {
+        "datatype": "uint16",
+        "index": 22,
+        "name": "num_ofm_depth_iters",
+        "value": 1
+      }
+    },
+    "layer_order": 288
+  },
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+    "TanhTemplatedBf16": {
+      "000": {
+        "datatype": "uint32",
+        "index": 0,
+        "name": "ifmsv_size",
+        "value": 1472
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+        "value": 0
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+        "name": "ofm_shift",
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+      "008": {
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+        "index": 8,
+        "name": "num_kernel_iters",
+        "value": 20
+      }
+    },
+    "layer_order": 289
+  },
+  "Mul_433": {
+    "MulBf16": {
+      "000": {
+        "datatype": "uint32",
+        "index": 0,
+        "name": "ifmsv_size",
+        "value": 1024
+      },
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+      },
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+        "value": 0
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+        "index": 8,
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+        "index": 10,
+        "name": "num_kernel_iters",
+        "value": 30
+      }
+    },
+    "layer_order": 290
+  },
+  "Add_434": {
+    "AddBf16": {
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+        "name": "ifmsv_size",
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+        "name": "num_kernel_iters",
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+        "index": 13,
+        "name": "act",
+        "value": 0
+      }
+    },
+    "layer_order": 291
+  },
+  "Conv_439": {
+    "Conv2DBf16": {
+      "000": {
+        "datatype": "uint8",
+        "index": 0,
+        "name": "ifm_sv_width",
+        "value": 66
+      },
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+        "index": 1,
+        "name": "ifm_sv_height",
+        "value": 6
+      },
+      "002": {
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+        "index": 2,
+        "name": "ifm_sv_depth",
+        "value": 8
+      },
+      "004": {
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+        "index": 4,
+        "name": "ofm_sv_depth",
+        "value": 8
+      },
+      "006": {
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+        "index": 6,
+        "name": "ksize.width",
+        "value": 3
+      },
+      "007": {
+        "datatype": "uint8",
+        "index": 7,
+        "name": "ksize.height",
+        "value": 3
+      },
+      "008": {
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+        "index": 8,
+        "name": "out_mode",
+        "value": 0
+      },
+      "009": {
+        "datatype": "uint4",
+        "index": 9,
+        "name": "stride_log2.stride_log2_width",
+        "value": 0
+      },
+      "010": {
+        "datatype": "uint8",
+        "index": 10,
+        "name": "psum_buff_offset_scaled",
+        "value": 4
+      },
+      "011": {
+        "datatype": "uint8",
+        "index": 11,
+        "name": "num_ifm_depth_iters",
+        "value": 5
+      },
+      "012": {
+        "datatype": "bfloat16",
+        "index": 12,
+        "name": "lrelu_alpha_kernel",
+        "value": 0
+      },
+      "014": {
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+        "index": 14,
+        "name": "ofm_width_pad",
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+      },
+      "015": {
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+        "name": "act",
+        "value": 1
+      },
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+        "name": "conv_type",
+        "value": 64
+      },
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+        "index": 17,
+        "name": "ofm_offset_packed.left",
+        "value": 0
+      },
+      "018": {
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+        "index": 18,
+        "name": "num_ifm_width_iters",
+        "value": 5
+      },
+      "020": {
+        "datatype": "uint16",
+        "index": 20,
+        "name": "num_ifm_height_iters",
+        "value": 12
+      },
+      "022": {
+        "datatype": "uint16",
+        "index": 22,
+        "name": "num_ofm_depth_iters",
+        "value": 1
+      }
+    },
+    "layer_order": 295
+  },
+  "Conv_441": {
+    "Conv2DBf16": {
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+        "name": "ifm_sv_width",
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+      },
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+        "name": "ifm_sv_height",
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+      },
+      "002": {
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+        "index": 2,
+        "name": "ifm_sv_depth",
+        "value": 16
+      },
+      "004": {
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+        "index": 4,
+        "name": "ofm_sv_depth",
+        "value": 8
+      },
+      "006": {
+        "datatype": "uint8",
+        "index": 6,
+        "name": "ksize.width",
+        "value": 3
+      },
+      "007": {
+        "datatype": "uint8",
+        "index": 7,
+        "name": "ksize.height",
+        "value": 3
+      },
+      "008": {
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+        "name": "out_mode",
+        "value": 0
+      },
+      "009": {
+        "datatype": "uint4",
+        "index": 9,
+        "name": "stride_log2.stride_log2_width",
+        "value": 0
+      },
+      "010": {
+        "datatype": "uint8",
+        "index": 10,
+        "name": "psum_buff_offset_scaled",
+        "value": 2
+      },
+      "011": {
+        "datatype": "uint8",
+        "index": 11,
+        "name": "num_ifm_depth_iters",
+        "value": 1
+      },
+      "012": {
+        "datatype": "bfloat16",
+        "index": 12,
+        "name": "lrelu_alpha_kernel",
+        "value": 0
+      },
+      "014": {
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+        "index": 14,
+        "name": "ofm_width_pad",
+        "value": 0
+      },
+      "015": {
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+        "index": 15,
+        "name": "act",
+        "value": 1
+      },
+      "016": {
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+        "index": 16,
+        "name": "conv_type",
+        "value": 64
+      },
+      "017": {
+        "datatype": "uint4",
+        "index": 17,
+        "name": "ofm_offset_packed.left",
+        "value": 0
+      },
+      "018": {
+        "datatype": "uint16",
+        "index": 18,
+        "name": "num_ifm_width_iters",
+        "value": 10
+      },
+      "020": {
+        "datatype": "uint16",
+        "index": 20,
+        "name": "num_ifm_height_iters",
+        "value": 9
+      },
+      "022": {
+        "datatype": "uint16",
+        "index": 22,
+        "name": "num_ofm_depth_iters",
+        "value": 1
+      }
+    },
+    "layer_order": 296
+  },
+  "Conv_443": {
+    "Conv2DBf16": {
+      "000": {
+        "datatype": "uint8",
+        "index": 0,
+        "name": "ifm_sv_width",
+        "value": 64
+      },
+      "001": {
+        "datatype": "uint8",
+        "index": 1,
+        "name": "ifm_sv_height",
+        "value": 1
+      },
+      "002": {
+        "datatype": "uint16",
+        "index": 2,
+        "name": "ifm_sv_depth",
+        "value": 64
+      },
+      "004": {
+        "datatype": "uint16",
+        "index": 4,
+        "name": "ofm_sv_depth",
+        "value": 8
+      },
+      "006": {
+        "datatype": "uint8",
+        "index": 6,
+        "name": "ksize.width",
+        "value": 1
+      },
+      "007": {
+        "datatype": "uint8",
+        "index": 7,
+        "name": "ksize.height",
+        "value": 1
+      },
+      "008": {
+        "datatype": "uint8",
+        "index": 8,
+        "name": "out_mode",
+        "value": 0
+      },
+      "009": {
+        "datatype": "uint4",
+        "index": 9,
+        "name": "stride_log2.stride_log2_width",
+        "value": 0
+      },
+      "010": {
+        "datatype": "uint8",
+        "index": 10,
+        "name": "psum_buff_offset_scaled",
+        "value": 4
+      },
+      "011": {
+        "datatype": "uint8",
+        "index": 11,
+        "name": "num_ifm_depth_iters",
+        "value": 1
+      },
+      "012": {
+        "datatype": "bfloat16",
+        "index": 12,
+        "name": "lrelu_alpha_kernel",
+        "value": 16256
+      },
+      "014": {
+        "datatype": "uint8",
+        "index": 14,
+        "name": "ofm_width_pad",
+        "value": 0
+      },
+      "015": {
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+        "index": 15,
+        "name": "act",
+        "value": 0
+      },
+      "016": {
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+        "index": 16,
+        "name": "conv_type",
+        "value": 64
+      },
+      "017": {
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+        "index": 17,
+        "name": "ofm_offset_packed.left",
+        "value": 0
+      },
+      "018": {
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+        "index": 18,
+        "name": "num_ifm_width_iters",
+        "value": 5
+      },
+      "020": {
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+        "index": 20,
+        "name": "num_ifm_height_iters",
+        "value": 45
+      },
+      "022": {
+        "datatype": "uint16",
+        "index": 22,
+        "name": "num_ofm_depth_iters",
+        "value": 1
+      }
+    },
+    "layer_order": 297
+  },
+  "Clip_447": {
+    "ClipBf16": {
+      "000": {
+        "datatype": "uint32",
+        "index": 0,
+        "name": "ifmsv_size",
+        "value": 1600
+      },
+      "004": {
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+        "name": "ifm_shift",
+        "value": 0
+      },
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+        "name": "ifm_shift_biased",
+        "value": 0
+      },
+      "006": {
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+        "index": 6,
+        "name": "ofm_shift",
+        "value": 0
+      },
+      "007": {
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+        "name": "ofm_shift_biased",
+        "value": 0
+      },
+      "008": {
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+        "index": 8,
+        "name": "num_kernel_iters",
+        "value": 72
+      },
+      "032": {
+        "datatype": "bfloat16",
+        "index": 32,
+        "name": "clamp_min",
+        "value": 0
+      },
+      "036": {
+        "datatype": "bfloat16",
+        "index": 36,
+        "name": "clamp_max",
+        "value": 16256
+      }
+    },
+    "layer_order": 299
+  },
+  "Add_445": {
+    "AddBf16": {
+      "000": {
+        "datatype": "uint32",
+        "index": 0,
+        "name": "ifmsv_size",
+        "value": 640
+      },
+      "004": {
+        "datatype": "int8",
+        "index": 4,
+        "name": "ifm1_shift",
+        "value": 0
+      },
+      "005": {
+        "datatype": "uint8",
+        "index": 5,
+        "name": "ifm1_shift_biased",
+        "value": 0
+      },
+      "006": {
+        "datatype": "int8",
+        "index": 6,
+        "name": "ifm2_shift",
+        "value": 0
+      },
+      "007": {
+        "datatype": "uint8",
+        "index": 7,
+        "name": "ifm2_shift_biased",
+        "value": 0
+      },
+      "008": {
+        "datatype": "int8",
+        "index": 8,
+        "name": "ofm_shift",
+        "value": 0
+      },
+      "009": {
+        "datatype": "int8",
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+        "name": "ofm_shift_biased",
+        "value": 0
+      },
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+        "index": 10,
+        "name": "num_kernel_iters",
+        "value": 180
+      },
+      "013": {
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+        "index": 13,
+        "name": "act",
+        "value": 0
+      }
+    },
+    "layer_order": 301
+  },
+  "Clip_446": {
+    "ClipBf16": {
+      "000": {
+        "datatype": "uint32",
+        "index": 0,
+        "name": "ifmsv_size",
+        "value": 1600
+      },
+      "004": {
+        "datatype": "int8",
+        "index": 4,
+        "name": "ifm_shift",
+        "value": 0
+      },
+      "005": {
+        "datatype": "uint8",
+        "index": 5,
+        "name": "ifm_shift_biased",
+        "value": 0
+      },
+      "006": {
+        "datatype": "int8",
+        "index": 6,
+        "name": "ofm_shift",
+        "value": 0
+      },
+      "007": {
+        "datatype": "uint8",
+        "index": 7,
+        "name": "ofm_shift_biased",
+        "value": 0
+      },
+      "008": {
+        "datatype": "uint16",
+        "index": 8,
+        "name": "num_kernel_iters",
+        "value": 72
+      },
+      "032": {
+        "datatype": "bfloat16",
+        "index": 32,
+        "name": "clamp_min",
+        "value": 0
+      },
+      "036": {
+        "datatype": "bfloat16",
+        "index": 36,
+        "name": "clamp_max",
+        "value": 16256
+      }
+    },
+    "layer_order": 302
+  }
+}
diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/superkernels.cpp b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/superkernels.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..e20a6ad5d2d1331dcaa33c052379e907d0f49a2b
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/superkernels.cpp
@@ -0,0 +1,651 @@
+#include "superkernels.h"
+#include "mllib_kernels.h"
+
+add1d_attribute_broadcasting<bfloat16,bfloat16,bfloat16>::params_t add1d_attribute_broadcasting_params;
+
+clip1d<bfloat16>::params_t clip1d_params;
+
+mul1d_attribute_broadcasting<bfloat16,bfloat16,bfloat16>::params_t mul1d_attribute_broadcasting_params;
+
+sigmoid1d<bfloat16,0>::params_t sigmoid1d_params;
+
+tanh1d<bfloat16,0>::params_t tanh1d_params;
+
+add1d<bfloat16,bfloat16,bfloat16,LINEAR>::params_t add1d_params;
+
+mul1d<bfloat16,bfloat16,bfloat16>::params_t mul1d_params;
+
+sub1d<bfloat16,bfloat16,bfloat16>::params_t sub1d_params;
+
+reduce_mean_c8<bfloat16,bfloat16>::params_t reduce_mean_c8_params;
+
+conv2d_bf16_params_t conv2d_params;
+maxpool2d_internal_params maxpool2d_params; 
+pad2d_bf16_params_t pad2d_params;
+conv2d_dw_bf16_params_t conv2d_dw_params;
+avgpool2d_internal_params<DTYPE_IFM> avgpool2d_params;
+
+
+// start of pad2d bf16 chained with maxpool variables
+static int num_depth_iter = 0;
+static int num_height_iter = 0;
+static int num_width_iter = 0;
+static int curr_height_iter = -1;
+static int curr_width_iter = -1;
+// End of pad2d bf16 chained with maxpool variables
+
+static int num_iter = 1;
+static int depth_iter = 0;
+static int curr_iter = 0;
+static int total_iters = 0;
+
+static int pad_top = 0;
+static int pad_bot = 0;
+static int pad_left = 0;
+static int pad_right = 0;
+
+static int core_id = 0;
+static uint32_t core_col = 0;
+static uint32_t core_row = 0;
+static uint32_t ifmsv_size = 0;
+// EltUnary & EltBinary variables
+static uint32_t ifm1_offset = 0;
+static uint32_t ifm2_offset = 0;
+
+static int height_iter = 0;
+static int width_iter = 0;
+static int reduce_axis = 0;
+// reduction op variables
+static int l3_width = 0;
+static int l3_height = 0;
+static int l3_depth = 0;
+pad_3d_params_t pad_3d_params;
+
+#define SK_NODE_INIT \
+    tile::current().set_saturation(saturation_mode::saturate); \
+    tile::current().set_rounding(rounding_mode::conv_even);
+
+void conv2d_maxpool
+(
+adf::input_buffer_conf<DTYPE_IFM, BPCTYPE_IFM>  & __restrict ifm,
+adf::input_buffer_conf<DTYPE_WTS, BPCTYPE_WTS>  & __restrict wts,
+const uint32_t (&layer_params)[LP_SIZE_SKGEN],
+adf::output_buffer_conf<DTYPE_OFM, BPCTYPE_OFM> & __restrict ofm
+){
+
+  core_id = get_coreid();
+  core_col = core_id >> 16 & 0x03;
+
+  if (curr_iter == 0) {
+    SK_NODE_INIT;
+    setup_conv2d_bf16_params</*enable_och_gran_8=*/true>(layer_params, conv2d_params, BATCH_SIZE);
+
+#ifdef CONVBF16_MAXPOOL_CHAIN
+    setup_maxpool2d_params(((bfloat16 *)layer_params) + LAYER_OFFSET/2, maxpool2d_params, BATCH_SIZE);
+    setup_pad2d_params((bfloat16 *)layer_params + PAD2D_OFFSET/2, pad2d_params, BATCH_SIZE);
+#endif
+    num_depth_iter = conv2d_params.num_ifm_depth_iters;
+    int num_iter_out = conv2d_params.num_ifm_width_iters * conv2d_params.num_ifm_height_iters * conv2d_params.num_ofm_depth_iters;
+    num_iter = num_iter_out * conv2d_params.num_ifm_depth_iters;
+
+#ifdef CONVBF16_MAXPOOL_CHAIN
+    pad_top = pad2d_params.pad_top;
+    pad_bot = pad2d_params.pad_bot;
+    pad_left = pad2d_params.pad_left;
+    pad_right = pad2d_params.pad_right;
+
+    if (pad_top & pad_left) {
+      pad2d_params.pad_top = (core_col == 0) ? 1 : 0;
+    } else if (pad_bot & pad_right) {
+      pad2d_params.enable_bottom_padding = (core_col == (4 - 1)) ? 1 : 0;
+    }
+#endif
+
+  }
+
+  depth_iter++;
+  curr_iter++;
+  total_iters++;
+
+  if (depth_iter == 1)
+    ofm.acquire();
+
+  conv2d_bf16<BATCH_SIZE, ACT_TYPE, DTYPE_IFM, DTYPE_WTS, DTYPE_OFM, BPCTYPE_IFM, BPCTYPE_WTS, BPCTYPE_OFM,
+              /*enable_psum_float=*/false, /*enable_FC=*/false, /*enable_och_gran_8=*/true>
+  (ifm, wts, ofm, conv2d_params);
+
+  if (depth_iter == num_depth_iter) {
+#ifdef CONVBF16_MAXPOOL_CHAIN
+    if (maxpool2d_params.nifms > 0) {
+      if (pad2d_params.en_pad) {
+        pad2d<BATCH_SIZE, DTYPE_OFM, BPCTYPE_OFM, BPCTYPE_OFM>((adf::input_buffer_conf<DTYPE_OFM, BPCTYPE_OFM> &)ofm, ofm, pad2d_params);
+      }
+      maxpool2d<BATCH_SIZE, DTYPE_OFM, BPCTYPE_OFM, BPCTYPE_OFM>((adf::input_buffer_conf<DTYPE_OFM, BPCTYPE_OFM> &)ofm, ofm, maxpool2d_params);
+
+      if (pad2d_params.en_pad) {
+	if (pad_top & pad_left) {
+	  pad2d_params.pad_top = 0;
+	} else if (pad_bot & pad_right) {
+          pad2d_params.enable_bottom_padding = false;
+        }
+      }
+
+    }
+#endif
+    ofm.release();
+    depth_iter = 0; // Reset depth_iter
+  }
+
+  if (curr_iter == num_iter) {
+    curr_iter = 0; // Reset curr_iter
+  }
+}
+void superkernel_add1d_attribute_broadcasting(
+	adf::input_buffer_conf<bfloat16, bpc_sync_0d> & __restrict ifm,
+	const uint32_t (&layer_params)[LP_SIZE_SKGEN],
+	adf::output_buffer_conf<bfloat16, bpc_async_0d> & __restrict ofm
+) {
+  core_id = get_coreid();
+  core_row = (core_id & 0xff) - 2;
+  core_col = core_id >> 16 & 0x03;
+
+  if (curr_iter == 0) {
+    SK_NODE_INIT;
+    // setup runtime parameters
+    add1d_attribute_broadcasting<bfloat16,bfloat16,bfloat16>::setup(add1d_attribute_broadcasting_params, layer_params);
+    // number of temporal iterations
+    num_iter = add1d_attribute_broadcasting_params.num_kernel_iters;
+    // for full-broadcast/superset handling
+    ifm1_offset = core_row * add1d_attribute_broadcasting_params.ifmsv_size;
+  }
+
+  ofm.acquire();
+  ++curr_iter;
+  bfloat16* ifm1_ptr = (bfloat16*)ifm.data() + ifm1_offset;
+
+  add1d_attribute_broadcasting<bfloat16,bfloat16,bfloat16>::run(ifm1_ptr, ofm.data(), add1d_attribute_broadcasting_params);
+  ofm.release();
+  if (curr_iter == num_iter) {
+    curr_iter = 0;
+  }
+}
+void superkernel_clip1d(
+	adf::input_buffer_conf<bfloat16, bpc_sync_0d> & __restrict ifm,
+	const uint32_t (&layer_params)[LP_SIZE_SKGEN],
+	adf::output_buffer_conf<bfloat16, bpc_async_0d> & __restrict ofm
+) {
+  core_id = get_coreid();
+  core_row = (core_id & 0xff) - 2;
+  core_col = core_id >> 16 & 0x03;
+
+  if (curr_iter == 0) {
+    SK_NODE_INIT;
+    // setup runtime parameters
+    clip1d<bfloat16>::setup(clip1d_params, layer_params);
+    // number of temporal iterations
+    num_iter = clip1d_params.num_kernel_iters;
+    // for full-broadcast/superset handling
+    ifm1_offset = core_row * clip1d_params.ifmsv_size;
+  }
+
+  ofm.acquire();
+  ++curr_iter;
+  bfloat16* ifm1_ptr = (bfloat16*)ifm.data() + ifm1_offset;
+
+  clip1d<bfloat16>::run(ifm1_ptr, ofm.data(), clip1d_params);
+  ofm.release();
+  if (curr_iter == num_iter) {
+    curr_iter = 0;
+  }
+}
+void superkernel_mul1d_attribute_broadcasting(
+	adf::input_buffer_conf<bfloat16, bpc_sync_0d> & __restrict ifm,
+	const uint32_t (&layer_params)[LP_SIZE_SKGEN],
+	adf::output_buffer_conf<bfloat16, bpc_async_0d> & __restrict ofm
+) {
+  core_id = get_coreid();
+  core_row = (core_id & 0xff) - 2;
+  core_col = core_id >> 16 & 0x03;
+
+  if (curr_iter == 0) {
+    SK_NODE_INIT;
+    // setup runtime parameters
+    mul1d_attribute_broadcasting<bfloat16,bfloat16,bfloat16>::setup(mul1d_attribute_broadcasting_params, layer_params);
+    // number of temporal iterations
+    num_iter = mul1d_attribute_broadcasting_params.num_kernel_iters;
+    // for full-broadcast/superset handling
+    ifm1_offset = core_row * mul1d_attribute_broadcasting_params.ifmsv_size;
+  }
+
+  ofm.acquire();
+  ++curr_iter;
+  bfloat16* ifm1_ptr = (bfloat16*)ifm.data() + ifm1_offset;
+
+  mul1d_attribute_broadcasting<bfloat16,bfloat16,bfloat16>::run(ifm1_ptr, ofm.data(), mul1d_attribute_broadcasting_params);
+  ofm.release();
+  if (curr_iter == num_iter) {
+    curr_iter = 0;
+  }
+}
+void superkernel_sigmoid1d(
+	adf::input_buffer_conf<bfloat16, bpc_sync_0d> & __restrict ifm,
+	const uint32_t (&layer_params)[LP_SIZE_SKGEN],
+	adf::output_buffer_conf<bfloat16, bpc_async_0d> & __restrict ofm
+) {
+  core_id = get_coreid();
+  core_row = (core_id & 0xff) - 2;
+  core_col = core_id >> 16 & 0x03;
+
+  if (curr_iter == 0) {
+    SK_NODE_INIT;
+    // setup runtime parameters
+    sigmoid1d<bfloat16,0>::setup(sigmoid1d_params, layer_params);
+    // number of temporal iterations
+    num_iter = sigmoid1d_params.num_kernel_iters;
+    // for full-broadcast/superset handling
+    ifm1_offset = core_row * sigmoid1d_params.ifmsv_size;
+  }
+
+  ofm.acquire();
+  ++curr_iter;
+  bfloat16* ifm1_ptr = (bfloat16*)ifm.data() + ifm1_offset;
+
+  sigmoid1d<bfloat16,0>::run(ifm1_ptr, ofm.data(), sigmoid1d_params);
+  ofm.release();
+  if (curr_iter == num_iter) {
+    curr_iter = 0;
+  }
+}
+void superkernel_tanh1d(
+	adf::input_buffer_conf<bfloat16, bpc_sync_0d> & __restrict ifm,
+	const uint32_t (&layer_params)[LP_SIZE_SKGEN],
+	adf::output_buffer_conf<bfloat16, bpc_async_0d> & __restrict ofm
+) {
+  core_id = get_coreid();
+  core_row = (core_id & 0xff) - 2;
+  core_col = core_id >> 16 & 0x03;
+
+  if (curr_iter == 0) {
+    SK_NODE_INIT;
+    // setup runtime parameters
+    tanh1d<bfloat16,0>::setup(tanh1d_params, layer_params);
+    // number of temporal iterations
+    num_iter = tanh1d_params.num_kernel_iters;
+    // for full-broadcast/superset handling
+    ifm1_offset = core_row * tanh1d_params.ifmsv_size;
+  }
+
+  ofm.acquire();
+  ++curr_iter;
+  bfloat16* ifm1_ptr = (bfloat16*)ifm.data() + ifm1_offset;
+
+  tanh1d<bfloat16,0>::run(ifm1_ptr, ofm.data(), tanh1d_params);
+  ofm.release();
+  if (curr_iter == num_iter) {
+    curr_iter = 0;
+  }
+}
+
+void superkernel_avgpool
+(
+adf::input_buffer_conf<DTYPE_IFM, BPCTYPE_IFM>  & __restrict ifm,
+const uint32_t (&layer_params)[LP_SIZE_SKGEN],
+adf::output_buffer_conf<DTYPE_OFM, BPCTYPE_OFM> & __restrict ofm
+){
+
+    core_id = get_coreid();
+    core_row = (core_id & 0xff) - 2;
+    core_col = core_id >> 16 & 0x03;
+    if (curr_iter == 0) {
+        SK_NODE_INIT;
+      setup_avgpool2d_params<DTYPE_IFM>((DTYPE_IFM *)layer_params + LAYER_OFFSET/2, avgpool2d_params, BATCH_SIZE);
+      num_iter = avgpool2d_params.ofm_len;
+      ifmsv_size = *((uint16_t *)layer_params + 25);
+    }
+
+    ofm.acquire();
+    curr_iter++;
+    int offset = core_row * ifmsv_size ;
+
+    DTYPE_IFM* temp_ifm = (DTYPE_IFM *) ifm.data() + offset;
+    adf::_io_buffer_ml< DTYPE_IFM, adf::direction::in, adf::io_buffer_config< adf::extents<4294967295u>, adf::locking::sync, adf::addressing::linear, adf::margin<0>>> ifm_new = {temp_ifm, ifmsv_size, 0, 0};
+          avgpool2d<BATCH_SIZE, DTYPE_AVG_OFM, BPCTYPE_OFM, BPCTYPE_OFM>((adf::input_buffer_conf<DTYPE_AVG_OFM, BPCTYPE_OFM> &)ifm_new, ofm, avgpool2d_params);
+    ofm.release();
+
+    if (curr_iter == num_iter) {
+      curr_iter = 0;
+      curr_width_iter = -1;
+      curr_height_iter = -1;
+      //dummy for avgpool
+      pad_top = 0;
+      pad_bot = 0;
+      pad_left = 0;
+      pad_right = 0;
+    }
+    
+}
+void superkernel_add1d(
+	adf::input_buffer_conf<bfloat16, bpc_sync_0d> & __restrict ifm1,
+	const uint32_t (&layer_params)[LP_SIZE_SKGEN],
+	adf::input_buffer_conf<bfloat16, bpc_async_0d> & __restrict ifm2,
+	adf::output_buffer_conf<bfloat16, bpc_async_0d> & __restrict ofm
+)  {
+  core_id = get_coreid();
+  core_row = (core_id & 0xff) - 2;
+  core_col = core_id >> 16 & 0x03;
+
+  if (curr_iter == 0) {
+    SK_NODE_INIT;
+    // setup runtime parameters
+    add1d<bfloat16,bfloat16,bfloat16,LINEAR>::setup(add1d_params, layer_params);
+    // number of temporal iterations
+    num_iter = add1d_params.num_kernel_iters;
+    // for full-broadcast/superset handling
+    ifm1_offset = core_row * add1d_params.ifmsv_size;
+    ifm2_offset = core_row * add1d_params.ifmsv_size;
+  }
+
+  ++curr_iter;
+
+  ofm.acquire();
+  ifm2.acquire();
+
+  bfloat16* ifm1_ptr = (bfloat16*)ifm1.data() + ifm1_offset;
+  bfloat16* ifm2_ptr = (bfloat16*)ifm2.data() + ifm2_offset;
+
+  add1d<bfloat16,bfloat16,bfloat16,LINEAR>::run(ifm1_ptr, ifm2_ptr, ofm.data(), add1d_params);
+  ifm2.release();
+  ofm.release();
+
+  if (curr_iter == num_iter) {
+    curr_iter = 0;
+  }
+}
+void superkernel_mul1d(
+	adf::input_buffer_conf<bfloat16, bpc_sync_0d> & __restrict ifm1,
+	const uint32_t (&layer_params)[LP_SIZE_SKGEN],
+	adf::input_buffer_conf<bfloat16, bpc_async_0d> & __restrict ifm2,
+	adf::output_buffer_conf<bfloat16, bpc_async_0d> & __restrict ofm
+)  {
+  core_id = get_coreid();
+  core_row = (core_id & 0xff) - 2;
+  core_col = core_id >> 16 & 0x03;
+
+  if (curr_iter == 0) {
+    SK_NODE_INIT;
+    // setup runtime parameters
+    mul1d<bfloat16,bfloat16,bfloat16>::setup(mul1d_params, layer_params);
+    // number of temporal iterations
+    num_iter = mul1d_params.num_kernel_iters;
+    // for full-broadcast/superset handling
+    ifm1_offset = core_row * mul1d_params.ifmsv_size;
+    ifm2_offset = core_row * mul1d_params.ifmsv_size;
+  }
+
+  ++curr_iter;
+
+  ofm.acquire();
+  ifm2.acquire();
+
+  bfloat16* ifm1_ptr = (bfloat16*)ifm1.data() + ifm1_offset;
+  bfloat16* ifm2_ptr = (bfloat16*)ifm2.data() + ifm2_offset;
+
+  mul1d<bfloat16,bfloat16,bfloat16>::run(ifm1_ptr, ifm2_ptr, ofm.data(), mul1d_params);
+  ifm2.release();
+  ofm.release();
+
+  if (curr_iter == num_iter) {
+    curr_iter = 0;
+  }
+}
+void superkernel_sub1d(
+	adf::input_buffer_conf<bfloat16, bpc_sync_0d> & __restrict ifm1,
+	const uint32_t (&layer_params)[LP_SIZE_SKGEN],
+	adf::input_buffer_conf<bfloat16, bpc_async_0d> & __restrict ifm2,
+	adf::output_buffer_conf<bfloat16, bpc_async_0d> & __restrict ofm
+)  {
+  core_id = get_coreid();
+  core_row = (core_id & 0xff) - 2;
+  core_col = core_id >> 16 & 0x03;
+
+  if (curr_iter == 0) {
+    SK_NODE_INIT;
+    // setup runtime parameters
+    sub1d<bfloat16,bfloat16,bfloat16>::setup(sub1d_params, layer_params);
+    // number of temporal iterations
+    num_iter = sub1d_params.num_kernel_iters;
+    // for full-broadcast/superset handling
+    ifm1_offset = core_row * sub1d_params.ifmsv_size;
+    ifm2_offset = core_row * sub1d_params.ifmsv_size;
+  }
+
+  ++curr_iter;
+
+  ofm.acquire();
+  ifm2.acquire();
+
+  bfloat16* ifm1_ptr = (bfloat16*)ifm1.data() + ifm1_offset;
+  bfloat16* ifm2_ptr = (bfloat16*)ifm2.data() + ifm2_offset;
+
+  sub1d<bfloat16,bfloat16,bfloat16>::run(ifm1_ptr, ifm2_ptr, ofm.data(), sub1d_params);
+  ifm2.release();
+  ofm.release();
+
+  if (curr_iter == num_iter) {
+    curr_iter = 0;
+  }
+}
+void superkernel_conv2d_dwc
+(
+adf::input_buffer_conf<DTYPE_IFM, BPCTYPE_IFM>  & __restrict ifm,
+adf::input_buffer_conf<DTYPE_WTS, BPCTYPE_WTS>  & __restrict wts,
+const uint32_t (&layer_params)[LP_SIZE_SKGEN],
+adf::output_buffer_conf<DTYPE_OFM, BPCTYPE_OFM> & __restrict ofm
+){
+  core_id = get_coreid();
+  core_row = (core_id & 0xff) - 2;
+  core_col = core_id >> 16 & 0x03;
+
+  if (curr_iter == 0) {
+    SK_NODE_INIT;
+    setup_conv2d_dw_params_bf16(layer_params, conv2d_dw_params, 1);
+    ifmsv_size = *((uint16_t *)layer_params + 4);  // 25 th index
+    num_iter = *((uint16_t *)layer_params + 6);
+  }
+  ofm.acquire();
+  curr_iter++;
+  int offset = core_row * ifmsv_size ;
+
+  bfloat16* temp_ifm = (bfloat16 *) ifm.data() + offset;
+  adf::_io_buffer_ml< bfloat16, adf::direction::in, adf::io_buffer_config< adf::extents<4294967295u>, adf::locking::sync, adf::addressing::linear, adf::margin<0>>> ifm_new = {temp_ifm, ifmsv_size, 0, 0};
+  conv2d_dw<1, bfloat16, bfloat16,  bfloat16,adf::bpc_sync_0d, adf::bpc_sync_0d, adf::bpc_async_0d>((adf::input_buffer_conf<bfloat16, adf::bpc_sync_0d>&)ifm_new, wts, ofm, conv2d_dw_params);
+  ofm.release();
+
+  if (curr_iter == num_iter) {
+      curr_iter = 0;
+  }
+}
+void superkernel_reduce_mean_c8(
+	adf::input_buffer_conf<bfloat16, bpc_sync_0d> & __restrict ifm,
+	const uint32_t (&layer_params)[LP_SIZE_SKGEN],
+	adf::output_buffer_conf<bfloat16, bpc_async_0d> & __restrict ofm
+) {
+  core_id = get_coreid();
+  core_row = (core_id & 0xff) - 2;
+  core_col = core_id >> 16 & 0x03;
+
+  if (curr_iter == 0) {
+    SK_NODE_INIT;
+    // setup runtime parameters
+    reduce_mean_c8<bfloat16,bfloat16>::setup(reduce_mean_c8_params, layer_params);
+    ifm1_offset = core_row * reduce_mean_c8_params.sv_height * reduce_mean_c8_params.sv_channel * reduce_mean_c8_params.sv_width;
+    reduce_axis = reduce_mean_c8_params.reduce_axis;
+    num_iter = *(((uint32_t *)layer_params) + 10);
+
+#ifdef PAD3D_FOR_REDUCEOP
+    // setting up padding params
+    pad_3d_params.height = pad_3d_params.width = pad_3d_params.depth = 0;
+    pad_3d_params.pad_width_start = pad_3d_params.pad_width_end = 0;
+    pad_3d_params.pad_height_start = pad_3d_params.pad_height_end = 0;
+    pad_3d_params.pad_channel_start = pad_3d_params.pad_channel_end = 0;
+    pad_3d_params.bf16_constant_value = *(((uint32_t *)layer_params) + 14);
+    pad_3d_params.int8_constant_value = 0;
+
+    pad_3d_params.height = reduce_mean_c8_params.sv_height;
+    pad_3d_params.width = reduce_mean_c8_params.sv_width;
+    pad_3d_params.depth = reduce_mean_c8_params.sv_channel;
+
+    l3_width = *(((uint32_t *)layer_params) + 11);
+    l3_height = *(((uint32_t *)layer_params) + 12);
+    l3_depth = *(((uint32_t *)layer_params) + 13);
+#endif
+
+  }
+
+  if ((reduce_axis == 1) && (depth_iter  % reduce_mean_c8_params.loop_width == 0)) {
+    ofm.acquire();
+  }
+  if ((reduce_axis == 2) && (width_iter  % reduce_mean_c8_params.loop_width == 0)) {
+    ofm.acquire();
+  }
+  if ((reduce_axis == 4) && (height_iter  % reduce_mean_c8_params.loop_width == 0)) {
+    ofm.acquire();
+  }
+  ++curr_iter;
+
+  bfloat16* ifm1_ptr = (bfloat16*)ifm.data() + ifm1_offset;
+
+#ifdef PAD3D_FOR_REDUCEOP
+  bool is_pad_call_req = false;
+
+  // padding in width dimension
+  if (reduce_axis == 2) {
+    uint32_t curr_width = width_iter * reduce_mean_c8_params.sv_width;
+    uint32_t sv_valid_width = (curr_width < l3_width) ? ((curr_width + reduce_mean_c8_params.sv_width) < l3_width ? reduce_mean_c8_params.sv_width : (l3_width - curr_width)) : 0;
+    pad_3d_params.pad_width_end = reduce_mean_c8_params.sv_width - sv_valid_width;
+    if (pad_3d_params.pad_width_end > 0)
+      is_pad_call_req = true;
+  }
+
+  // padding in height dimension
+  if (reduce_axis == 4) {
+    uint32_t curr_height = height_iter * reduce_mean_c8_params.sv_height;
+    uint32_t sv_valid_height = (curr_height < l3_height) ? ((curr_height + reduce_mean_c8_params.sv_height) < l3_height ? reduce_mean_c8_params.sv_height : (l3_height - curr_height)) : 0;
+    pad_3d_params.pad_height_end = reduce_mean_c8_params.sv_height - sv_valid_height;
+    if (pad_3d_params.pad_height_end > 0)
+      is_pad_call_req = true;
+  }
+
+  // padding in depth dimension
+  if (reduce_axis == 1) {
+    uint32_t curr_depth = depth_iter * reduce_mean_c8_params.sv_channel;
+    uint32_t sv_valid_depth = (curr_depth < l3_depth) ? ((curr_depth + reduce_mean_c8_params.sv_channel) < l3_depth ? reduce_mean_c8_params.sv_channel : (l3_depth - curr_depth)) : 0;
+    pad_3d_params.pad_channel_end = reduce_mean_c8_params.sv_channel - sv_valid_depth;
+    if (pad_3d_params.pad_channel_end > 0)
+      is_pad_call_req = true;
+  }
+  if (is_pad_call_req)
+    pad_3d<CONSTANT,bfloat16, bpc_async_0d, bpc_async_0d, 1>((adf::input_buffer_conf<bfloat16, bpc_async_0d> &)ifm1_ptr, (adf::output_buffer_conf<bfloat16, bpc_async_0d> &)ifm1_ptr,pad_3d_params);
+
+#endif
+
+  reduce_mean_c8<bfloat16,bfloat16>::run(ifm1_ptr, ofm.data(), reduce_mean_c8_params);
+
+  if ((reduce_axis == 1) && (++depth_iter  % reduce_mean_c8_params.loop_width == 0)) {
+    depth_iter = 0;
+    ofm.release();
+  }
+  if ((reduce_axis == 2) && (++width_iter  % reduce_mean_c8_params.loop_width == 0)) {
+    width_iter = 0;
+    ofm.release();
+  }
+  if ((reduce_axis == 4) && (++height_iter  % reduce_mean_c8_params.loop_width == 0)) {
+    height_iter = 0;
+    ofm.release();
+  }
+  if (curr_iter == num_iter) {
+    curr_iter = 0;
+  }
+}
+
+void superkernel_conv_eltbinary
+(
+  adf::input_buffer_conf<DTYPE_IFM, BPCTYPE_IFM>  & __restrict ifm1,
+  adf::input_buffer_conf<DTYPE_WTS, BPCTYPE_WTS>  & __restrict wts,
+  adf::input_buffer_conf<DTYPE_IFM, BPCTYPE_IFM2> & __restrict ifm2,
+  const uint32_t (&layer_params)[LP_SIZE_CONV_ELTBINARY_SKGEN],
+  adf::output_buffer_conf<DTYPE_OFM, BPCTYPE_OFM> & __restrict ofm
+){
+  core_id = get_coreid();
+  core_row = (core_id & 0xff) - 2;
+  core_col = core_id >> 16 & 0x03;
+
+  if (curr_iter == 0) {
+    SK_NODE_INIT;
+    unsigned elt_ifmsv_size = 0;
+    // setup runtime parameters for conv
+    setup_conv2d_bf16_params</*enable_och_gran_8=*/true>(layer_params, conv2d_params, BATCH_SIZE);
+    
+    // setup runtime parameters for elementwise operator
+    uint32_t eltwise_binary_mode = layer_params[LP_SIZE_SKGEN];
+    switch (eltwise_binary_mode) {
+
+      case ELTBINARY_ADD1D:
+        add1d<DTYPE_ELTWISE_IFM, DTYPE_ELTWISE_IFM, DTYPE_OFM>::setup(add1d_params, ((int8 *)layer_params+32));
+        elt_ifmsv_size = add1d_params.ifmsv_size;
+        break;
+    
+      case ELTBINARY_MUL1D:
+        mul1d<DTYPE_ELTWISE_IFM, DTYPE_ELTWISE_IFM, DTYPE_OFM>::setup(mul1d_params, ((int8 *)layer_params+32));
+        elt_ifmsv_size = mul1d_params.ifmsv_size;
+        break;
+    
+      default:
+    }
+
+    num_depth_iter = conv2d_params.num_ifm_depth_iters;
+    int num_iter_out = conv2d_params.num_ifm_width_iters * conv2d_params.num_ifm_height_iters * conv2d_params.num_ofm_depth_iters;
+    num_iter = num_iter_out * num_depth_iter;
+
+    // for full-broadcast
+    ifm2_offset = core_row * elt_ifmsv_size;
+  }
+
+  depth_iter++;
+  total_iters++;
+  curr_iter++;
+
+  if (depth_iter == 1)
+    ofm.acquire();
+
+  conv2d_bf16<BATCH_SIZE, ACT_TYPE, DTYPE_IFM, DTYPE_WTS,DTYPE_OFM, BPCTYPE_IFM, BPCTYPE_WTS, BPCTYPE_OFM,/*enable_psum_float=*/false, /*enable_FC=*/false,/*enable_och_gran_8=*/true>(ifm1, wts, ofm, conv2d_params);
+
+  if (depth_iter == num_depth_iter)
+  {
+    ifm2.acquire();
+    DTYPE_IFM* ifm2_ptr = (DTYPE_IFM*)ifm2.data() + ifm2_offset;
+    DTYPE_OFM* ofm_ptr = (DTYPE_OFM*)ofm.data();
+    
+   uint32_t eltwise_binary_mode = layer_params[LP_SIZE_SKGEN];
+   switch (eltwise_binary_mode) {
+
+      case ELTBINARY_ADD1D:
+        add1d<DTYPE_ELTWISE_IFM, DTYPE_ELTWISE_IFM, DTYPE_OFM>::run(ofm_ptr, ifm2_ptr, ofm_ptr, add1d_params);
+        break;
+    
+      case ELTBINARY_MUL1D:
+        mul1d<DTYPE_ELTWISE_IFM, DTYPE_ELTWISE_IFM, DTYPE_OFM>::run(ofm_ptr, ifm2_ptr, ofm_ptr, mul1d_params);
+        break;
+    
+      default:
+    }
+
+    ifm2.release();
+    ofm.release();
+    depth_iter = 0; // Reset depth_iter
+  }
+
+  if (curr_iter == num_iter)
+    curr_iter = 0;
+
+}
diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/superkernels.h b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/superkernels.h
new file mode 100644
index 0000000000000000000000000000000000000000..08177a4c88fb155eba7dde26db1072b36ff0b447
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/superkernels.h
@@ -0,0 +1,81 @@
+#pragma once
+#include "mllib_config.h"
+#include "layer_runtime_params.h"
+void conv2d_maxpool
+(
+adf::input_buffer_conf<DTYPE_IFM, BPCTYPE_IFM>  & __restrict ifm,
+adf::input_buffer_conf<DTYPE_WTS, BPCTYPE_WTS>  & __restrict wts,
+const uint32_t (&layer_params)[LP_SIZE_SKGEN],
+adf::output_buffer_conf<DTYPE_OFM, BPCTYPE_OFM> & __restrict ofm
+) __attribute__( ( noinline ) );
+void superkernel_add1d_attribute_broadcasting(
+	adf::input_buffer_conf<bfloat16, bpc_sync_0d> & __restrict ifm,
+	const uint32_t (&layer_params)[LP_SIZE_SKGEN],
+	adf::output_buffer_conf<bfloat16, bpc_async_0d> & __restrict ofm
+)  __attribute__( ( noinline ) );
+void superkernel_add1d(
+	adf::input_buffer_conf<bfloat16, bpc_sync_0d> & __restrict ifm1,
+	const uint32_t (&layer_params)[LP_SIZE_SKGEN],
+	adf::input_buffer_conf<bfloat16, bpc_async_0d> & __restrict ifm2,
+	adf::output_buffer_conf<bfloat16, bpc_async_0d> & __restrict ofm
+)  __attribute__( ( noinline ) );
+void superkernel_clip1d(
+	adf::input_buffer_conf<bfloat16, bpc_sync_0d> & __restrict ifm,
+	const uint32_t (&layer_params)[LP_SIZE_SKGEN],
+	adf::output_buffer_conf<bfloat16, bpc_async_0d> & __restrict ofm
+)  __attribute__( ( noinline ) );
+void superkernel_mul1d_attribute_broadcasting(
+	adf::input_buffer_conf<bfloat16, bpc_sync_0d> & __restrict ifm,
+	const uint32_t (&layer_params)[LP_SIZE_SKGEN],
+	adf::output_buffer_conf<bfloat16, bpc_async_0d> & __restrict ofm
+)  __attribute__( ( noinline ) );
+void superkernel_mul1d(
+	adf::input_buffer_conf<bfloat16, bpc_sync_0d> & __restrict ifm1,
+	const uint32_t (&layer_params)[LP_SIZE_SKGEN],
+	adf::input_buffer_conf<bfloat16, bpc_async_0d> & __restrict ifm2,
+	adf::output_buffer_conf<bfloat16, bpc_async_0d> & __restrict ofm
+)  __attribute__( ( noinline ) );
+void superkernel_sigmoid1d(
+	adf::input_buffer_conf<bfloat16, bpc_sync_0d> & __restrict ifm,
+	const uint32_t (&layer_params)[LP_SIZE_SKGEN],
+	adf::output_buffer_conf<bfloat16, bpc_async_0d> & __restrict ofm
+)  __attribute__( ( noinline ) );
+void superkernel_sub1d(
+	adf::input_buffer_conf<bfloat16, bpc_sync_0d> & __restrict ifm1,
+	const uint32_t (&layer_params)[LP_SIZE_SKGEN],
+	adf::input_buffer_conf<bfloat16, bpc_async_0d> & __restrict ifm2,
+	adf::output_buffer_conf<bfloat16, bpc_async_0d> & __restrict ofm
+)  __attribute__( ( noinline ) );
+void superkernel_tanh1d(
+	adf::input_buffer_conf<bfloat16, bpc_sync_0d> & __restrict ifm,
+	const uint32_t (&layer_params)[LP_SIZE_SKGEN],
+	adf::output_buffer_conf<bfloat16, bpc_async_0d> & __restrict ofm
+)  __attribute__( ( noinline ) );
+void superkernel_reduce_mean_c8(
+	adf::input_buffer_conf<bfloat16, bpc_sync_0d> & __restrict ifm,
+	const uint32_t (&layer_params)[LP_SIZE_SKGEN],
+	adf::output_buffer_conf<bfloat16, bpc_async_0d> & __restrict ofm
+)  __attribute__( ( noinline ) );
+
+void superkernel_avgpool
+(
+adf::input_buffer_conf<DTYPE_IFM, BPCTYPE_IFM>  & __restrict ifm,
+const uint32_t (&layer_params)[LP_SIZE_SKGEN],
+adf::output_buffer_conf<DTYPE_OFM, BPCTYPE_OFM> & __restrict ofm
+) __attribute__( ( noinline ) );
+void superkernel_conv2d_dwc
+(
+adf::input_buffer_conf<DTYPE_IFM, BPCTYPE_IFM>  & __restrict ifm,
+adf::input_buffer_conf<DTYPE_WTS, BPCTYPE_WTS>  & __restrict wts,
+const uint32_t (&layer_params)[LP_SIZE_SKGEN],
+adf::output_buffer_conf<DTYPE_OFM, BPCTYPE_OFM> & __restrict ofm
+) __attribute__( ( noinline ) );
+
+void superkernel_conv_eltbinary
+(
+  adf::input_buffer_conf<DTYPE_IFM, BPCTYPE_IFM>  & __restrict ifm1,
+  adf::input_buffer_conf<DTYPE_WTS, BPCTYPE_WTS>  & __restrict wts,
+  adf::input_buffer_conf<DTYPE_IFM, BPCTYPE_IFM2> & __restrict ifm2,
+  const uint32_t (&layer_params)[LP_SIZE_CONV_ELTBINARY_SKGEN],
+  adf::output_buffer_conf<DTYPE_OFM, BPCTYPE_OFM> & __restrict ofm
+) __attribute__( ( noinline ) );
diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/tensor_dims.json b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/tensor_dims.json
new file mode 100644
index 0000000000000000000000000000000000000000..628b3bd20767c40fcdaad39a69c4001527983a71
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/tensor_dims.json
@@ -0,0 +1,32071 @@
+{
+  "__VERSION__": 1,
+  "Div_2": {
+    "MulAttributeBroadcastingBf16": {
+      "aie_arch": "aie2p",
+      "compiler": "chess",
+      "ifm_shift": 0,
+      "ifm_shift_biased": 0,
+      "ifmsv_depth": 24,
+      "ifmsv_height": 20,
+      "ifmsv_size": 1920,
+      "ifmsv_width": 4,
+      "num_kernel_iters": 8,
+      "ofm_shift": 0,
+      "ofm_shift_biased": 0,
+      "scalar": 0.00390625,
+      "scalar_position": 1,
+      "scalar_shift": 0,
+      "scalar_shift_biased": 0
+    },
+    "dims_and_bounds": [
+      {
+        "bounds": [
+          180,
+          320,
+          4
+        ],
+        "dims": [
+          184,
+          320,
+          4
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      },
+      {
+        "bounds": [
+          180,
+          320,
+          4
+        ],
+        "dims": [
+          192,
+          320,
+          4
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      }
+    ],
+    "input_layer_names": [
+      {
+        "name": "Input.0",
+        "type": "external"
+      }
+    ],
+    "layer_order": 1
+  },
+  "Slice_7": {
+    "SliceHCWC8Adf": {
+      "aie_arch": "aie2p",
+      "axis_letter": "W",
+      "dim_c": 184,
+      "dim_h": 320,
+      "dim_w": 4,
+      "dtype": "bfloat16",
+      "end": 3,
+      "input_l3_format": "HCWN_C8",
+      "kernel_col": 4,
+      "num_ifm_shim_ch": 2,
+      "num_ofm_shim_ch": 2,
+      "output_l3_format": "HCWN_C8",
+      "start": 0,
+      "step": 1
+    },
+    "dims_and_bounds": [
+      {
+        "bounds": [
+          180,
+          320,
+          4
+        ],
+        "dims": [
+          184,
+          320,
+          4
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      },
+      {
+        "bounds": [
+          180,
+          320,
+          3
+        ],
+        "dims": [
+          184,
+          320,
+          3
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      }
+    ],
+    "input_layer_names": [
+      {
+        "name": "Div_2",
+        "type": "internal"
+      }
+    ],
+    "layer_order": 2
+  },
+  "Generated-#0": {
+    "BufferPadAdf": {
+      "aie_arch": "aie2p",
+      "dim_0": 320,
+      "dim_0_padded": 320,
+      "dim_1": 23,
+      "dim_1_padded": 23,
+      "dim_2": 3,
+      "dim_2_padded": 8,
+      "dim_3": 8,
+      "dim_3_padded": 8,
+      "dtype": "bfloat16",
+      "input_l3_format": "HCWN_C8",
+      "kernel_col": 4,
+      "output_l3_format": "HCWN_C8"
+    },
+    "dims_and_bounds": [
+      {
+        "bounds": [
+          180,
+          320,
+          3
+        ],
+        "dims": [
+          184,
+          320,
+          3
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      },
+      {
+        "bounds": [
+          180,
+          320,
+          3
+        ],
+        "dims": [
+          184,
+          320,
+          8
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      }
+    ],
+    "input_layer_names": [
+      {
+        "name": "Slice_7",
+        "type": "internal"
+      }
+    ],
+    "layer_order": 3
+  },
+  "Generated-#2": {
+    "Transpose4dAdf": {
+      "aie_arch": "aie2p",
+      "dim_0": 320,
+      "dim_1": 23,
+      "dim_2": 8,
+      "dim_3": 8,
+      "dtype": "bfloat16",
+      "input_l3_format": "HCWN_C8",
+      "kernel_col": 4,
+      "output_l3_format": "HCWN_C8",
+      "perm": 10
+    },
+    "dims_and_bounds": [
+      {
+        "bounds": [
+          180,
+          320,
+          3
+        ],
+        "dims": [
+          184,
+          320,
+          8
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      },
+      {
+        "bounds": [
+          3,
+          180,
+          320
+        ],
+        "dims": [
+          8,
+          184,
+          320
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      }
+    ],
+    "input_layer_names": [
+      {
+        "name": "Generated-#0",
+        "type": "internal"
+      }
+    ],
+    "layer_order": 4
+  },
+  "Generated-#4": {
+    "BufferUnpadAdf": {
+      "aie_arch": "aie2p",
+      "dim_0": 184,
+      "dim_0_unpadded": 180,
+      "dim_1": 1,
+      "dim_1_unpadded": 1,
+      "dim_2": 320,
+      "dim_2_unpadded": 320,
+      "dim_3": 8,
+      "dim_3_unpadded": 8,
+      "dtype": "bfloat16",
+      "input_l3_format": "HCWN_C8",
+      "kernel_col": 4,
+      "output_l3_format": "HCWN_C8"
+    },
+    "dims_and_bounds": [
+      {
+        "bounds": [
+          3,
+          180,
+          320
+        ],
+        "dims": [
+          8,
+          184,
+          320
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      },
+      {
+        "bounds": [
+          3,
+          180,
+          320
+        ],
+        "dims": [
+          8,
+          180,
+          320
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      }
+    ],
+    "input_layer_names": [
+      {
+        "name": "Generated-#2",
+        "type": "internal"
+      }
+    ],
+    "layer_order": 5
+  },
+  "Sub_14": {
+    "AddBf16": {
+      "act": 0,
+      "act_type": "LINEAR",
+      "aie_arch": "aie2p",
+      "compiler": "chess",
+      "dtype": "bfloat16",
+      "ifm1_shift": 0,
+      "ifm1_shift_biased": 0,
+      "ifm2_shift": 0,
+      "ifm2_shift_biased": 0,
+      "ifmsv_depth": 8,
+      "ifmsv_height": 5,
+      "ifmsv_size": 640,
+      "ifmsv_width": 16,
+      "num_elems": 57600,
+      "num_kernel_iters": 180,
+      "ofm_shift": 0,
+      "ofm_shift_biased": 0
+    },
+    "constants_reader": {
+      "Const.0": {
+        "bytes_to_skip": 20764800,
+        "channel_stride": 8,
+        "depth": 1,
+        "dtype": "bfloat16",
+        "height": 180,
+        "nibbles": 4,
+        "num_reads": 86400,
+        "rank": 4,
+        "reads_per_line": 3,
+        "width": 320
+      }
+    },
+    "dims_and_bounds": [
+      {
+        "bounds": [
+          3,
+          180,
+          320
+        ],
+        "dims": [
+          8,
+          180,
+          320
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      },
+      {
+        "bounds": [
+          3,
+          180,
+          320
+        ],
+        "dims": [
+          8,
+          180,
+          320
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      },
+      {
+        "bounds": [
+          3,
+          180,
+          320
+        ],
+        "dims": [
+          8,
+          180,
+          320
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      }
+    ],
+    "input_layer_names": [
+      {
+        "name": "Generated-#4",
+        "type": "internal"
+      },
+      {
+        "name": "Const.0",
+        "type": "constant"
+      }
+    ],
+    "layer_order": 6
+  },
+  "Div_16": {
+    "MulBf16": {
+      "aie_arch": "aie2p",
+      "compiler": "chess",
+      "dtype": "bfloat16",
+      "ifm1_shift": 0,
+      "ifm1_shift_biased": 0,
+      "ifm2_shift": 0,
+      "ifm2_shift_biased": 0,
+      "ifmsv_depth": 8,
+      "ifmsv_height": 5,
+      "ifmsv_size": 640,
+      "ifmsv_width": 16,
+      "num_elems": 57600,
+      "num_kernel_iters": 180,
+      "ofm_shift": 0,
+      "ofm_shift_biased": 0
+    },
+    "constants_reader": {
+      "Const.1": {
+        "bytes_to_skip": 20764800,
+        "channel_stride": 8,
+        "depth": 1,
+        "dtype": "bfloat16",
+        "height": 180,
+        "nibbles": 4,
+        "num_reads": 86400,
+        "rank": 4,
+        "reads_per_line": 3,
+        "width": 320
+      }
+    },
+    "dims_and_bounds": [
+      {
+        "bounds": [
+          3,
+          180,
+          320
+        ],
+        "dims": [
+          8,
+          180,
+          320
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      },
+      {
+        "bounds": [
+          3,
+          180,
+          320
+        ],
+        "dims": [
+          8,
+          180,
+          320
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
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+          "height": 0,
+          "width": 0
+        }
+      },
+      {
+        "bounds": [
+          16,
+          180,
+          320
+        ],
+        "dims": [
+          16,
+          180,
+          320
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      }
+    ],
+    "input_layer_names": [
+      {
+        "name": "Conv_439",
+        "type": "internal"
+      }
+    ],
+    "layer_order": 296,
+    "split_width": false,
+    "wts_reader": {
+      "BFP16MMUL": true,
+      "bias_bytes_to_skip": 144,
+      "bias_rep": 4,
+      "bias_sg_bytes_to_skip": 36,
+      "bias_sub_group_num_reads": 12,
+      "cstride": 8,
+      "ifm_depth_iter": 1,
+      "ifm_depth_padded": 16,
+      "is_dwc": false,
+      "is_zero_padded": false,
+      "istride": 8,
+      "kernel_height": 3,
+      "kernel_width": 3,
+      "krnl_w_div": 1,
+      "num_bias_sub_groups": 1,
+      "ofm_depth_iter": 1,
+      "ofm_depth_padded": 32,
+      "output_stride": 8,
+      "rtp_bytes_to_skip": 144,
+      "total_layer_bytes_to_skip": 20733696,
+      "wts_no_of_reads": 1728
+    }
+  },
+  "Conv_443": {
+    "Conv2DBf16": {
+      "AIE_API_EMULATE_BFLOAT16_MMUL_WITH_BFP16": 1,
+      "act": 0,
+      "act_type": "RELU",
+      "aie_arch": "aie2p",
+      "alpha": 0,
+      "alpha_scaled": 3277,
+      "batch_size": 1,
+      "compiler": "chess",
+      "conv2d_ofm_pad": 0,
+      "conv_type": 64,
+      "data_io.ofm.dimensions.width": 64,
+      "dtype_ifm": "bfloat16",
+      "dtype_ofm": "bfloat16",
+      "dtype_wts": "bfloat16",
+      "enable_padding": 0,
+      "force_och_gran_8": 1,
+      "func_type": 0,
+      "ifm_depth": 16,
+      "ifm_depth_concat_extend": 0,
+      "ifm_depth_iter": 1,
+      "ifm_height": 180,
+      "ifm_sign": 0,
+      "ifm_sv_depth": 64,
+      "ifm_sv_height": 1,
+      "ifm_sv_height.padding": 0,
+      "ifm_sv_width": 64,
+      "ifm_width": 320,
+      "ifm_x_iter": 5,
+      "ifm_y_iter": 45,
+      "kernel_height": 1,
+      "kernel_width": 1,
+      "ksize.height": 1,
+      "ksize.width": 1,
+      "lrelu_alpha": 1,
+      "lrelu_alpha_kernel": 1,
+      "num_adf_cols": 4,
+      "num_adf_rows": 4,
+      "num_ifm_depth_iters": 1,
+      "num_ifm_height_iters": 45,
+      "num_ifm_width_iters": 5,
+      "num_ofm_depth_iters": 1,
+      "ofm_depth": 8,
+      "ofm_depth_iter": 1,
+      "ofm_height": 180,
+      "ofm_offset_packed.left": 0,
+      "ofm_offset_packed.top": 0,
+      "ofm_sv_depth": 8,
+      "ofm_sv_height": 1,
+      "ofm_sv_overlap_height": 0,
+      "ofm_sv_overlap_width": 0,
+      "ofm_sv_width": 64,
+      "ofm_width": 320,
+      "ofm_width_pad": 0,
+      "op_type": 0,
+      "out_mode": 0,
+      "pad_bottom": 0,
+      "pad_left": 0,
+      "pad_right": 0,
+      "pad_top": 0,
+      "pad_value": 0,
+      "padding_sv_height": 1,
+      "padding_sv_width": 64,
+      "psum_buff_offset_scaled": 4,
+      "relu_int8_enable": 0,
+      "shift_bias_init": 0,
+      "shift_lrelu_alpha": 0,
+      "shift_lrelu_in": 0,
+      "shift_lrelu_out": 0,
+      "shift_out": 0,
+      "shift_psum": 0,
+      "shift_psum_in": 0,
+      "signed_value": 0,
+      "stride_h": 1,
+      "stride_height": 1,
+      "stride_log2.stride_log2_height": 0,
+      "stride_log2.stride_log2_width": 0,
+      "stride_w": 1,
+      "stride_width": 1,
+      "zp_en": 0
+    },
+    "dims_and_bounds": [
+      {
+        "bounds": [
+          16,
+          180,
+          320
+        ],
+        "dims": [
+          16,
+          180,
+          320
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      },
+      {
+        "bounds": [
+          4,
+          180,
+          320
+        ],
+        "dims": [
+          8,
+          180,
+          320
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      }
+    ],
+    "input_layer_names": [
+      {
+        "name": "Conv_441",
+        "type": "internal"
+      }
+    ],
+    "layer_order": 297,
+    "split_width": false,
+    "wts_reader": {
+      "BFP16MMUL": true,
+      "bias_bytes_to_skip": 144,
+      "bias_rep": 4,
+      "bias_sg_bytes_to_skip": 36,
+      "bias_sub_group_num_reads": 12,
+      "cstride": 8,
+      "ifm_depth_iter": 1,
+      "ifm_depth_padded": 64,
+      "is_dwc": false,
+      "is_zero_padded": false,
+      "istride": 8,
+      "kernel_height": 1,
+      "kernel_width": 1,
+      "krnl_w_div": 1,
+      "num_bias_sub_groups": 1,
+      "ofm_depth_iter": 1,
+      "ofm_depth_padded": 32,
+      "output_stride": 8,
+      "rtp_bytes_to_skip": 144,
+      "total_layer_bytes_to_skip": 20755008,
+      "wts_no_of_reads": 768
+    }
+  },
+  "Split_444_Duplicated#1": {
+    "SliceHCWC8Adf": {
+      "aie_arch": "aie2p",
+      "axis_letter": "C",
+      "dim_c": 8,
+      "dim_h": 180,
+      "dim_w": 320,
+      "dtype": "bfloat16",
+      "end": 4,
+      "input_l3_format": "HCWN_C8",
+      "kernel_col": 4,
+      "num_ifm_shim_ch": 2,
+      "num_ofm_shim_ch": 2,
+      "output_l3_format": "HCWN_C8",
+      "start": 3,
+      "step": 1
+    },
+    "dims_and_bounds": [
+      {
+        "bounds": [
+          4,
+          180,
+          320
+        ],
+        "dims": [
+          8,
+          180,
+          320
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      },
+      {
+        "bounds": [
+          1,
+          180,
+          320
+        ],
+        "dims": [
+          8,
+          180,
+          320
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      }
+    ],
+    "input_layer_names": [
+      {
+        "name": "Conv_443",
+        "type": "internal"
+      }
+    ],
+    "layer_order": 298
+  },
+  "Clip_447": {
+    "ClipBf16": {
+      "aie_arch": "aie2p",
+      "clamp_max": 1,
+      "clamp_min": 0,
+      "compiler": "chess",
+      "ifm_shift": 0,
+      "ifm_shift_biased": 0,
+      "ifmsv_depth": 8,
+      "ifmsv_height": 5,
+      "ifmsv_size": 1600,
+      "ifmsv_width": 40,
+      "num_kernel_iters": 72,
+      "ofm_shift": 0,
+      "ofm_shift_biased": 0
+    },
+    "dims_and_bounds": [
+      {
+        "bounds": [
+          1,
+          180,
+          320
+        ],
+        "dims": [
+          8,
+          180,
+          320
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      },
+      {
+        "bounds": [
+          1,
+          180,
+          320
+        ],
+        "dims": [
+          8,
+          180,
+          320
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      }
+    ],
+    "external_output_layer": 5,
+    "input_layer_names": [
+      {
+        "name": "Split_444_Duplicated#1",
+        "type": "internal"
+      }
+    ],
+    "layer_order": 299
+  },
+  "Split_444_Duplicated#0": {
+    "SliceHCWC8Adf": {
+      "aie_arch": "aie2p",
+      "axis_letter": "C",
+      "dim_c": 8,
+      "dim_h": 180,
+      "dim_w": 320,
+      "dtype": "bfloat16",
+      "end": 3,
+      "input_l3_format": "HCWN_C8",
+      "kernel_col": 4,
+      "num_ifm_shim_ch": 2,
+      "num_ofm_shim_ch": 2,
+      "output_l3_format": "HCWN_C8",
+      "start": 0,
+      "step": 1
+    },
+    "dims_and_bounds": [
+      {
+        "bounds": [
+          4,
+          180,
+          320
+        ],
+        "dims": [
+          8,
+          180,
+          320
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      },
+      {
+        "bounds": [
+          3,
+          180,
+          320
+        ],
+        "dims": [
+          8,
+          180,
+          320
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      }
+    ],
+    "input_layer_names": [
+      {
+        "name": "Conv_443",
+        "type": "internal"
+      }
+    ],
+    "layer_order": 300
+  },
+  "Add_445": {
+    "AddBf16": {
+      "act": 0,
+      "act_type": "LINEAR",
+      "aie_arch": "aie2p",
+      "compiler": "chess",
+      "dtype": "bfloat16",
+      "ifm1_shift": 0,
+      "ifm1_shift_biased": 0,
+      "ifm2_shift": 0,
+      "ifm2_shift_biased": 0,
+      "ifmsv_depth": 8,
+      "ifmsv_height": 5,
+      "ifmsv_size": 640,
+      "ifmsv_width": 16,
+      "num_elems": 57600,
+      "num_kernel_iters": 180,
+      "ofm_shift": 0,
+      "ofm_shift_biased": 0
+    },
+    "dims_and_bounds": [
+      {
+        "bounds": [
+          3,
+          180,
+          320
+        ],
+        "dims": [
+          8,
+          180,
+          320
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      },
+      {
+        "bounds": [
+          3,
+          180,
+          320
+        ],
+        "dims": [
+          8,
+          180,
+          320
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      },
+      {
+        "bounds": [
+          3,
+          180,
+          320
+        ],
+        "dims": [
+          8,
+          180,
+          320
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      }
+    ],
+    "input_layer_names": [
+      {
+        "name": "Split_444_Duplicated#0",
+        "type": "internal"
+      },
+      {
+        "name": "Generated-#4",
+        "type": "internal"
+      }
+    ],
+    "layer_order": 301
+  },
+  "Clip_446": {
+    "ClipBf16": {
+      "aie_arch": "aie2p",
+      "clamp_max": 1,
+      "clamp_min": 0,
+      "compiler": "chess",
+      "ifm_shift": 0,
+      "ifm_shift_biased": 0,
+      "ifmsv_depth": 8,
+      "ifmsv_height": 5,
+      "ifmsv_size": 1600,
+      "ifmsv_width": 40,
+      "num_kernel_iters": 72,
+      "ofm_shift": 0,
+      "ofm_shift_biased": 0
+    },
+    "dims_and_bounds": [
+      {
+        "bounds": [
+          3,
+          180,
+          320
+        ],
+        "dims": [
+          8,
+          180,
+          320
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      },
+      {
+        "bounds": [
+          3,
+          180,
+          320
+        ],
+        "dims": [
+          8,
+          180,
+          320
+        ],
+        "dtype": "bfloat16",
+        "keys": [
+          "depth",
+          "height",
+          "width"
+        ],
+        "padding_at_start": {
+          "cin": 0,
+          "cout": 0,
+          "height": 0,
+          "width": 0
+        }
+      }
+    ],
+    "external_output_layer": 4,
+    "input_layer_names": [
+      {
+        "name": "Add_445",
+        "type": "internal"
+      }
+    ],
+    "layer_order": 302
+  }
+}
diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/tiling.h b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/tiling.h
new file mode 100644
index 0000000000000000000000000000000000000000..16efd0d8421a085a975c041ff10e2ebba97b69a2
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/tiling.h
@@ -0,0 +1,19592 @@
+#include <adf.h>
+using namespace adf;
+
+// Layer: 1
+// LayerName: Div_2
+std::vector<uint32_t> ifm_dim_1 = {8, 4, 23, 320};
+std::vector<uint32_t> ifm_bound_1 = {8, 4, 23, 320};
+std::vector<uint32_t> ifmsv_dim_1 = {8, 4, 3, 20};
+uint32_t ifmsv_size_1 = 7680;
+uint32_t kernel_iter_1 = 8;
+bool has_l1_write_access_pattern_1 = false;
+std::vector<access_pattern> l1_write_pattern_1 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_1 = {
+{
+  tiling({.buffer_dimension = {8, 4, 23, 320}, .tiling_dimension = {8, 4, 3, 20}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 8}, {.dimension = 3, .stride = 80, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 4, 23, 320}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 4, 23, 320}, .tiling_dimension = {8, 4, 3, 20}, .offset = {0, 0, 0, 20}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 8}, {.dimension = 3, .stride = 80, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 4, 23, 320}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 4, 23, 320}, .tiling_dimension = {8, 4, 3, 20}, .offset = {0, 0, 0, 40}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 8}, {.dimension = 3, .stride = 80, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 4, 23, 320}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 4, 23, 320}, .tiling_dimension = {8, 4, 3, 20}, .offset = {0, 0, 0, 60}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 8}, {.dimension = 3, .stride = 80, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 4, 23, 320}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_1 = 0;
+bool has_l1_wts_write_access_pattern_1 = false;
+std::vector<access_pattern> l1_wts_write_pattern_1 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_1 = {};
+
+
+std::vector<uint32_t> ofm_dim_1 = {8, 4, 24, 320};
+std::vector<uint32_t> ofm_bound_1 = {8, 4, 23, 320};
+std::vector<uint32_t> ofmsv_dim_1 = {8, 4, 3, 20};
+uint32_t ofmsv_size_1 = 1920;
+uint32_t ofm_repetition_1 = 1;
+bool has_l1_read_access_pattern_1 = false;
+
+std::vector<access_pattern> l1_read_pattern_1 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_1 = {
+{
+  tiling({.buffer_dimension = {8, 4, 24, 320}, .tiling_dimension = {8, 4, 3, 20}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 2}, {.dimension = 3, .stride = 80, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 4, 24, 320}, .tiling_dimension = {8, 4, 3, 20}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 2}, {.dimension = 3, .stride = 80, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 4, 24, 320}, .tiling_dimension = {8, 4, 3, 20}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 2}, {.dimension = 3, .stride = 80, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 4, 24, 320}, .tiling_dimension = {8, 4, 3, 20}, .offset = {0, 0, 9, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 2}, {.dimension = 3, .stride = 80, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 4, 24, 320}, .tiling_dimension = {8, 4, 3, 20}, .offset = {0, 0, 0, 20}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 2}, {.dimension = 3, .stride = 80, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 4, 24, 320}, .tiling_dimension = {8, 4, 3, 20}, .offset = {0, 0, 3, 20}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 2}, {.dimension = 3, .stride = 80, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 4, 24, 320}, .tiling_dimension = {8, 4, 3, 20}, .offset = {0, 0, 6, 20}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 2}, {.dimension = 3, .stride = 80, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 4, 24, 320}, .tiling_dimension = {8, 4, 3, 20}, .offset = {0, 0, 9, 20}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 2}, {.dimension = 3, .stride = 80, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 4, 24, 320}, .tiling_dimension = {8, 4, 3, 20}, .offset = {0, 0, 0, 40}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 2}, {.dimension = 3, .stride = 80, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 4, 24, 320}, .tiling_dimension = {8, 4, 3, 20}, .offset = {0, 0, 3, 40}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 2}, {.dimension = 3, .stride = 80, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 4, 24, 320}, .tiling_dimension = {8, 4, 3, 20}, .offset = {0, 0, 6, 40}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 2}, {.dimension = 3, .stride = 80, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 4, 24, 320}, .tiling_dimension = {8, 4, 3, 20}, .offset = {0, 0, 9, 40}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 2}, {.dimension = 3, .stride = 80, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 4, 24, 320}, .tiling_dimension = {8, 4, 3, 20}, .offset = {0, 0, 0, 60}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 2}, {.dimension = 3, .stride = 80, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 4, 24, 320}, .tiling_dimension = {8, 4, 3, 20}, .offset = {0, 0, 3, 60}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 2}, {.dimension = 3, .stride = 80, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 4, 24, 320}, .tiling_dimension = {8, 4, 3, 20}, .offset = {0, 0, 6, 60}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 2}, {.dimension = 3, .stride = 80, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 4, 24, 320}, .tiling_dimension = {8, 4, 3, 20}, .offset = {0, 0, 9, 60}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 2}, {.dimension = 3, .stride = 80, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 6
+// LayerName: Sub_14
+std::vector<uint32_t> ifm_dim_6 = {8, 320, 1, 20};
+std::vector<uint32_t> ifm_bound_6 = {8, 320, 1, 20};
+std::vector<uint32_t> ifmsv_dim_6 = {8, 16, 1, 5};
+uint32_t ifmsv_size_6 = 2560;
+uint32_t kernel_iter_6 = 180;
+bool has_l1_write_access_pattern_6 = false;
+std::vector<access_pattern> l1_write_pattern_6 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_6 = {
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 5}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_6 = {8, 320, 1, 20};
+std::vector<uint32_t> ifm2_bound_6 = {8, 320, 1, 20};
+std::vector<uint32_t> ifm2sv_dim_6 = {8, 16, 1, 5};
+uint32_t ifm2sv_size_6 = 2560;
+std::vector<std::vector<access_pattern>> ifm2_pattern_6 = {
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 5}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_6 = 0;
+bool has_l1_wts_write_access_pattern_6 = false;
+std::vector<access_pattern> l1_wts_write_pattern_6 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_6 = {};
+
+
+std::vector<uint32_t> ofm_dim_6 = {8, 320, 4, 20};
+std::vector<uint32_t> ofm_bound_6 = {8, 320, 1, 20};
+std::vector<uint32_t> ofmsv_dim_6 = {8, 16, 1, 5};
+uint32_t ofmsv_size_6 = 640;
+uint32_t ofm_repetition_6 = 1;
+bool has_l1_read_access_pattern_6 = false;
+
+std::vector<access_pattern> l1_read_pattern_6 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_6 = {
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 5}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 1, 5}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 2, 5}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 3, 5}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 1, 10}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 2, 10}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 3, 10}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 1, 15}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 2, 15}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 3, 15}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 7
+// LayerName: Div_16
+std::vector<uint32_t> ifm_dim_7 = {8, 320, 1, 20};
+std::vector<uint32_t> ifm_bound_7 = {8, 320, 1, 20};
+std::vector<uint32_t> ifmsv_dim_7 = {8, 16, 1, 5};
+uint32_t ifmsv_size_7 = 2560;
+uint32_t kernel_iter_7 = 180;
+bool has_l1_write_access_pattern_7 = false;
+std::vector<access_pattern> l1_write_pattern_7 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_7 = {
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 5}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_7 = {8, 320, 1, 20};
+std::vector<uint32_t> ifm2_bound_7 = {8, 320, 1, 20};
+std::vector<uint32_t> ifm2sv_dim_7 = {8, 16, 1, 5};
+uint32_t ifm2sv_size_7 = 2560;
+std::vector<std::vector<access_pattern>> ifm2_pattern_7 = {
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 5}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_7 = 0;
+bool has_l1_wts_write_access_pattern_7 = false;
+std::vector<access_pattern> l1_wts_write_pattern_7 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_7 = {};
+
+
+std::vector<uint32_t> ofm_dim_7 = {8, 320, 4, 20};
+std::vector<uint32_t> ofm_bound_7 = {8, 320, 1, 20};
+std::vector<uint32_t> ofmsv_dim_7 = {8, 16, 1, 5};
+uint32_t ofmsv_size_7 = 640;
+uint32_t ofm_repetition_7 = 1;
+bool has_l1_read_access_pattern_7 = false;
+
+std::vector<access_pattern> l1_read_pattern_7 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_7 = {
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 5}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 1, 5}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 2, 5}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 3, 5}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 1, 10}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 2, 10}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 3, 10}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 1, 15}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 2, 15}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 3, 15}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 8
+// LayerName: Conv_17
+std::vector<uint32_t> ifm_dim_8 = {8, 320, 1, 61};
+std::vector<uint32_t> ifm_bound_8 = {8, 320, 1, 61};
+std::vector<uint32_t> ifmsv_dim_8 = {8, 66, 1, 10};
+uint32_t ifmsv_size_8 = 5280;
+uint32_t kernel_iter_8 = 30;
+bool has_l1_write_access_pattern_8 = false;
+std::vector<access_pattern> l1_write_pattern_8 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_8 = {
+{
+  tiling({.buffer_dimension = {8, 320, 1, 60}, .tiling_dimension = {8, 66, 1, 10}, .offset = {0, -1, 0, -1}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 32, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 1, 61}, .tiling_dimension = {8, 66, 1, 10}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 32, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 320, 1, 61}, .tiling_dimension = {8, 66, 1, 10}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 32, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 60}, .tiling_dimension = {8, 66, 1, 10}, .offset = {0, -1, 0, 7}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 32, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 1, 61}, .tiling_dimension = {8, 66, 1, 10}, .offset = {0, -1, 0, 8}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 32, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 320, 1, 61}, .tiling_dimension = {8, 66, 1, 10}, .offset = {0, -1, 0, 8}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 32, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 60}, .tiling_dimension = {8, 66, 1, 10}, .offset = {0, -1, 0, 15}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 32, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 1, 61}, .tiling_dimension = {8, 66, 1, 10}, .offset = {0, -1, 0, 16}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 32, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 320, 1, 61}, .tiling_dimension = {8, 66, 1, 10}, .offset = {0, -1, 0, 16}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 32, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 60}, .tiling_dimension = {8, 66, 1, 10}, .offset = {0, -1, 0, 23}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 32, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 1, 61}, .tiling_dimension = {8, 66, 1, 10}, .offset = {0, -1, 0, 24}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 32, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 320, 1, 61}, .tiling_dimension = {8, 66, 1, 10}, .offset = {0, -1, 0, 24}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 32, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_8 = {2432};
+std::vector<uint32_t> wts_dim_8 = {2432};
+std::vector<uint32_t> wtssv_dim_8 = {608};
+uint32_t wtssv_size_8 = 608;
+uint32_t wts_repetition_8 = 1;
+bool has_l1_wts_write_access_pattern_8 = false;
+std::vector<access_pattern> l1_wts_write_pattern_8 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_8 = {
+{
+  tiling({.buffer_dimension = {608, 4}, .tiling_dimension = {608, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 30, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {608, 4}, .tiling_dimension = {608, 1}, .offset = {0, 1}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 30, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {608, 4}, .tiling_dimension = {608, 1}, .offset = {0, 2}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 30, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {608, 4}, .tiling_dimension = {608, 1}, .offset = {0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 30, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_8[] = {
+{
+  tiling({.buffer_dimension = {2432, 1}, .tiling_dimension = {1216, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2432, 1}, .tiling_dimension = {1216, 1}, .offset = {1216, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_8[] = {
+{
+  tiling({.buffer_dimension = {2432}, .tiling_dimension = {1216}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2432}, .tiling_dimension = {1216}, .offset = {1216}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_8 = {8, 160, 4, 32};
+std::vector<uint32_t> ofm_bound_8 = {8, 160, 2, 30};
+std::vector<uint32_t> ofmsv_dim_8 = {8, 32, 1, 4};
+uint32_t ofmsv_size_8 = 1024;
+uint32_t ofm_repetition_8 = 1;
+bool has_l1_read_access_pattern_8 = false;
+
+std::vector<access_pattern> l1_read_pattern_8 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_8 = {
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 1, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 2, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 3, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 1, 8}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 2, 8}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 3, 8}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 1, 12}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 3, 12}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 9
+// LayerName: Add_19
+std::vector<uint32_t> ifm_dim_9 = {8, 160, 2, 90};
+std::vector<uint32_t> ifm_bound_9 = {8, 160, 2, 90};
+std::vector<uint32_t> ifmsv_dim_9 = {8, 8, 1, 23};
+uint32_t ifmsv_size_9 = 5888;
+uint32_t kernel_iter_9 = 20;
+bool has_l1_write_access_pattern_9 = false;
+std::vector<access_pattern> l1_write_pattern_9 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_9 = {
+{
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 160, 2, 90}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 0, 23}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 160, 2, 90}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 0, 46}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 160, 2, 90}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 0, 69}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 160, 2, 90}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_9 = 0;
+bool has_l1_wts_write_access_pattern_9 = false;
+std::vector<access_pattern> l1_wts_write_pattern_9 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_9 = {};
+
+
+std::vector<uint32_t> ofm_dim_9 = {8, 160, 4, 92};
+std::vector<uint32_t> ofm_bound_9 = {8, 160, 2, 90};
+std::vector<uint32_t> ofmsv_dim_9 = {8, 8, 1, 23};
+uint32_t ofmsv_size_9 = 1472;
+uint32_t ofm_repetition_9 = 1;
+bool has_l1_read_access_pattern_9 = false;
+
+std::vector<access_pattern> l1_read_pattern_9 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_9 = {
+{
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 0, 23}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 1, 23}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 2, 23}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 3, 23}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 0, 46}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 1, 46}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 2, 46}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 3, 46}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 0, 69}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 1, 69}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 2, 69}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 3, 69}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 10
+// LayerName: Clip_22
+std::vector<uint32_t> ifm_dim_10 = {8, 160, 2, 45};
+std::vector<uint32_t> ifm_bound_10 = {8, 160, 2, 45};
+std::vector<uint32_t> ifmsv_dim_10 = {8, 20, 1, 12};
+uint32_t ifmsv_size_10 = 7680;
+uint32_t kernel_iter_10 = 16;
+bool has_l1_write_access_pattern_10 = false;
+std::vector<access_pattern> l1_write_pattern_10 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_10 = {
+{
+  tiling({.buffer_dimension = {8, 160, 2, 45}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 45}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 45}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 45}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_10 = 0;
+bool has_l1_wts_write_access_pattern_10 = false;
+std::vector<access_pattern> l1_wts_write_pattern_10 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_10 = {};
+
+
+std::vector<uint32_t> ofm_dim_10 = {8, 160, 4, 48};
+std::vector<uint32_t> ofm_bound_10 = {8, 160, 2, 45};
+std::vector<uint32_t> ofmsv_dim_10 = {8, 20, 1, 12};
+uint32_t ofmsv_size_10 = 1920;
+uint32_t ofm_repetition_10 = 1;
+bool has_l1_read_access_pattern_10 = false;
+
+std::vector<access_pattern> l1_read_pattern_10 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_10 = {
+{
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 1, 12}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 3, 12}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 1, 24}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 2, 24}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 3, 24}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 1, 36}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 2, 36}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 3, 36}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 11
+// LayerName: Div_24
+std::vector<uint32_t> ifm_dim_11 = {8, 160, 2, 90};
+std::vector<uint32_t> ifm_bound_11 = {8, 160, 2, 90};
+std::vector<uint32_t> ifmsv_dim_11 = {8, 8, 1, 23};
+uint32_t ifmsv_size_11 = 5888;
+uint32_t kernel_iter_11 = 20;
+bool has_l1_write_access_pattern_11 = false;
+std::vector<access_pattern> l1_write_pattern_11 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_11 = {
+{
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 160, 2, 90}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 0, 23}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 160, 2, 90}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 0, 46}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 160, 2, 90}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 0, 69}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 160, 2, 90}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_11 = 0;
+bool has_l1_wts_write_access_pattern_11 = false;
+std::vector<access_pattern> l1_wts_write_pattern_11 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_11 = {};
+
+
+std::vector<uint32_t> ofm_dim_11 = {8, 160, 4, 92};
+std::vector<uint32_t> ofm_bound_11 = {8, 160, 2, 90};
+std::vector<uint32_t> ofmsv_dim_11 = {8, 8, 1, 23};
+uint32_t ofmsv_size_11 = 1472;
+uint32_t ofm_repetition_11 = 1;
+bool has_l1_read_access_pattern_11 = false;
+
+std::vector<access_pattern> l1_read_pattern_11 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_11 = {
+{
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 0, 23}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 1, 23}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 2, 23}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 3, 23}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 0, 46}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 1, 46}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 2, 46}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 3, 46}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 0, 69}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 1, 69}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 2, 69}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 3, 69}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 12
+// LayerName: Mul_25
+std::vector<uint32_t> ifm_dim_12 = {8, 160, 2, 30};
+std::vector<uint32_t> ifm_bound_12 = {8, 160, 2, 30};
+std::vector<uint32_t> ifmsv_dim_12 = {8, 16, 1, 8};
+uint32_t ifmsv_size_12 = 4096;
+uint32_t kernel_iter_12 = 30;
+bool has_l1_write_access_pattern_12 = false;
+std::vector<access_pattern> l1_write_pattern_12 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_12 = {
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_12 = {8, 160, 2, 30};
+std::vector<uint32_t> ifm2_bound_12 = {8, 160, 2, 30};
+std::vector<uint32_t> ifm2sv_dim_12 = {8, 16, 1, 8};
+uint32_t ifm2sv_size_12 = 4096;
+std::vector<std::vector<access_pattern>> ifm2_pattern_12 = {
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_12 = 0;
+bool has_l1_wts_write_access_pattern_12 = false;
+std::vector<access_pattern> l1_wts_write_pattern_12 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_12 = {};
+
+
+std::vector<uint32_t> ofm_dim_12 = {8, 160, 4, 32};
+std::vector<uint32_t> ofm_bound_12 = {8, 160, 2, 30};
+std::vector<uint32_t> ofmsv_dim_12 = {8, 16, 1, 8};
+uint32_t ofmsv_size_12 = 1024;
+uint32_t ofm_repetition_12 = 1;
+bool has_l1_read_access_pattern_12 = false;
+
+std::vector<access_pattern> l1_read_pattern_12 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_12 = {
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 1, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 2, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 3, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 1, 16}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 2, 16}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 3, 16}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 1, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 2, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 3, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 13
+// LayerName: Conv_26
+std::vector<uint32_t> ifm_dim_13 = {8, 160, 2, 90};
+std::vector<uint32_t> ifm_bound_13 = {8, 160, 2, 90};
+std::vector<uint32_t> ifmsv_dim_13 = {8, 20, 1, 8};
+uint32_t ifmsv_size_13 = 5120;
+uint32_t kernel_iter_13 = 40;
+bool has_l1_write_access_pattern_13 = false;
+std::vector<access_pattern> l1_write_pattern_13 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_13 = {
+{
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 20, 1, 8}, .offset = {0, -1, 0, -1}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 160, 2, 90}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 20, 1, 8}, .offset = {0, -1, 0, 5}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 160, 2, 90}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 20, 1, 8}, .offset = {0, -1, 0, 11}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 160, 2, 90}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 20, 1, 8}, .offset = {0, -1, 0, 17}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 160, 2, 90}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_13 = {512};
+std::vector<uint32_t> wts_dim_13 = {512};
+std::vector<uint32_t> wtssv_dim_13 = {128};
+uint32_t wts_repetition_13 = 1;
+uint32_t wtssv_size_13 = 128;
+bool has_l1_wts_write_access_pattern_13 = false;
+std::vector<access_pattern> l1_wts_write_pattern_13 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_13 = {
+{
+  tiling({.buffer_dimension = {512}, .tiling_dimension = {128}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 40, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {512}, .tiling_dimension = {128}, .offset = {128}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 40, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {512}, .tiling_dimension = {128}, .offset = {256}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 40, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {512}, .tiling_dimension = {128}, .offset = {384}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 40, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_13[] = {
+{
+  tiling({.buffer_dimension = {512, 1}, .tiling_dimension = {256, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {512, 1}, .tiling_dimension = {256, 1}, .offset = {256, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_13[] = {
+{
+  tiling({.buffer_dimension = {512}, .tiling_dimension = {256}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {512}, .tiling_dimension = {256}, .offset = {256}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_13 = {8, 160, 4, 96};
+std::vector<uint32_t> ofm_bound_13 = {8, 160, 2, 90};
+std::vector<uint32_t> ofmsv_dim_13 = {8, 16, 1, 6};
+uint32_t ofmsv_size_13 = 768;
+uint32_t ofm_repetition_13 = 1;
+bool has_l1_read_access_pattern_13 = false;
+
+std::vector<access_pattern> l1_read_pattern_13 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_13 = {
+{
+  tiling({.buffer_dimension = {8, 160, 4, 96}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 96}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 96}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 96}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 96}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 96}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 1, 6}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 96}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 96}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 3, 6}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 96}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 96}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 1, 12}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 96}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 96}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 3, 12}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 96}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 96}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 1, 18}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 96}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 2, 18}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 96}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 3, 18}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 14
+// LayerName: Conv_28
+std::vector<uint32_t> ifm_dim_14 = {8, 160, 2, 45};
+std::vector<uint32_t> ifm_bound_14 = {8, 160, 2, 45};
+std::vector<uint32_t> ifmsv_dim_14 = {8, 32, 8, 2};
+uint32_t ifmsv_size_14 = 4096;
+uint32_t kernel_iter_14 = 60;
+bool has_l1_write_access_pattern_14 = false;
+std::vector<access_pattern> l1_write_pattern_14 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_14 = {
+{
+  tiling({.buffer_dimension = {8, 160, 2, 45}, .tiling_dimension = {8, 32, 8, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 45}, .tiling_dimension = {8, 32, 8, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 45}, .tiling_dimension = {8, 32, 8, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 45}, .tiling_dimension = {8, 32, 8, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_14 = {8, 160, 4, 48};
+std::vector<uint32_t> ifm2_bound_14 = {8, 160, 2, 45};
+std::vector<uint32_t> ifm2sv_dim_14 = {8, 32, 1, 2};
+uint32_t ifm2sv_size_14 = 2048;
+std::vector<std::vector<access_pattern>> ifm2_pattern_14 = {
+{
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 32, 1, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 32, 1, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 32, 1, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 32, 1, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_14 = {2176};
+std::vector<uint32_t> wts_dim_14 = {2176};
+std::vector<uint32_t> wtssv_dim_14 = {544};
+uint32_t wtssv_size_14 = 544;
+uint32_t wts_repetition_14 = 1;
+bool has_l1_wts_write_access_pattern_14 = false;
+std::vector<access_pattern> l1_wts_write_pattern_14 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_14 = {
+{
+  tiling({.buffer_dimension = {544, 4}, .tiling_dimension = {544, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 60, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {544, 4}, .tiling_dimension = {544, 1}, .offset = {0, 1}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 60, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {544, 4}, .tiling_dimension = {544, 1}, .offset = {0, 2}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 60, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {544, 4}, .tiling_dimension = {544, 1}, .offset = {0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 60, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_14[] = {
+{
+  tiling({.buffer_dimension = {2176, 1}, .tiling_dimension = {1088, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176, 1}, .tiling_dimension = {1088, 1}, .offset = {1088, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_14[] = {
+{
+  tiling({.buffer_dimension = {2176}, .tiling_dimension = {1088}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176}, .tiling_dimension = {1088}, .offset = {1088}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_14 = {8, 160, 4, 48};
+std::vector<uint32_t> ofm_bound_14 = {8, 160, 2, 45};
+std::vector<uint32_t> ofmsv_dim_14 = {8, 32, 1, 2};
+uint32_t ofmsv_size_14 = 512;
+uint32_t ofm_repetition_14 = 1;
+bool has_l1_read_access_pattern_14 = false;
+
+std::vector<access_pattern> l1_read_pattern_14 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_14 = {
+{
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 32, 1, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 32, 1, 2}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 32, 1, 2}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 32, 1, 2}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 32, 1, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 32, 1, 2}, .offset = {0, 0, 1, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 32, 1, 2}, .offset = {0, 0, 2, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 32, 1, 2}, .offset = {0, 0, 3, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 32, 1, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 32, 1, 2}, .offset = {0, 0, 1, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 32, 1, 2}, .offset = {0, 0, 2, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 32, 1, 2}, .offset = {0, 0, 3, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 32, 1, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 32, 1, 2}, .offset = {0, 0, 1, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 32, 1, 2}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 48}, .tiling_dimension = {8, 32, 1, 2}, .offset = {0, 0, 3, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 15
+// LayerName: Conv_30
+std::vector<uint32_t> ifm_dim_15 = {8, 160, 2, 18};
+std::vector<uint32_t> ifm_bound_15 = {8, 160, 2, 18};
+std::vector<uint32_t> ifmsv_dim_15 = {8, 8, 8, 9};
+uint32_t ifmsv_size_15 = 4608;
+uint32_t kernel_iter_15 = 50;
+bool has_l1_write_access_pattern_15 = false;
+std::vector<access_pattern> l1_write_pattern_15 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_15 = {
+{
+  tiling({.buffer_dimension = {8, 160, 2, 18}, .tiling_dimension = {8, 8, 8, 9}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 9, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 18}, .tiling_dimension = {8, 8, 8, 9}, .offset = {0, 8, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 9, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 18}, .tiling_dimension = {8, 8, 8, 9}, .offset = {0, 16, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 9, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 18}, .tiling_dimension = {8, 8, 8, 9}, .offset = {0, 24, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 9, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_15 = {4352};
+std::vector<uint32_t> wts_dim_15 = {4352};
+std::vector<uint32_t> wtssv_dim_15 = {1088};
+uint32_t wtssv_size_15 = 1088;
+uint32_t wts_repetition_15 = 1;
+bool has_l1_wts_write_access_pattern_15 = false;
+std::vector<access_pattern> l1_wts_write_pattern_15 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_15 = {
+{
+  tiling({.buffer_dimension = {1088, 4}, .tiling_dimension = {1088, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 50, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1088, 4}, .tiling_dimension = {1088, 1}, .offset = {0, 1}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 50, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1088, 4}, .tiling_dimension = {1088, 1}, .offset = {0, 2}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 50, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1088, 4}, .tiling_dimension = {1088, 1}, .offset = {0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 50, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_15[] = {
+{
+  tiling({.buffer_dimension = {4352, 1}, .tiling_dimension = {2176, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4352, 1}, .tiling_dimension = {2176, 1}, .offset = {2176, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_15[] = {
+{
+  tiling({.buffer_dimension = {4352}, .tiling_dimension = {2176}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4352}, .tiling_dimension = {2176}, .offset = {2176}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_15 = {8, 160, 8, 18};
+std::vector<uint32_t> ofm_bound_15 = {8, 160, 8, 18};
+std::vector<uint32_t> ofmsv_dim_15 = {8, 8, 2, 9};
+uint32_t ofmsv_size_15 = 1152;
+uint32_t ofm_repetition_15 = 1;
+bool has_l1_read_access_pattern_15 = false;
+
+std::vector<access_pattern> l1_read_pattern_15 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_15 = {
+{
+  tiling({.buffer_dimension = {8, 160, 8, 18}, .tiling_dimension = {8, 8, 2, 9}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 9, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 18}, .tiling_dimension = {8, 8, 2, 9}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 9, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 18}, .tiling_dimension = {8, 8, 2, 9}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 9, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 18}, .tiling_dimension = {8, 8, 2, 9}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 9, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 8, 18}, .tiling_dimension = {8, 8, 2, 9}, .offset = {0, 8, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 9, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 18}, .tiling_dimension = {8, 8, 2, 9}, .offset = {0, 8, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 9, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 18}, .tiling_dimension = {8, 8, 2, 9}, .offset = {0, 8, 4, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 9, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 18}, .tiling_dimension = {8, 8, 2, 9}, .offset = {0, 8, 6, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 9, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 8, 18}, .tiling_dimension = {8, 8, 2, 9}, .offset = {0, 16, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 9, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 18}, .tiling_dimension = {8, 8, 2, 9}, .offset = {0, 16, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 9, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 18}, .tiling_dimension = {8, 8, 2, 9}, .offset = {0, 16, 4, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 9, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 18}, .tiling_dimension = {8, 8, 2, 9}, .offset = {0, 16, 6, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 9, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 8, 18}, .tiling_dimension = {8, 8, 2, 9}, .offset = {0, 24, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 9, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 18}, .tiling_dimension = {8, 8, 2, 9}, .offset = {0, 24, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 9, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 18}, .tiling_dimension = {8, 8, 2, 9}, .offset = {0, 24, 4, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 9, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 18}, .tiling_dimension = {8, 8, 2, 9}, .offset = {0, 24, 6, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 9, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 16
+// LayerName: Conv_32
+std::vector<uint32_t> ifm_dim_16 = {8, 160, 8, 17};
+std::vector<uint32_t> ifm_bound_16 = {8, 160, 8, 17};
+std::vector<uint32_t> ifmsv_dim_16 = {8, 28, 1, 6};
+uint32_t ifmsv_size_16 = 5376;
+uint32_t kernel_iter_16 = 84;
+bool has_l1_write_access_pattern_16 = false;
+std::vector<access_pattern> l1_write_pattern_16 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_16 = {
+{
+  tiling({.buffer_dimension = {8, 160, 8, 16}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, -1}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 8}, {.dimension = 1, .stride = 24, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 17}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 8}, {.dimension = 1, .stride = 24, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 160, 8, 17}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 8}, {.dimension = 1, .stride = 24, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2}),
+  tiling({.buffer_dimension = {8, 160, 8, 17}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 8}, {.dimension = 1, .stride = 24, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 3}),
+  tiling({.buffer_dimension = {8, 160, 8, 17}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 8}, {.dimension = 1, .stride = 24, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 4}),
+  tiling({.buffer_dimension = {8, 160, 8, 11}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 8}, {.dimension = 1, .stride = 24, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 5})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 8, 16}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 8}, {.dimension = 1, .stride = 24, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 17}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 8}, {.dimension = 1, .stride = 24, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 160, 8, 17}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 8}, {.dimension = 1, .stride = 24, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2}),
+  tiling({.buffer_dimension = {8, 160, 8, 17}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 8}, {.dimension = 1, .stride = 24, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 3}),
+  tiling({.buffer_dimension = {8, 160, 8, 17}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 8}, {.dimension = 1, .stride = 24, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 4}),
+  tiling({.buffer_dimension = {8, 160, 8, 11}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 8}, {.dimension = 1, .stride = 24, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 5})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 8, 16}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 7}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 8}, {.dimension = 1, .stride = 24, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 17}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 8}, {.dimension = 1, .stride = 24, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 160, 8, 17}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 8}, {.dimension = 1, .stride = 24, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2}),
+  tiling({.buffer_dimension = {8, 160, 8, 17}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 8}, {.dimension = 1, .stride = 24, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 3}),
+  tiling({.buffer_dimension = {8, 160, 8, 17}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 8}, {.dimension = 1, .stride = 24, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 4}),
+  tiling({.buffer_dimension = {8, 160, 8, 11}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 8}, {.dimension = 1, .stride = 24, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 5})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 8, 16}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 11}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 8}, {.dimension = 1, .stride = 24, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 17}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 8}, {.dimension = 1, .stride = 24, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 160, 8, 17}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 8}, {.dimension = 1, .stride = 24, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2}),
+  tiling({.buffer_dimension = {8, 160, 8, 17}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 8}, {.dimension = 1, .stride = 24, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 3}),
+  tiling({.buffer_dimension = {8, 160, 8, 17}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 8}, {.dimension = 1, .stride = 24, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 4}),
+  tiling({.buffer_dimension = {8, 160, 8, 11}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 8}, {.dimension = 1, .stride = 24, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 5})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_16 = {1024};
+std::vector<uint32_t> wts_dim_16 = {1024};
+std::vector<uint32_t> wtssv_dim_16 = {128};
+uint32_t wts_repetition_16 = 6;
+uint32_t wtssv_size_16 = 128;
+bool has_l1_wts_write_access_pattern_16 = false;
+std::vector<access_pattern> l1_wts_write_pattern_16 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_16 = {
+{
+  tiling({.buffer_dimension = {1024}, .tiling_dimension = {128}, .offset = {0}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 2} }, .packet_port_id = -1, .repetition = 7, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1024}, .tiling_dimension = {128}, .offset = {128}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 2} }, .packet_port_id = -1, .repetition = 7, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1024}, .tiling_dimension = {128}, .offset = {256}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 2} }, .packet_port_id = -1, .repetition = 7, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1024}, .tiling_dimension = {128}, .offset = {384}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 2} }, .packet_port_id = -1, .repetition = 7, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_16[] = {
+{
+  tiling({.buffer_dimension = {1024, 1}, .tiling_dimension = {512, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1024, 1}, .tiling_dimension = {512, 1}, .offset = {512, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_16[] = {
+{
+  tiling({.buffer_dimension = {1024}, .tiling_dimension = {512}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1024}, .tiling_dimension = {512}, .offset = {512}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_16 = {8, 84, 8, 8};
+std::vector<uint32_t> ofm_bound_16 = {8, 80, 8, 8};
+std::vector<uint32_t> ofmsv_dim_16 = {8, 12, 1, 2};
+uint32_t ofmsv_size_16 = 192;
+uint32_t ofm_repetition_16 = 1;
+bool has_l1_read_access_pattern_16 = false;
+
+std::vector<access_pattern> l1_read_pattern_16 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_16 = {
+{
+  tiling({.buffer_dimension = {8, 84, 8, 8}, .tiling_dimension = {8, 12, 1, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 2}, {.dimension = 1, .stride = 12, .wrap = 7} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 84, 8, 8}, .tiling_dimension = {8, 12, 1, 2}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 2}, {.dimension = 1, .stride = 12, .wrap = 7} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 84, 8, 8}, .tiling_dimension = {8, 12, 1, 2}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 2}, {.dimension = 1, .stride = 12, .wrap = 7} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 84, 8, 8}, .tiling_dimension = {8, 12, 1, 2}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 2}, {.dimension = 1, .stride = 12, .wrap = 7} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 84, 8, 8}, .tiling_dimension = {8, 12, 1, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 2}, {.dimension = 1, .stride = 12, .wrap = 7} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 84, 8, 8}, .tiling_dimension = {8, 12, 1, 2}, .offset = {0, 0, 1, 2}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 2}, {.dimension = 1, .stride = 12, .wrap = 7} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 84, 8, 8}, .tiling_dimension = {8, 12, 1, 2}, .offset = {0, 0, 2, 2}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 2}, {.dimension = 1, .stride = 12, .wrap = 7} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 84, 8, 8}, .tiling_dimension = {8, 12, 1, 2}, .offset = {0, 0, 3, 2}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 2}, {.dimension = 1, .stride = 12, .wrap = 7} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 84, 8, 8}, .tiling_dimension = {8, 12, 1, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 2}, {.dimension = 1, .stride = 12, .wrap = 7} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 84, 8, 8}, .tiling_dimension = {8, 12, 1, 2}, .offset = {0, 0, 1, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 2}, {.dimension = 1, .stride = 12, .wrap = 7} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 84, 8, 8}, .tiling_dimension = {8, 12, 1, 2}, .offset = {0, 0, 2, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 2}, {.dimension = 1, .stride = 12, .wrap = 7} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 84, 8, 8}, .tiling_dimension = {8, 12, 1, 2}, .offset = {0, 0, 3, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 2}, {.dimension = 1, .stride = 12, .wrap = 7} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 84, 8, 8}, .tiling_dimension = {8, 12, 1, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 2}, {.dimension = 1, .stride = 12, .wrap = 7} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 84, 8, 8}, .tiling_dimension = {8, 12, 1, 2}, .offset = {0, 0, 1, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 2}, {.dimension = 1, .stride = 12, .wrap = 7} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 84, 8, 8}, .tiling_dimension = {8, 12, 1, 2}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 2}, {.dimension = 1, .stride = 12, .wrap = 7} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 84, 8, 8}, .tiling_dimension = {8, 12, 1, 2}, .offset = {0, 0, 3, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 2}, {.dimension = 1, .stride = 12, .wrap = 7} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 18
+// LayerName: Conv_34
+std::vector<uint32_t> ifm_dim_18 = {8, 80, 8, 45};
+std::vector<uint32_t> ifm_bound_18 = {8, 80, 8, 45};
+std::vector<uint32_t> ifmsv_dim_18 = {8, 16, 8, 4};
+uint32_t ifmsv_size_18 = 4096;
+uint32_t kernel_iter_18 = 15;
+bool has_l1_write_access_pattern_18 = false;
+std::vector<access_pattern> l1_write_pattern_18 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_18 = {
+{
+  tiling({.buffer_dimension = {8, 80, 8, 45}, .tiling_dimension = {8, 16, 8, 4}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 8, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 45}, .tiling_dimension = {8, 16, 8, 4}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 8, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 45}, .tiling_dimension = {8, 16, 8, 4}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 8, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 45}, .tiling_dimension = {8, 16, 8, 4}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 8, 45}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_18 = {4352};
+std::vector<uint32_t> wts_dim_18 = {4352};
+std::vector<uint32_t> wtssv_dim_18 = {1088};
+uint32_t wtssv_size_18 = 1088;
+uint32_t wts_repetition_18 = 1;
+bool has_l1_wts_write_access_pattern_18 = false;
+std::vector<access_pattern> l1_wts_write_pattern_18 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_18 = {
+{
+  tiling({.buffer_dimension = {1088, 4}, .tiling_dimension = {1088, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 15, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1088, 4}, .tiling_dimension = {1088, 1}, .offset = {0, 1}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 15, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1088, 4}, .tiling_dimension = {1088, 1}, .offset = {0, 2}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 15, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1088, 4}, .tiling_dimension = {1088, 1}, .offset = {0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 15, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_18[] = {
+{
+  tiling({.buffer_dimension = {4352, 1}, .tiling_dimension = {2176, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4352, 1}, .tiling_dimension = {2176, 1}, .offset = {2176, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_18[] = {
+{
+  tiling({.buffer_dimension = {4352}, .tiling_dimension = {2176}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4352}, .tiling_dimension = {2176}, .offset = {2176}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_18 = {8, 80, 8, 48};
+std::vector<uint32_t> ofm_bound_18 = {8, 80, 3, 45};
+std::vector<uint32_t> ofmsv_dim_18 = {8, 16, 2, 4};
+uint32_t ofmsv_size_18 = 1024;
+uint32_t ofm_repetition_18 = 1;
+bool has_l1_read_access_pattern_18 = false;
+
+std::vector<access_pattern> l1_read_pattern_18 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_18 = {
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 2, 4}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 4, 4}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 6, 4}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 2, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 4, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 6, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 4, 12}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 6, 12}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 19
+// LayerName: Conv_35
+std::vector<uint32_t> ifm_dim_19 = {8, 80, 8, 48};
+std::vector<uint32_t> ifm_bound_19 = {8, 80, 3, 45};
+std::vector<uint32_t> ifmsv_dim_19 = {8, 32, 8, 2};
+uint32_t ifmsv_size_19 = 4096;
+uint32_t kernel_iter_19 = 18;
+bool has_l1_write_access_pattern_19 = false;
+std::vector<access_pattern> l1_write_pattern_19 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_19 = {
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 32, 8, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 32, 8, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 32, 8, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 32, 8, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_19 = {6528};
+std::vector<uint32_t> wts_dim_19 = {6528};
+std::vector<uint32_t> wtssv_dim_19 = {1632};
+uint32_t wtssv_size_19 = 1632;
+uint32_t wts_repetition_19 = 1;
+bool has_l1_wts_write_access_pattern_19 = false;
+std::vector<access_pattern> l1_wts_write_pattern_19 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_19 = {
+{
+  tiling({.buffer_dimension = {1632, 4}, .tiling_dimension = {1632, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 18, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1632, 4}, .tiling_dimension = {1632, 1}, .offset = {0, 1}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 18, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1632, 4}, .tiling_dimension = {1632, 1}, .offset = {0, 2}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 18, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1632, 4}, .tiling_dimension = {1632, 1}, .offset = {0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 18, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_19[] = {
+{
+  tiling({.buffer_dimension = {6528, 1}, .tiling_dimension = {3264, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {6528, 1}, .tiling_dimension = {3264, 1}, .offset = {3264, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_19[] = {
+{
+  tiling({.buffer_dimension = {6528}, .tiling_dimension = {3264}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {6528}, .tiling_dimension = {3264}, .offset = {3264}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_19 = {8, 96, 12, 48};
+std::vector<uint32_t> ofm_bound_19 = {8, 80, 9, 45};
+std::vector<uint32_t> ofmsv_dim_19 = {8, 32, 3, 2};
+uint32_t ofmsv_size_19 = 1536;
+uint32_t ofm_repetition_19 = 1;
+bool has_l1_read_access_pattern_19 = false;
+
+std::vector<access_pattern> l1_read_pattern_19 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_19 = {
+{
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 9, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 3, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 6, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 9, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 3, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 6, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 9, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 3, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 9, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 20
+// LayerName: Conv_37
+std::vector<uint32_t> ifm_dim_20 = {8, 80, 9, 25};
+std::vector<uint32_t> ifm_bound_20 = {8, 80, 9, 25};
+std::vector<uint32_t> ifmsv_dim_20 = {8, 20, 1, 8};
+uint32_t ifmsv_size_20 = 5120;
+uint32_t kernel_iter_20 = 30;
+bool has_l1_write_access_pattern_20 = false;
+std::vector<access_pattern> l1_write_pattern_20 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_20 = {
+{
+  tiling({.buffer_dimension = {8, 80, 9, 24}, .tiling_dimension = {8, 20, 1, 8}, .offset = {0, -1, 0, -1}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 12}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 9, 23}, .tiling_dimension = {8, 20, 1, 8}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 12}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 9, 24}, .tiling_dimension = {8, 20, 1, 8}, .offset = {0, -1, 0, 5}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 12}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 9, 23}, .tiling_dimension = {8, 20, 1, 8}, .offset = {0, -1, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 12}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 9, 24}, .tiling_dimension = {8, 20, 1, 8}, .offset = {0, -1, 0, 11}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 12}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 9, 23}, .tiling_dimension = {8, 20, 1, 8}, .offset = {0, -1, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 12}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 9, 24}, .tiling_dimension = {8, 20, 1, 8}, .offset = {0, -1, 0, 17}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 12}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 9, 23}, .tiling_dimension = {8, 20, 1, 8}, .offset = {0, -1, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 12}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_20 = {1536};
+std::vector<uint32_t> wts_dim_20 = {1536};
+std::vector<uint32_t> wtssv_dim_20 = {128};
+uint32_t wts_repetition_20 = 2;
+uint32_t wtssv_size_20 = 128;
+bool has_l1_wts_write_access_pattern_20 = false;
+std::vector<access_pattern> l1_wts_write_pattern_20 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_20 = {
+{
+  tiling({.buffer_dimension = {1536}, .tiling_dimension = {128}, .offset = {0}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 3} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1536}, .tiling_dimension = {128}, .offset = {128}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 3} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1536}, .tiling_dimension = {128}, .offset = {256}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 3} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1536}, .tiling_dimension = {128}, .offset = {384}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 3} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_20[] = {
+{
+  tiling({.buffer_dimension = {1536, 1}, .tiling_dimension = {768, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1536, 1}, .tiling_dimension = {768, 1}, .offset = {768, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_20[] = {
+{
+  tiling({.buffer_dimension = {1536}, .tiling_dimension = {768}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1536}, .tiling_dimension = {768}, .offset = {768}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_20 = {8, 80, 12, 24};
+std::vector<uint32_t> ofm_bound_20 = {8, 80, 9, 23};
+std::vector<uint32_t> ofmsv_dim_20 = {8, 16, 1, 6};
+uint32_t ofmsv_size_20 = 768;
+uint32_t ofm_repetition_20 = 1;
+bool has_l1_read_access_pattern_20 = false;
+
+std::vector<access_pattern> l1_read_pattern_20 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_20 = {
+{
+  tiling({.buffer_dimension = {8, 80, 12, 24}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 12, 24}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 12, 24}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 12, 24}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 12, 24}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 12, 24}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 1, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 12, 24}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 12, 24}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 3, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 12, 24}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 12, 24}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 1, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 12, 24}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 12, 24}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 3, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 12, 24}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 12, 24}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 1, 18}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 12, 24}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 2, 18}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 12, 24}, .tiling_dimension = {8, 16, 1, 6}, .offset = {0, 0, 3, 18}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 22
+// LayerName: Conv_39
+std::vector<uint32_t> ifm_dim_22 = {8, 80, 9, 45};
+std::vector<uint32_t> ifm_bound_22 = {8, 80, 9, 45};
+std::vector<uint32_t> ifmsv_dim_22 = {8, 16, 9, 4};
+uint32_t ifmsv_size_22 = 4608;
+uint32_t kernel_iter_22 = 15;
+bool has_l1_write_access_pattern_22 = false;
+std::vector<access_pattern> l1_write_pattern_22 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_22 = {
+{
+  tiling({.buffer_dimension = {8, 80, 9, 45}, .tiling_dimension = {8, 16, 9, 4}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 9, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 9, 45}, .tiling_dimension = {8, 16, 9, 4}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 9, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 9, 45}, .tiling_dimension = {8, 16, 9, 4}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 9, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 9, 45}, .tiling_dimension = {8, 16, 9, 4}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 9, 45}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_22 = {8, 80, 8, 48};
+std::vector<uint32_t> ifm2_bound_22 = {8, 80, 3, 45};
+std::vector<uint32_t> ifm2sv_dim_22 = {8, 16, 2, 4};
+uint32_t ifm2sv_size_22 = 4096;
+std::vector<std::vector<access_pattern>> ifm2_pattern_22 = {
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_22 = {4864};
+std::vector<uint32_t> wts_dim_22 = {4864};
+std::vector<uint32_t> wtssv_dim_22 = {1216};
+uint32_t wtssv_size_22 = 1216;
+uint32_t wts_repetition_22 = 1;
+bool has_l1_wts_write_access_pattern_22 = false;
+std::vector<access_pattern> l1_wts_write_pattern_22 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_22 = {
+{
+  tiling({.buffer_dimension = {1216, 4}, .tiling_dimension = {1216, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 15, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1216, 4}, .tiling_dimension = {1216, 1}, .offset = {0, 1}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 15, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1216, 4}, .tiling_dimension = {1216, 1}, .offset = {0, 2}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 15, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1216, 4}, .tiling_dimension = {1216, 1}, .offset = {0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 15, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_22[] = {
+{
+  tiling({.buffer_dimension = {4864, 1}, .tiling_dimension = {2432, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4864, 1}, .tiling_dimension = {2432, 1}, .offset = {2432, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_22[] = {
+{
+  tiling({.buffer_dimension = {4864}, .tiling_dimension = {2432}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4864}, .tiling_dimension = {2432}, .offset = {2432}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_22 = {8, 80, 8, 48};
+std::vector<uint32_t> ofm_bound_22 = {8, 80, 3, 45};
+std::vector<uint32_t> ofmsv_dim_22 = {8, 16, 2, 4};
+uint32_t ofmsv_size_22 = 1024;
+uint32_t ofm_repetition_22 = 1;
+bool has_l1_read_access_pattern_22 = false;
+
+std::vector<access_pattern> l1_read_pattern_22 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_22 = {
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 2, 4}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 4, 4}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 6, 4}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 2, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 4, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 6, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 4, 12}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 4}, .offset = {0, 0, 6, 12}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 23
+// LayerName: Conv_41
+std::vector<uint32_t> ifm_dim_23 = {8, 80, 8, 48};
+std::vector<uint32_t> ifm_bound_23 = {8, 80, 3, 45};
+std::vector<uint32_t> ifmsv_dim_23 = {8, 32, 8, 2};
+uint32_t ifmsv_size_23 = 4096;
+uint32_t kernel_iter_23 = 18;
+bool has_l1_write_access_pattern_23 = false;
+std::vector<access_pattern> l1_write_pattern_23 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_23 = {
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 32, 8, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 32, 8, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 32, 8, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 32, 8, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_23 = {6528};
+std::vector<uint32_t> wts_dim_23 = {6528};
+std::vector<uint32_t> wtssv_dim_23 = {1632};
+uint32_t wtssv_size_23 = 1632;
+uint32_t wts_repetition_23 = 1;
+bool has_l1_wts_write_access_pattern_23 = false;
+std::vector<access_pattern> l1_wts_write_pattern_23 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_23 = {
+{
+  tiling({.buffer_dimension = {1632, 4}, .tiling_dimension = {1632, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 18, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1632, 4}, .tiling_dimension = {1632, 1}, .offset = {0, 1}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 18, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1632, 4}, .tiling_dimension = {1632, 1}, .offset = {0, 2}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 18, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1632, 4}, .tiling_dimension = {1632, 1}, .offset = {0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 18, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_23[] = {
+{
+  tiling({.buffer_dimension = {6528, 1}, .tiling_dimension = {3264, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {6528, 1}, .tiling_dimension = {3264, 1}, .offset = {3264, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_23[] = {
+{
+  tiling({.buffer_dimension = {6528}, .tiling_dimension = {3264}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {6528}, .tiling_dimension = {3264}, .offset = {3264}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_23 = {8, 96, 12, 48};
+std::vector<uint32_t> ofm_bound_23 = {8, 80, 9, 45};
+std::vector<uint32_t> ofmsv_dim_23 = {8, 32, 3, 2};
+uint32_t ofmsv_size_23 = 1536;
+uint32_t ofm_repetition_23 = 1;
+bool has_l1_read_access_pattern_23 = false;
+
+std::vector<access_pattern> l1_read_pattern_23 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_23 = {
+{
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 9, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 3, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 6, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 9, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 3, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 6, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 9, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 3, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 32, 3, 2}, .offset = {0, 0, 9, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 24
+// LayerName: Conv_43
+std::vector<uint32_t> ifm_dim_24 = {8, 96, 12, 48};
+std::vector<uint32_t> ifm_bound_24 = {8, 80, 9, 45};
+std::vector<uint32_t> ifmsv_dim_24 = {8, 20, 1, 8};
+uint32_t ifmsv_size_24 = 5120;
+uint32_t kernel_iter_24 = 45;
+bool has_l1_write_access_pattern_24 = false;
+std::vector<access_pattern> l1_write_pattern_24 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_24 = {
+{
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 20, 1, 8}, .offset = {0, -2, 0, -2}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 12}, {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 9, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 20, 1, 8}, .offset = {0, -2, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 12}, {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 9, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 20, 1, 8}, .offset = {0, -2, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 12}, {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 9, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 96, 12, 48}, .tiling_dimension = {8, 20, 1, 8}, .offset = {0, -2, 0, 10}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 12}, {.dimension = 1, .stride = 16, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 9, 45}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_24 = {4224};
+std::vector<uint32_t> wts_dim_24 = {4224};
+std::vector<uint32_t> wtssv_dim_24 = {352};
+uint32_t wts_repetition_24 = 1;
+uint32_t wtssv_size_24 = 352;
+bool has_l1_wts_write_access_pattern_24 = false;
+std::vector<access_pattern> l1_wts_write_pattern_24 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_24 = {
+{
+  tiling({.buffer_dimension = {4224}, .tiling_dimension = {352}, .offset = {0}, .tile_traversal = { {.dimension = 0, .stride = 1408, .wrap = 3} }, .packet_port_id = -1, .repetition = 15, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4224}, .tiling_dimension = {352}, .offset = {352}, .tile_traversal = { {.dimension = 0, .stride = 1408, .wrap = 3} }, .packet_port_id = -1, .repetition = 15, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4224}, .tiling_dimension = {352}, .offset = {704}, .tile_traversal = { {.dimension = 0, .stride = 1408, .wrap = 3} }, .packet_port_id = -1, .repetition = 15, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4224}, .tiling_dimension = {352}, .offset = {1056}, .tile_traversal = { {.dimension = 0, .stride = 1408, .wrap = 3} }, .packet_port_id = -1, .repetition = 15, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_24[] = {
+{
+  tiling({.buffer_dimension = {4224, 1}, .tiling_dimension = {2112, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4224, 1}, .tiling_dimension = {2112, 1}, .offset = {2112, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_24[] = {
+{
+  tiling({.buffer_dimension = {4224}, .tiling_dimension = {2112}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4224}, .tiling_dimension = {2112}, .offset = {2112}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_24 = {8, 40, 12, 24};
+std::vector<uint32_t> ofm_bound_24 = {8, 40, 9, 23};
+std::vector<uint32_t> ofmsv_dim_24 = {8, 8, 1, 2};
+uint32_t ofmsv_size_24 = 128;
+uint32_t ofm_repetition_24 = 1;
+bool has_l1_read_access_pattern_24 = false;
+
+std::vector<access_pattern> l1_read_pattern_24 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_24 = {
+{
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 8, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 8, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 8, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 8, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 8, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 1, 2}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 8, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 2, 2}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 8, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 3, 2}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 8, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 8, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 1, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 8, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 2, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 8, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 3, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 8, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 8, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 1, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 8, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 8, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 3, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 8, .wrap = 5}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 26
+// LayerName: Generated-#8
+std::vector<uint32_t> ifm_dim_26 = {8, 920, 9, 1};
+std::vector<uint32_t> ifm_bound_26 = {8, 920, 9, 1};
+std::vector<uint32_t> ifmsv_dim_26 = {8, 64, 4, 1};
+uint32_t ifmsv_size_26 = 8192;
+uint32_t kernel_iter_26 = 15;
+bool has_l1_write_access_pattern_26 = false;
+std::vector<access_pattern> l1_write_pattern_26 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_26 = {
+{
+  tiling({.buffer_dimension = {8, 920, 9, 1}, .tiling_dimension = {8, 64, 4, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 64, .wrap = 15} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 920, 9, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 920, 9, 1}, .tiling_dimension = {8, 64, 4, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 64, .wrap = 15} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 920, 9, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 920, 9, 1}, .tiling_dimension = {8, 64, 4, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 64, .wrap = 15} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 920, 9, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 920, 9, 1}, .tiling_dimension = {8, 64, 4, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 64, .wrap = 15} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 920, 9, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_26 = 0;
+bool has_l1_wts_write_access_pattern_26 = false;
+std::vector<access_pattern> l1_wts_write_pattern_26 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_26 = {};
+
+
+std::vector<uint32_t> ofm_dim_26 = {8, 1, 16, 4};
+std::vector<uint32_t> ofm_bound_26 = {8, 1, 9, 1};
+std::vector<uint32_t> ofmsv_dim_26 = {8, 1, 4, 1};
+uint32_t ofmsv_size_26 = 32;
+uint32_t ofm_repetition_26 = 15;
+bool has_l1_read_access_pattern_26 = false;
+std::vector<access_pattern> l1_read_pattern_26 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ofm_pattern_26 = {
+{
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 4, 1}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 8, 1}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 12, 1}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 4, 2}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 8, 2}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 12, 2}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 4, 3}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 8, 3}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 12, 3}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 27
+// LayerName: Conv_46
+std::vector<uint32_t> ifm_dim_27 = {8, 1, 16, 4};
+std::vector<uint32_t> ifm_bound_27 = {8, 1, 9, 1};
+std::vector<uint32_t> ifmsv_dim_27 = {8, 16, 9, 1};
+uint32_t ifmsv_size_27 = 1152;
+uint32_t kernel_iter_27 = 1;
+bool has_l1_write_access_pattern_27 = false;
+std::vector<access_pattern> l1_write_pattern_27 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_27 = {
+{
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 16, 9, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 9, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 16, 9, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 9, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 16, 9, 1}, .offset = {0, 32, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 9, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 16, 9, 1}, .offset = {0, 48, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 9, 1}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_27 = {4864};
+std::vector<uint32_t> wts_dim_27 = {4864};
+std::vector<uint32_t> wtssv_dim_27 = {1216};
+uint32_t wtssv_size_27 = 1216;
+uint32_t wts_repetition_27 = 1;
+bool has_l1_wts_write_access_pattern_27 = false;
+std::vector<access_pattern> l1_wts_write_pattern_27 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_27 = {
+{
+  tiling({.buffer_dimension = {1216, 4}, .tiling_dimension = {1216, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1216, 4}, .tiling_dimension = {1216, 1}, .offset = {0, 1}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1216, 4}, .tiling_dimension = {1216, 1}, .offset = {0, 2}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1216, 4}, .tiling_dimension = {1216, 1}, .offset = {0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_27[] = {
+{
+  tiling({.buffer_dimension = {4864, 1}, .tiling_dimension = {2432, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4864, 1}, .tiling_dimension = {2432, 1}, .offset = {2432, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_27[] = {
+{
+  tiling({.buffer_dimension = {4864}, .tiling_dimension = {2432}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4864}, .tiling_dimension = {2432}, .offset = {2432}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_27 = {8, 64, 8, 1};
+std::vector<uint32_t> ofm_bound_27 = {8, 1, 3, 1};
+std::vector<uint32_t> ofmsv_dim_27 = {8, 16, 2, 1};
+uint32_t ofmsv_size_27 = 256;
+uint32_t ofm_repetition_27 = 1;
+bool has_l1_read_access_pattern_27 = false;
+
+std::vector<access_pattern> l1_read_pattern_27 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_27 = {
+{
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 2, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 6, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 2, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 4, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 6, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 2, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 4, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 6, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 2, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 4, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 6, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 28
+// LayerName: Conv_48
+std::vector<uint32_t> ifm_dim_28 = {8, 64, 8, 1};
+std::vector<uint32_t> ifm_bound_28 = {8, 1, 3, 1};
+std::vector<uint32_t> ifmsv_dim_28 = {8, 8, 8, 1};
+uint32_t ifmsv_size_28 = 512;
+uint32_t kernel_iter_28 = 1;
+bool has_l1_write_access_pattern_28 = false;
+std::vector<access_pattern> l1_write_pattern_28 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_28 = {
+{
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 8, 8, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 3, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 8, 8, 1}, .offset = {0, 8, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 3, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 8, 8, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 3, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 8, 8, 1}, .offset = {0, 24, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 3, 1}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_28 = {8704};
+std::vector<uint32_t> wts_dim_28 = {8704};
+std::vector<uint32_t> wtssv_dim_28 = {2176};
+uint32_t wtssv_size_28 = 2176;
+uint32_t wts_repetition_28 = 1;
+bool has_l1_wts_write_access_pattern_28 = false;
+std::vector<access_pattern> l1_wts_write_pattern_28 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_28 = {
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {2176, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {2176, 1}, .offset = {0, 1}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {2176, 1}, .offset = {0, 2}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {2176, 1}, .offset = {0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_28[] = {
+{
+  tiling({.buffer_dimension = {8704, 1}, .tiling_dimension = {4352, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8704, 1}, .tiling_dimension = {4352, 1}, .offset = {4352, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_28[] = {
+{
+  tiling({.buffer_dimension = {8704}, .tiling_dimension = {4352}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8704}, .tiling_dimension = {4352}, .offset = {4352}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_28 = {8, 32, 16, 1};
+std::vector<uint32_t> ofm_bound_28 = {8, 1, 9, 1};
+std::vector<uint32_t> ofmsv_dim_28 = {8, 8, 4, 1};
+uint32_t ofmsv_size_28 = 256;
+uint32_t ofm_repetition_28 = 1;
+bool has_l1_read_access_pattern_28 = false;
+
+std::vector<access_pattern> l1_read_pattern_28 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_28 = {
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 0, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 0, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 8, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 8, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 8, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 8, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 16, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 16, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 16, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 24, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 24, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 24, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 24, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 29
+// LayerName: Add_50
+std::vector<uint32_t> ifm_dim_29 = {8, 32, 16, 1};
+std::vector<uint32_t> ifm_bound_29 = {8, 1, 9, 1};
+std::vector<uint32_t> ifmsv_dim_29 = {8, 1, 3, 16};
+uint32_t ifmsv_size_29 = 1536;
+uint32_t kernel_iter_29 = 1;
+bool has_l1_write_access_pattern_29 = false;
+std::vector<access_pattern> l1_write_pattern_29 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_29 = {
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 1, 3, 16}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 9, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 1, 3, 16}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 9, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 1, 3, 16}, .offset = {0, 0, 0, 32}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 9, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 1, 3, 16}, .offset = {0, 0, 0, 48}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 9, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_29 = 0;
+bool has_l1_wts_write_access_pattern_29 = false;
+std::vector<access_pattern> l1_wts_write_pattern_29 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_29 = {};
+
+
+std::vector<uint32_t> ofm_dim_29 = {8, 1, 12, 64};
+std::vector<uint32_t> ofm_bound_29 = {8, 1, 9, 1};
+std::vector<uint32_t> ofmsv_dim_29 = {8, 1, 3, 16};
+uint32_t ofmsv_size_29 = 384;
+uint32_t ofm_repetition_29 = 1;
+bool has_l1_read_access_pattern_29 = false;
+
+std::vector<access_pattern> l1_read_pattern_29 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_29 = {
+{
+  tiling({.buffer_dimension = {8, 1, 12, 64}, .tiling_dimension = {8, 1, 3, 16}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 12, 64}, .tiling_dimension = {8, 1, 3, 16}, .offset = {0, 0, 3, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 12, 64}, .tiling_dimension = {8, 1, 3, 16}, .offset = {0, 0, 6, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 12, 64}, .tiling_dimension = {8, 1, 3, 16}, .offset = {0, 0, 9, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 12, 64}, .tiling_dimension = {8, 1, 3, 16}, .offset = {0, 0, 0, 16}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 12, 64}, .tiling_dimension = {8, 1, 3, 16}, .offset = {0, 0, 3, 16}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 12, 64}, .tiling_dimension = {8, 1, 3, 16}, .offset = {0, 0, 6, 16}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 12, 64}, .tiling_dimension = {8, 1, 3, 16}, .offset = {0, 0, 9, 16}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 12, 64}, .tiling_dimension = {8, 1, 3, 16}, .offset = {0, 0, 0, 32}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 12, 64}, .tiling_dimension = {8, 1, 3, 16}, .offset = {0, 0, 3, 32}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 12, 64}, .tiling_dimension = {8, 1, 3, 16}, .offset = {0, 0, 6, 32}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 12, 64}, .tiling_dimension = {8, 1, 3, 16}, .offset = {0, 0, 9, 32}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 12, 64}, .tiling_dimension = {8, 1, 3, 16}, .offset = {0, 0, 0, 48}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 12, 64}, .tiling_dimension = {8, 1, 3, 16}, .offset = {0, 0, 3, 48}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 12, 64}, .tiling_dimension = {8, 1, 3, 16}, .offset = {0, 0, 6, 48}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 12, 64}, .tiling_dimension = {8, 1, 3, 16}, .offset = {0, 0, 9, 48}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 30
+// LayerName: Clip_53
+std::vector<uint32_t> ifm_dim_30 = {8, 1, 12, 64};
+std::vector<uint32_t> ifm_bound_30 = {8, 1, 9, 1};
+std::vector<uint32_t> ifmsv_dim_30 = {8, 1, 4, 8};
+uint32_t ifmsv_size_30 = 1024;
+uint32_t kernel_iter_30 = 1;
+bool has_l1_write_access_pattern_30 = false;
+std::vector<access_pattern> l1_write_pattern_30 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_30 = {
+{
+  tiling({.buffer_dimension = {8, 1, 12, 64}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 9, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 12, 64}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 9, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 12, 64}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 9, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 12, 64}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 9, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_30 = 0;
+bool has_l1_wts_write_access_pattern_30 = false;
+std::vector<access_pattern> l1_wts_write_pattern_30 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_30 = {};
+
+
+std::vector<uint32_t> ofm_dim_30 = {8, 1, 16, 32};
+std::vector<uint32_t> ofm_bound_30 = {8, 1, 9, 1};
+std::vector<uint32_t> ofmsv_dim_30 = {8, 1, 4, 8};
+uint32_t ofmsv_size_30 = 256;
+uint32_t ofm_repetition_30 = 1;
+bool has_l1_read_access_pattern_30 = false;
+
+std::vector<access_pattern> l1_read_pattern_30 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_30 = {
+{
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 4, 8}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 8, 8}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 12, 8}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 0, 16}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 4, 16}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 8, 16}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 12, 16}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 0, 24}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 4, 24}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 8, 24}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 12, 24}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 31
+// LayerName: Div_55
+std::vector<uint32_t> ifm_dim_31 = {8, 1, 16, 32};
+std::vector<uint32_t> ifm_bound_31 = {8, 1, 9, 1};
+std::vector<uint32_t> ifmsv_dim_31 = {8, 1, 4, 16};
+uint32_t ifmsv_size_31 = 2048;
+uint32_t kernel_iter_31 = 1;
+bool has_l1_write_access_pattern_31 = false;
+std::vector<access_pattern> l1_write_pattern_31 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_31 = {
+{
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 9, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 9, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 32}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 9, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 48}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 9, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_31 = 0;
+bool has_l1_wts_write_access_pattern_31 = false;
+std::vector<access_pattern> l1_wts_write_pattern_31 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_31 = {};
+
+
+std::vector<uint32_t> ofm_dim_31 = {8, 1, 16, 64};
+std::vector<uint32_t> ofm_bound_31 = {8, 1, 9, 1};
+std::vector<uint32_t> ofmsv_dim_31 = {8, 1, 4, 16};
+uint32_t ofmsv_size_31 = 512;
+uint32_t ofm_repetition_31 = 1;
+bool has_l1_read_access_pattern_31 = false;
+
+std::vector<access_pattern> l1_read_pattern_31 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_31 = {
+{
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 16}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 4, 16}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 8, 16}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 12, 16}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 32}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 4, 32}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 8, 32}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 12, 32}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 48}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 4, 48}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 8, 48}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 12, 48}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 33
+// LayerName: Mul_56
+std::vector<uint32_t> ifm_dim_33 = {8, 40, 9, 23};
+std::vector<uint32_t> ifm_bound_33 = {8, 40, 9, 23};
+std::vector<uint32_t> ifmsv_dim_33 = {8, 20, 1, 6};
+uint32_t ifmsv_size_33 = 3840;
+uint32_t kernel_iter_33 = 6;
+bool has_l1_write_access_pattern_33 = false;
+std::vector<access_pattern> l1_write_pattern_33 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_33 = {
+{
+  tiling({.buffer_dimension = {8, 40, 9, 23}, .tiling_dimension = {8, 20, 1, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 12}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 9, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 9, 23}, .tiling_dimension = {8, 20, 1, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 12}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 9, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 9, 23}, .tiling_dimension = {8, 20, 1, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 12}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 9, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 9, 23}, .tiling_dimension = {8, 20, 1, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 12}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 9, 23}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_33 = {8, 40, 12, 24};
+std::vector<uint32_t> ifm2_bound_33 = {8, 40, 9, 23};
+std::vector<uint32_t> ifm2sv_dim_33 = {8, 20, 1, 6};
+uint32_t ifm2sv_size_33 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_33 = {
+{
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 20, 1, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 12}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 9, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 20, 1, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 12}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 9, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 20, 1, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 12}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 9, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 20, 1, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 12}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 9, 23}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_33 = 0;
+bool has_l1_wts_write_access_pattern_33 = false;
+std::vector<access_pattern> l1_wts_write_pattern_33 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_33 = {};
+
+
+std::vector<uint32_t> ofm_dim_33 = {8, 40, 12, 24};
+std::vector<uint32_t> ofm_bound_33 = {8, 40, 9, 23};
+std::vector<uint32_t> ofmsv_dim_33 = {8, 20, 1, 6};
+uint32_t ofmsv_size_33 = 960;
+uint32_t ofm_repetition_33 = 1;
+bool has_l1_read_access_pattern_33 = false;
+
+std::vector<access_pattern> l1_read_pattern_33 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_33 = {
+{
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 20, 1, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 20, 1, 6}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 20, 1, 6}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 20, 1, 6}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 20, 1, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 20, 1, 6}, .offset = {0, 0, 1, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 20, 1, 6}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 20, 1, 6}, .offset = {0, 0, 3, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 20, 1, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 20, 1, 6}, .offset = {0, 0, 1, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 20, 1, 6}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 20, 1, 6}, .offset = {0, 0, 3, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 20, 1, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 20, 1, 6}, .offset = {0, 0, 1, 18}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 20, 1, 6}, .offset = {0, 0, 2, 18}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 20, 1, 6}, .offset = {0, 0, 3, 18}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 3}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 34
+// LayerName: Conv_57
+std::vector<uint32_t> ifm_dim_34 = {8, 40, 12, 24};
+std::vector<uint32_t> ifm_bound_34 = {8, 40, 9, 23};
+std::vector<uint32_t> ifmsv_dim_34 = {8, 8, 9, 6};
+uint32_t ifmsv_size_34 = 3456;
+uint32_t kernel_iter_34 = 5;
+bool has_l1_write_access_pattern_34 = false;
+std::vector<access_pattern> l1_write_pattern_34 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_34 = {
+{
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 8, 9, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 9, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 8, 9, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 9, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 8, 9, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 9, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 8, 9, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 9, 23}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_34 = {4864};
+std::vector<uint32_t> wts_dim_34 = {4864};
+std::vector<uint32_t> wtssv_dim_34 = {1216};
+uint32_t wtssv_size_34 = 1216;
+uint32_t wts_repetition_34 = 1;
+bool has_l1_wts_write_access_pattern_34 = false;
+std::vector<access_pattern> l1_wts_write_pattern_34 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_34 = {
+{
+  tiling({.buffer_dimension = {1216, 4}, .tiling_dimension = {1216, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1216, 4}, .tiling_dimension = {1216, 1}, .offset = {0, 1}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1216, 4}, .tiling_dimension = {1216, 1}, .offset = {0, 2}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1216, 4}, .tiling_dimension = {1216, 1}, .offset = {0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_34[] = {
+{
+  tiling({.buffer_dimension = {4864, 1}, .tiling_dimension = {2432, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4864, 1}, .tiling_dimension = {2432, 1}, .offset = {2432, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_34[] = {
+{
+  tiling({.buffer_dimension = {4864}, .tiling_dimension = {2432}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4864}, .tiling_dimension = {2432}, .offset = {2432}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_34 = {8, 40, 8, 24};
+std::vector<uint32_t> ofm_bound_34 = {8, 40, 5, 23};
+std::vector<uint32_t> ofmsv_dim_34 = {8, 8, 2, 6};
+uint32_t ofmsv_size_34 = 768;
+uint32_t ofm_repetition_34 = 1;
+bool has_l1_read_access_pattern_34 = false;
+
+std::vector<access_pattern> l1_read_pattern_34 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_34 = {
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 8, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 8, 2, 6}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 8, 2, 6}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 8, 2, 6}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 8, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 8, 2, 6}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 8, 2, 6}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 8, 2, 6}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 8, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 8, 2, 6}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 8, 2, 6}, .offset = {0, 0, 4, 12}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 8, 2, 6}, .offset = {0, 0, 6, 12}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 8, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 8, 2, 6}, .offset = {0, 0, 2, 18}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 8, 2, 6}, .offset = {0, 0, 4, 18}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 8, 2, 6}, .offset = {0, 0, 6, 18}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 35
+// LayerName: Conv_58
+std::vector<uint32_t> ifm_dim_35 = {8, 40, 8, 24};
+std::vector<uint32_t> ifm_bound_35 = {8, 40, 5, 23};
+std::vector<uint32_t> ifmsv_dim_35 = {8, 32, 8, 2};
+uint32_t ifmsv_size_35 = 4096;
+uint32_t kernel_iter_35 = 6;
+bool has_l1_write_access_pattern_35 = false;
+std::vector<access_pattern> l1_write_pattern_35 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_35 = {
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 32, 8, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 32, 8, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 32, 8, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 32, 8, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_35 = {8704};
+std::vector<uint32_t> wts_dim_35 = {8704};
+std::vector<uint32_t> wtssv_dim_35 = {2176};
+uint32_t wtssv_size_35 = 2176;
+uint32_t wts_repetition_35 = 1;
+bool has_l1_wts_write_access_pattern_35 = false;
+std::vector<access_pattern> l1_wts_write_pattern_35 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_35 = {
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {2176, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {2176, 1}, .offset = {0, 1}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {2176, 1}, .offset = {0, 2}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {2176, 1}, .offset = {0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_35[] = {
+{
+  tiling({.buffer_dimension = {8704, 1}, .tiling_dimension = {4352, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8704, 1}, .tiling_dimension = {4352, 1}, .offset = {4352, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_35[] = {
+{
+  tiling({.buffer_dimension = {8704}, .tiling_dimension = {4352}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8704}, .tiling_dimension = {4352}, .offset = {4352}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_35 = {8, 64, 16, 24};
+std::vector<uint32_t> ofm_bound_35 = {8, 40, 15, 23};
+std::vector<uint32_t> ofmsv_dim_35 = {8, 32, 4, 2};
+uint32_t ofmsv_size_35 = 2048;
+uint32_t ofm_repetition_35 = 1;
+bool has_l1_read_access_pattern_35 = false;
+
+std::vector<access_pattern> l1_read_pattern_35 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_35 = {
+{
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 8, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 12, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 4, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 8, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 12, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 4, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 8, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 12, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 8, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 12, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 36
+// LayerName: Conv_60
+std::vector<uint32_t> ifm_dim_36 = {8, 64, 16, 24};
+std::vector<uint32_t> ifm_bound_36 = {8, 40, 15, 23};
+std::vector<uint32_t> ifmsv_dim_36 = {8, 12, 1, 10};
+uint32_t ifmsv_size_36 = 3840;
+uint32_t kernel_iter_36 = 20;
+bool has_l1_write_access_pattern_36 = false;
+std::vector<access_pattern> l1_write_pattern_36 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_36 = {
+{
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 12, 1, 10}, .offset = {0, -2, 0, -2}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 16}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 12, 1, 10}, .offset = {0, -2, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 16}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 12, 1, 10}, .offset = {0, -2, 0, 10}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 16}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 12, 1, 10}, .offset = {0, -2, 0, 16}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 16}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_36 = {5632};
+std::vector<uint32_t> wts_dim_36 = {5632};
+std::vector<uint32_t> wtssv_dim_36 = {352};
+uint32_t wts_repetition_36 = 1;
+uint32_t wtssv_size_36 = 352;
+bool has_l1_wts_write_access_pattern_36 = false;
+std::vector<access_pattern> l1_wts_write_pattern_36 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_36 = {
+{
+  tiling({.buffer_dimension = {5632}, .tiling_dimension = {352}, .offset = {0}, .tile_traversal = { {.dimension = 0, .stride = 1408, .wrap = 4} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {5632}, .tiling_dimension = {352}, .offset = {352}, .tile_traversal = { {.dimension = 0, .stride = 1408, .wrap = 4} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {5632}, .tiling_dimension = {352}, .offset = {704}, .tile_traversal = { {.dimension = 0, .stride = 1408, .wrap = 4} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {5632}, .tiling_dimension = {352}, .offset = {1056}, .tile_traversal = { {.dimension = 0, .stride = 1408, .wrap = 4} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_36[] = {
+{
+  tiling({.buffer_dimension = {5632, 1}, .tiling_dimension = {2816, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {5632, 1}, .tiling_dimension = {2816, 1}, .offset = {2816, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_36[] = {
+{
+  tiling({.buffer_dimension = {5632}, .tiling_dimension = {2816}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {5632}, .tiling_dimension = {2816}, .offset = {2816}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_36 = {8, 40, 16, 24};
+std::vector<uint32_t> ofm_bound_36 = {8, 40, 15, 23};
+std::vector<uint32_t> ofmsv_dim_36 = {8, 8, 1, 6};
+uint32_t ofmsv_size_36 = 384;
+uint32_t ofm_repetition_36 = 1;
+bool has_l1_read_access_pattern_36 = false;
+
+std::vector<access_pattern> l1_read_pattern_36 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_36 = {
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 1, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 3, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 1, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 3, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 1, 18}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 2, 18}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 3, 18}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 38
+// LayerName: Generated-#14
+std::vector<uint32_t> ifm_dim_38 = {8, 920, 15, 1};
+std::vector<uint32_t> ifm_bound_38 = {8, 920, 15, 1};
+std::vector<uint32_t> ifmsv_dim_38 = {8, 64, 4, 1};
+uint32_t ifmsv_size_38 = 8192;
+uint32_t kernel_iter_38 = 15;
+bool has_l1_write_access_pattern_38 = false;
+std::vector<access_pattern> l1_write_pattern_38 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_38 = {
+{
+  tiling({.buffer_dimension = {8, 920, 15, 1}, .tiling_dimension = {8, 64, 4, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 64, .wrap = 15} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 920, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 920, 15, 1}, .tiling_dimension = {8, 64, 4, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 64, .wrap = 15} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 920, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 920, 15, 1}, .tiling_dimension = {8, 64, 4, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 64, .wrap = 15} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 920, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 920, 15, 1}, .tiling_dimension = {8, 64, 4, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 64, .wrap = 15} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 920, 15, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_38 = 0;
+bool has_l1_wts_write_access_pattern_38 = false;
+std::vector<access_pattern> l1_wts_write_pattern_38 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_38 = {};
+
+
+std::vector<uint32_t> ofm_dim_38 = {8, 1, 16, 4};
+std::vector<uint32_t> ofm_bound_38 = {8, 1, 15, 1};
+std::vector<uint32_t> ofmsv_dim_38 = {8, 1, 4, 1};
+uint32_t ofmsv_size_38 = 32;
+uint32_t ofm_repetition_38 = 15;
+bool has_l1_read_access_pattern_38 = false;
+std::vector<access_pattern> l1_read_pattern_38 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ofm_pattern_38 = {
+{
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 4, 1}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 8, 1}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 12, 1}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 4, 2}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 8, 2}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 12, 2}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 4, 3}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 8, 3}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 12, 3}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 39
+// LayerName: Conv_63
+std::vector<uint32_t> ifm_dim_39 = {8, 1, 16, 4};
+std::vector<uint32_t> ifm_bound_39 = {8, 1, 15, 1};
+std::vector<uint32_t> ifmsv_dim_39 = {8, 16, 15, 1};
+uint32_t ifmsv_size_39 = 1920;
+uint32_t kernel_iter_39 = 1;
+bool has_l1_write_access_pattern_39 = false;
+std::vector<access_pattern> l1_write_pattern_39 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_39 = {
+{
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 16, 15, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 16, 15, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 16, 15, 1}, .offset = {0, 32, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 16, 15, 1}, .offset = {0, 48, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_39 = {7936};
+std::vector<uint32_t> wts_dim_39 = {7936};
+std::vector<uint32_t> wtssv_dim_39 = {1984};
+uint32_t wtssv_size_39 = 1984;
+uint32_t wts_repetition_39 = 1;
+bool has_l1_wts_write_access_pattern_39 = false;
+std::vector<access_pattern> l1_wts_write_pattern_39 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_39 = {
+{
+  tiling({.buffer_dimension = {1984, 4}, .tiling_dimension = {1984, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1984, 4}, .tiling_dimension = {1984, 1}, .offset = {0, 1}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1984, 4}, .tiling_dimension = {1984, 1}, .offset = {0, 2}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1984, 4}, .tiling_dimension = {1984, 1}, .offset = {0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_39[] = {
+{
+  tiling({.buffer_dimension = {7936, 1}, .tiling_dimension = {3968, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {7936, 1}, .tiling_dimension = {3968, 1}, .offset = {3968, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_39[] = {
+{
+  tiling({.buffer_dimension = {7936}, .tiling_dimension = {3968}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {7936}, .tiling_dimension = {3968}, .offset = {3968}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_39 = {8, 64, 8, 1};
+std::vector<uint32_t> ofm_bound_39 = {8, 1, 4, 1};
+std::vector<uint32_t> ofmsv_dim_39 = {8, 16, 2, 1};
+uint32_t ofmsv_size_39 = 256;
+uint32_t ofm_repetition_39 = 1;
+bool has_l1_read_access_pattern_39 = false;
+
+std::vector<access_pattern> l1_read_pattern_39 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_39 = {
+{
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 2, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 6, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 2, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 4, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 6, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 2, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 4, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 6, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 2, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 4, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 6, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 40
+// LayerName: Conv_65
+std::vector<uint32_t> ifm_dim_40 = {8, 64, 8, 1};
+std::vector<uint32_t> ifm_bound_40 = {8, 1, 4, 1};
+std::vector<uint32_t> ifmsv_dim_40 = {8, 8, 8, 1};
+uint32_t ifmsv_size_40 = 512;
+uint32_t kernel_iter_40 = 1;
+bool has_l1_write_access_pattern_40 = false;
+std::vector<access_pattern> l1_write_pattern_40 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_40 = {
+{
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 8, 8, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 4, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 8, 8, 1}, .offset = {0, 8, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 4, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 8, 8, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 4, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 8, 8, 1}, .offset = {0, 24, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 4, 1}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_40 = {8704};
+std::vector<uint32_t> wts_dim_40 = {8704};
+std::vector<uint32_t> wtssv_dim_40 = {2176};
+uint32_t wtssv_size_40 = 2176;
+uint32_t wts_repetition_40 = 1;
+bool has_l1_wts_write_access_pattern_40 = false;
+std::vector<access_pattern> l1_wts_write_pattern_40 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_40 = {
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {2176, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {2176, 1}, .offset = {0, 1}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {2176, 1}, .offset = {0, 2}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {2176, 1}, .offset = {0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_40[] = {
+{
+  tiling({.buffer_dimension = {8704, 1}, .tiling_dimension = {4352, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8704, 1}, .tiling_dimension = {4352, 1}, .offset = {4352, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_40[] = {
+{
+  tiling({.buffer_dimension = {8704}, .tiling_dimension = {4352}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8704}, .tiling_dimension = {4352}, .offset = {4352}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_40 = {8, 32, 16, 1};
+std::vector<uint32_t> ofm_bound_40 = {8, 1, 15, 1};
+std::vector<uint32_t> ofmsv_dim_40 = {8, 8, 4, 1};
+uint32_t ofmsv_size_40 = 256;
+uint32_t ofm_repetition_40 = 1;
+bool has_l1_read_access_pattern_40 = false;
+
+std::vector<access_pattern> l1_read_pattern_40 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_40 = {
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 0, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 0, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 8, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 8, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 8, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 8, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 16, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 16, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 16, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 24, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 24, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 24, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 24, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 41
+// LayerName: Add_67
+std::vector<uint32_t> ifm_dim_41 = {8, 32, 16, 1};
+std::vector<uint32_t> ifm_bound_41 = {8, 1, 15, 1};
+std::vector<uint32_t> ifmsv_dim_41 = {8, 1, 4, 12};
+uint32_t ifmsv_size_41 = 1536;
+uint32_t kernel_iter_41 = 1;
+bool has_l1_write_access_pattern_41 = false;
+std::vector<access_pattern> l1_write_pattern_41 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_41 = {
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_41 = 0;
+bool has_l1_wts_write_access_pattern_41 = false;
+std::vector<access_pattern> l1_wts_write_pattern_41 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_41 = {};
+
+
+std::vector<uint32_t> ofm_dim_41 = {8, 1, 16, 48};
+std::vector<uint32_t> ofm_bound_41 = {8, 1, 15, 1};
+std::vector<uint32_t> ofmsv_dim_41 = {8, 1, 4, 12};
+uint32_t ofmsv_size_41 = 384;
+uint32_t ofm_repetition_41 = 1;
+bool has_l1_read_access_pattern_41 = false;
+
+std::vector<access_pattern> l1_read_pattern_41 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_41 = {
+{
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 4, 12}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 8, 12}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 12, 12}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 4, 24}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 8, 24}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 12, 24}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 4, 36}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 8, 36}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 12, 36}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 42
+// LayerName: Clip_70
+std::vector<uint32_t> ifm_dim_42 = {8, 1, 16, 48};
+std::vector<uint32_t> ifm_bound_42 = {8, 1, 15, 1};
+std::vector<uint32_t> ifmsv_dim_42 = {8, 1, 4, 8};
+uint32_t ifmsv_size_42 = 1024;
+uint32_t kernel_iter_42 = 1;
+bool has_l1_write_access_pattern_42 = false;
+std::vector<access_pattern> l1_write_pattern_42 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_42 = {
+{
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_42 = 0;
+bool has_l1_wts_write_access_pattern_42 = false;
+std::vector<access_pattern> l1_wts_write_pattern_42 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_42 = {};
+
+
+std::vector<uint32_t> ofm_dim_42 = {8, 1, 16, 32};
+std::vector<uint32_t> ofm_bound_42 = {8, 1, 15, 1};
+std::vector<uint32_t> ofmsv_dim_42 = {8, 1, 4, 8};
+uint32_t ofmsv_size_42 = 256;
+uint32_t ofm_repetition_42 = 1;
+bool has_l1_read_access_pattern_42 = false;
+
+std::vector<access_pattern> l1_read_pattern_42 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_42 = {
+{
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 4, 8}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 8, 8}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 12, 8}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 0, 16}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 4, 16}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 8, 16}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 12, 16}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 0, 24}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 4, 24}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 8, 24}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 12, 24}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 43
+// LayerName: Div_72
+std::vector<uint32_t> ifm_dim_43 = {8, 1, 16, 32};
+std::vector<uint32_t> ifm_bound_43 = {8, 1, 15, 1};
+std::vector<uint32_t> ifmsv_dim_43 = {8, 1, 4, 16};
+uint32_t ifmsv_size_43 = 2048;
+uint32_t kernel_iter_43 = 1;
+bool has_l1_write_access_pattern_43 = false;
+std::vector<access_pattern> l1_write_pattern_43 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_43 = {
+{
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 32}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 48}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_43 = 0;
+bool has_l1_wts_write_access_pattern_43 = false;
+std::vector<access_pattern> l1_wts_write_pattern_43 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_43 = {};
+
+
+std::vector<uint32_t> ofm_dim_43 = {8, 1, 16, 64};
+std::vector<uint32_t> ofm_bound_43 = {8, 1, 15, 1};
+std::vector<uint32_t> ofmsv_dim_43 = {8, 1, 4, 16};
+uint32_t ofmsv_size_43 = 512;
+uint32_t ofm_repetition_43 = 1;
+bool has_l1_read_access_pattern_43 = false;
+
+std::vector<access_pattern> l1_read_pattern_43 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_43 = {
+{
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 16}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 4, 16}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 8, 16}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 12, 16}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 32}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 4, 32}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 8, 32}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 12, 32}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 48}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 4, 48}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 8, 48}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 12, 48}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 45
+// LayerName: Mul_73
+std::vector<uint32_t> ifm_dim_45 = {8, 40, 15, 23};
+std::vector<uint32_t> ifm_bound_45 = {8, 40, 15, 23};
+std::vector<uint32_t> ifmsv_dim_45 = {8, 10, 2, 6};
+uint32_t ifmsv_size_45 = 3840;
+uint32_t kernel_iter_45 = 8;
+bool has_l1_write_access_pattern_45 = false;
+std::vector<access_pattern> l1_write_pattern_45 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_45 = {
+{
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 8}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 8}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 8}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 8}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_45 = {8, 40, 16, 24};
+std::vector<uint32_t> ifm2_bound_45 = {8, 40, 15, 23};
+std::vector<uint32_t> ifm2sv_dim_45 = {8, 10, 2, 6};
+uint32_t ifm2sv_size_45 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_45 = {
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 8}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 8}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 8}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 8}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_45 = 0;
+bool has_l1_wts_write_access_pattern_45 = false;
+std::vector<access_pattern> l1_wts_write_pattern_45 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_45 = {};
+
+
+std::vector<uint32_t> ofm_dim_45 = {8, 40, 16, 24};
+std::vector<uint32_t> ofm_bound_45 = {8, 40, 15, 23};
+std::vector<uint32_t> ofmsv_dim_45 = {8, 10, 2, 6};
+uint32_t ofmsv_size_45 = 960;
+uint32_t ofm_repetition_45 = 1;
+bool has_l1_read_access_pattern_45 = false;
+
+std::vector<access_pattern> l1_read_pattern_45 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_45 = {
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 12}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 12}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 18}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 18}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 18}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 46
+// LayerName: Conv_74
+std::vector<uint32_t> ifm_dim_46 = {8, 40, 16, 24};
+std::vector<uint32_t> ifm_bound_46 = {8, 40, 15, 23};
+std::vector<uint32_t> ifmsv_dim_46 = {8, 40, 8, 1};
+uint32_t ifmsv_size_46 = 2560;
+uint32_t kernel_iter_46 = 12;
+bool has_l1_write_access_pattern_46 = false;
+std::vector<access_pattern> l1_write_pattern_46 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_46 = {
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 40, 8, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 40, 8, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 40, 8, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 40, 8, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_46 = {8, 40, 8, 24};
+std::vector<uint32_t> ifm2_bound_46 = {8, 40, 5, 23};
+std::vector<uint32_t> ifm2sv_dim_46 = {8, 40, 2, 1};
+uint32_t ifm2sv_size_46 = 2560;
+std::vector<std::vector<access_pattern>> ifm2_pattern_46 = {
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_46 = {8704};
+std::vector<uint32_t> wts_dim_46 = {8704};
+std::vector<uint32_t> wtssv_dim_46 = {1088};
+uint32_t wtssv_size_46 = 1088;
+uint32_t wts_repetition_46 = 1;
+bool has_l1_wts_write_access_pattern_46 = false;
+std::vector<access_pattern> l1_wts_write_pattern_46 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_46 = {
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {1088, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 1088, .wrap = 2} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {1088, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 1088, .wrap = 2} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {1088, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 1088, .wrap = 2} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {1088, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 1088, .wrap = 2} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_46[] = {
+{
+  tiling({.buffer_dimension = {8704, 1}, .tiling_dimension = {4352, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8704, 1}, .tiling_dimension = {4352, 1}, .offset = {4352, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_46[] = {
+{
+  tiling({.buffer_dimension = {8704}, .tiling_dimension = {4352}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8704}, .tiling_dimension = {4352}, .offset = {4352}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_46 = {8, 40, 8, 24};
+std::vector<uint32_t> ofm_bound_46 = {8, 40, 5, 23};
+std::vector<uint32_t> ofmsv_dim_46 = {8, 40, 2, 1};
+uint32_t ofmsv_size_46 = 640;
+uint32_t ofm_repetition_46 = 2;
+bool has_l1_read_access_pattern_46 = false;
+
+std::vector<access_pattern> l1_read_pattern_46 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_46 = {
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 2, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 4, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 6, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 2, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 4, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 6, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 47
+// LayerName: Conv_76
+std::vector<uint32_t> ifm_dim_47 = {8, 40, 8, 24};
+std::vector<uint32_t> ifm_bound_47 = {8, 40, 5, 23};
+std::vector<uint32_t> ifmsv_dim_47 = {8, 32, 8, 2};
+uint32_t ifmsv_size_47 = 4096;
+uint32_t kernel_iter_47 = 6;
+bool has_l1_write_access_pattern_47 = false;
+std::vector<access_pattern> l1_write_pattern_47 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_47 = {
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 32, 8, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 32, 8, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 32, 8, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 32, 8, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_47 = {8704};
+std::vector<uint32_t> wts_dim_47 = {8704};
+std::vector<uint32_t> wtssv_dim_47 = {2176};
+uint32_t wtssv_size_47 = 2176;
+uint32_t wts_repetition_47 = 1;
+bool has_l1_wts_write_access_pattern_47 = false;
+std::vector<access_pattern> l1_wts_write_pattern_47 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_47 = {
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {2176, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {2176, 1}, .offset = {0, 1}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {2176, 1}, .offset = {0, 2}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {2176, 1}, .offset = {0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_47[] = {
+{
+  tiling({.buffer_dimension = {8704, 1}, .tiling_dimension = {4352, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8704, 1}, .tiling_dimension = {4352, 1}, .offset = {4352, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_47[] = {
+{
+  tiling({.buffer_dimension = {8704}, .tiling_dimension = {4352}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8704}, .tiling_dimension = {4352}, .offset = {4352}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_47 = {8, 64, 16, 24};
+std::vector<uint32_t> ofm_bound_47 = {8, 40, 15, 23};
+std::vector<uint32_t> ofmsv_dim_47 = {8, 32, 4, 2};
+uint32_t ofmsv_size_47 = 2048;
+uint32_t ofm_repetition_47 = 1;
+bool has_l1_read_access_pattern_47 = false;
+
+std::vector<access_pattern> l1_read_pattern_47 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_47 = {
+{
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 8, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 12, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 4, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 8, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 12, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 4, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 8, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 12, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 8, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 12, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 48
+// LayerName: Conv_78
+std::vector<uint32_t> ifm_dim_48 = {8, 64, 16, 24};
+std::vector<uint32_t> ifm_bound_48 = {8, 40, 15, 23};
+std::vector<uint32_t> ifmsv_dim_48 = {8, 12, 1, 10};
+uint32_t ifmsv_size_48 = 3840;
+uint32_t kernel_iter_48 = 20;
+bool has_l1_write_access_pattern_48 = false;
+std::vector<access_pattern> l1_write_pattern_48 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_48 = {
+{
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 12, 1, 10}, .offset = {0, -2, 0, -2}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 16}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 12, 1, 10}, .offset = {0, -2, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 16}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 12, 1, 10}, .offset = {0, -2, 0, 10}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 16}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 16, 24}, .tiling_dimension = {8, 12, 1, 10}, .offset = {0, -2, 0, 16}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 16}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_48 = {5632};
+std::vector<uint32_t> wts_dim_48 = {5632};
+std::vector<uint32_t> wtssv_dim_48 = {352};
+uint32_t wts_repetition_48 = 1;
+uint32_t wtssv_size_48 = 352;
+bool has_l1_wts_write_access_pattern_48 = false;
+std::vector<access_pattern> l1_wts_write_pattern_48 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_48 = {
+{
+  tiling({.buffer_dimension = {5632}, .tiling_dimension = {352}, .offset = {0}, .tile_traversal = { {.dimension = 0, .stride = 1408, .wrap = 4} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {5632}, .tiling_dimension = {352}, .offset = {352}, .tile_traversal = { {.dimension = 0, .stride = 1408, .wrap = 4} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {5632}, .tiling_dimension = {352}, .offset = {704}, .tile_traversal = { {.dimension = 0, .stride = 1408, .wrap = 4} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {5632}, .tiling_dimension = {352}, .offset = {1056}, .tile_traversal = { {.dimension = 0, .stride = 1408, .wrap = 4} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_48[] = {
+{
+  tiling({.buffer_dimension = {5632, 1}, .tiling_dimension = {2816, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {5632, 1}, .tiling_dimension = {2816, 1}, .offset = {2816, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_48[] = {
+{
+  tiling({.buffer_dimension = {5632}, .tiling_dimension = {2816}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {5632}, .tiling_dimension = {2816}, .offset = {2816}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_48 = {8, 40, 16, 24};
+std::vector<uint32_t> ofm_bound_48 = {8, 40, 15, 23};
+std::vector<uint32_t> ofmsv_dim_48 = {8, 8, 1, 6};
+uint32_t ofmsv_size_48 = 384;
+uint32_t ofm_repetition_48 = 1;
+bool has_l1_read_access_pattern_48 = false;
+
+std::vector<access_pattern> l1_read_pattern_48 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_48 = {
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 1, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 3, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 1, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 3, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 1, 18}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 2, 18}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 3, 18}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 50
+// LayerName: Generated-#20
+std::vector<uint32_t> ifm_dim_50 = {8, 920, 15, 1};
+std::vector<uint32_t> ifm_bound_50 = {8, 920, 15, 1};
+std::vector<uint32_t> ifmsv_dim_50 = {8, 64, 4, 1};
+uint32_t ifmsv_size_50 = 8192;
+uint32_t kernel_iter_50 = 15;
+bool has_l1_write_access_pattern_50 = false;
+std::vector<access_pattern> l1_write_pattern_50 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_50 = {
+{
+  tiling({.buffer_dimension = {8, 920, 15, 1}, .tiling_dimension = {8, 64, 4, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 64, .wrap = 15} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 920, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 920, 15, 1}, .tiling_dimension = {8, 64, 4, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 64, .wrap = 15} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 920, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 920, 15, 1}, .tiling_dimension = {8, 64, 4, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 64, .wrap = 15} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 920, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 920, 15, 1}, .tiling_dimension = {8, 64, 4, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 1, .stride = 64, .wrap = 15} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 920, 15, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_50 = 0;
+bool has_l1_wts_write_access_pattern_50 = false;
+std::vector<access_pattern> l1_wts_write_pattern_50 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_50 = {};
+
+
+std::vector<uint32_t> ofm_dim_50 = {8, 1, 16, 4};
+std::vector<uint32_t> ofm_bound_50 = {8, 1, 15, 1};
+std::vector<uint32_t> ofmsv_dim_50 = {8, 1, 4, 1};
+uint32_t ofmsv_size_50 = 32;
+uint32_t ofm_repetition_50 = 15;
+bool has_l1_read_access_pattern_50 = false;
+std::vector<access_pattern> l1_read_pattern_50 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ofm_pattern_50 = {
+{
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 4, 1}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 8, 1}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 12, 1}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 4, 2}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 8, 2}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 12, 2}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 4, 3}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 8, 3}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 1, 4, 1}, .offset = {0, 0, 12, 3}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 51
+// LayerName: Conv_81
+std::vector<uint32_t> ifm_dim_51 = {8, 1, 16, 4};
+std::vector<uint32_t> ifm_bound_51 = {8, 1, 15, 1};
+std::vector<uint32_t> ifmsv_dim_51 = {8, 16, 15, 1};
+uint32_t ifmsv_size_51 = 1920;
+uint32_t kernel_iter_51 = 1;
+bool has_l1_write_access_pattern_51 = false;
+std::vector<access_pattern> l1_write_pattern_51 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_51 = {
+{
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 16, 15, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 16, 15, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 16, 15, 1}, .offset = {0, 32, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 4}, .tiling_dimension = {8, 16, 15, 1}, .offset = {0, 48, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_51 = {7936};
+std::vector<uint32_t> wts_dim_51 = {7936};
+std::vector<uint32_t> wtssv_dim_51 = {1984};
+uint32_t wtssv_size_51 = 1984;
+uint32_t wts_repetition_51 = 1;
+bool has_l1_wts_write_access_pattern_51 = false;
+std::vector<access_pattern> l1_wts_write_pattern_51 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_51 = {
+{
+  tiling({.buffer_dimension = {1984, 4}, .tiling_dimension = {1984, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1984, 4}, .tiling_dimension = {1984, 1}, .offset = {0, 1}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1984, 4}, .tiling_dimension = {1984, 1}, .offset = {0, 2}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1984, 4}, .tiling_dimension = {1984, 1}, .offset = {0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_51[] = {
+{
+  tiling({.buffer_dimension = {7936, 1}, .tiling_dimension = {3968, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {7936, 1}, .tiling_dimension = {3968, 1}, .offset = {3968, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_51[] = {
+{
+  tiling({.buffer_dimension = {7936}, .tiling_dimension = {3968}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {7936}, .tiling_dimension = {3968}, .offset = {3968}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_51 = {8, 64, 8, 1};
+std::vector<uint32_t> ofm_bound_51 = {8, 1, 4, 1};
+std::vector<uint32_t> ofmsv_dim_51 = {8, 16, 2, 1};
+uint32_t ofmsv_size_51 = 256;
+uint32_t ofm_repetition_51 = 1;
+bool has_l1_read_access_pattern_51 = false;
+
+std::vector<access_pattern> l1_read_pattern_51 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_51 = {
+{
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 2, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 6, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 2, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 4, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 6, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 2, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 4, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 6, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 2, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 4, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 6, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 52
+// LayerName: Conv_83
+std::vector<uint32_t> ifm_dim_52 = {8, 64, 8, 1};
+std::vector<uint32_t> ifm_bound_52 = {8, 1, 4, 1};
+std::vector<uint32_t> ifmsv_dim_52 = {8, 8, 8, 1};
+uint32_t ifmsv_size_52 = 512;
+uint32_t kernel_iter_52 = 1;
+bool has_l1_write_access_pattern_52 = false;
+std::vector<access_pattern> l1_write_pattern_52 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_52 = {
+{
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 8, 8, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 4, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 8, 8, 1}, .offset = {0, 8, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 4, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 8, 8, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 4, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 8, 1}, .tiling_dimension = {8, 8, 8, 1}, .offset = {0, 24, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 4, 1}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_52 = {8704};
+std::vector<uint32_t> wts_dim_52 = {8704};
+std::vector<uint32_t> wtssv_dim_52 = {2176};
+uint32_t wtssv_size_52 = 2176;
+uint32_t wts_repetition_52 = 1;
+bool has_l1_wts_write_access_pattern_52 = false;
+std::vector<access_pattern> l1_wts_write_pattern_52 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_52 = {
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {2176, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {2176, 1}, .offset = {0, 1}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {2176, 1}, .offset = {0, 2}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {2176, 1}, .offset = {0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_52[] = {
+{
+  tiling({.buffer_dimension = {8704, 1}, .tiling_dimension = {4352, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8704, 1}, .tiling_dimension = {4352, 1}, .offset = {4352, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_52[] = {
+{
+  tiling({.buffer_dimension = {8704}, .tiling_dimension = {4352}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8704}, .tiling_dimension = {4352}, .offset = {4352}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_52 = {8, 32, 16, 1};
+std::vector<uint32_t> ofm_bound_52 = {8, 1, 15, 1};
+std::vector<uint32_t> ofmsv_dim_52 = {8, 8, 4, 1};
+uint32_t ofmsv_size_52 = 256;
+uint32_t ofm_repetition_52 = 1;
+bool has_l1_read_access_pattern_52 = false;
+
+std::vector<access_pattern> l1_read_pattern_52 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_52 = {
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 0, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 0, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 8, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 8, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 8, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 8, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 16, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 16, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 16, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 24, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 24, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 24, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 24, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 53
+// LayerName: Add_85
+std::vector<uint32_t> ifm_dim_53 = {8, 32, 16, 1};
+std::vector<uint32_t> ifm_bound_53 = {8, 1, 15, 1};
+std::vector<uint32_t> ifmsv_dim_53 = {8, 1, 4, 12};
+uint32_t ifmsv_size_53 = 1536;
+uint32_t kernel_iter_53 = 1;
+bool has_l1_write_access_pattern_53 = false;
+std::vector<access_pattern> l1_write_pattern_53 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_53 = {
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_53 = 0;
+bool has_l1_wts_write_access_pattern_53 = false;
+std::vector<access_pattern> l1_wts_write_pattern_53 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_53 = {};
+
+
+std::vector<uint32_t> ofm_dim_53 = {8, 1, 16, 48};
+std::vector<uint32_t> ofm_bound_53 = {8, 1, 15, 1};
+std::vector<uint32_t> ofmsv_dim_53 = {8, 1, 4, 12};
+uint32_t ofmsv_size_53 = 384;
+uint32_t ofm_repetition_53 = 1;
+bool has_l1_read_access_pattern_53 = false;
+
+std::vector<access_pattern> l1_read_pattern_53 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_53 = {
+{
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 4, 12}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 8, 12}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 12, 12}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 4, 24}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 8, 24}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 12, 24}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 4, 36}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 8, 36}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 12}, .offset = {0, 0, 12, 36}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 54
+// LayerName: Clip_88
+std::vector<uint32_t> ifm_dim_54 = {8, 1, 16, 48};
+std::vector<uint32_t> ifm_bound_54 = {8, 1, 15, 1};
+std::vector<uint32_t> ifmsv_dim_54 = {8, 1, 4, 8};
+uint32_t ifmsv_size_54 = 1024;
+uint32_t kernel_iter_54 = 1;
+bool has_l1_write_access_pattern_54 = false;
+std::vector<access_pattern> l1_write_pattern_54 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_54 = {
+{
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 48}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_54 = 0;
+bool has_l1_wts_write_access_pattern_54 = false;
+std::vector<access_pattern> l1_wts_write_pattern_54 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_54 = {};
+
+
+std::vector<uint32_t> ofm_dim_54 = {8, 1, 16, 32};
+std::vector<uint32_t> ofm_bound_54 = {8, 1, 15, 1};
+std::vector<uint32_t> ofmsv_dim_54 = {8, 1, 4, 8};
+uint32_t ofmsv_size_54 = 256;
+uint32_t ofm_repetition_54 = 1;
+bool has_l1_read_access_pattern_54 = false;
+
+std::vector<access_pattern> l1_read_pattern_54 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_54 = {
+{
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 4, 8}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 8, 8}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 12, 8}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 0, 16}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 4, 16}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 8, 16}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 12, 16}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 0, 24}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 4, 24}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 8, 24}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 8}, .offset = {0, 0, 12, 24}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 55
+// LayerName: Div_90
+std::vector<uint32_t> ifm_dim_55 = {8, 1, 16, 32};
+std::vector<uint32_t> ifm_bound_55 = {8, 1, 15, 1};
+std::vector<uint32_t> ifmsv_dim_55 = {8, 1, 4, 16};
+uint32_t ifmsv_size_55 = 2048;
+uint32_t kernel_iter_55 = 1;
+bool has_l1_write_access_pattern_55 = false;
+std::vector<access_pattern> l1_write_pattern_55 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_55 = {
+{
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 32}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 32}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 48}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_55 = 0;
+bool has_l1_wts_write_access_pattern_55 = false;
+std::vector<access_pattern> l1_wts_write_pattern_55 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_55 = {};
+
+
+std::vector<uint32_t> ofm_dim_55 = {8, 1, 16, 64};
+std::vector<uint32_t> ofm_bound_55 = {8, 1, 15, 1};
+std::vector<uint32_t> ofmsv_dim_55 = {8, 1, 4, 16};
+uint32_t ofmsv_size_55 = 512;
+uint32_t ofm_repetition_55 = 1;
+bool has_l1_read_access_pattern_55 = false;
+
+std::vector<access_pattern> l1_read_pattern_55 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_55 = {
+{
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 16}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 4, 16}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 8, 16}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 12, 16}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 32}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 4, 32}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 8, 32}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 12, 32}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 48}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 4, 48}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 8, 48}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 12, 48}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 57
+// LayerName: Mul_91
+std::vector<uint32_t> ifm_dim_57 = {8, 40, 15, 23};
+std::vector<uint32_t> ifm_bound_57 = {8, 40, 15, 23};
+std::vector<uint32_t> ifmsv_dim_57 = {8, 10, 2, 6};
+uint32_t ifmsv_size_57 = 3840;
+uint32_t kernel_iter_57 = 8;
+bool has_l1_write_access_pattern_57 = false;
+std::vector<access_pattern> l1_write_pattern_57 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_57 = {
+{
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 8}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 8}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 8}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 15, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 8}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_57 = {8, 40, 16, 24};
+std::vector<uint32_t> ifm2_bound_57 = {8, 40, 15, 23};
+std::vector<uint32_t> ifm2sv_dim_57 = {8, 10, 2, 6};
+uint32_t ifm2sv_size_57 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_57 = {
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 8}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 8}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 8}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 8}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_57 = 0;
+bool has_l1_wts_write_access_pattern_57 = false;
+std::vector<access_pattern> l1_wts_write_pattern_57 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_57 = {};
+
+
+std::vector<uint32_t> ofm_dim_57 = {8, 40, 16, 24};
+std::vector<uint32_t> ofm_bound_57 = {8, 40, 15, 23};
+std::vector<uint32_t> ofmsv_dim_57 = {8, 10, 2, 6};
+uint32_t ofmsv_size_57 = 960;
+uint32_t ofm_repetition_57 = 1;
+bool has_l1_read_access_pattern_57 = false;
+
+std::vector<access_pattern> l1_read_pattern_57 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_57 = {
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 12}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 12}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 18}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 18}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 18}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 58
+// LayerName: Conv_92
+std::vector<uint32_t> ifm_dim_58 = {8, 40, 16, 24};
+std::vector<uint32_t> ifm_bound_58 = {8, 40, 15, 23};
+std::vector<uint32_t> ifmsv_dim_58 = {8, 40, 8, 1};
+uint32_t ifmsv_size_58 = 2560;
+uint32_t kernel_iter_58 = 12;
+bool has_l1_write_access_pattern_58 = false;
+std::vector<access_pattern> l1_write_pattern_58 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_58 = {
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 40, 8, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 40, 8, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 40, 8, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 16, 24}, .tiling_dimension = {8, 40, 8, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 15, 23}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_58 = {8, 40, 8, 24};
+std::vector<uint32_t> ifm2_bound_58 = {8, 40, 5, 23};
+std::vector<uint32_t> ifm2sv_dim_58 = {8, 40, 2, 1};
+uint32_t ifm2sv_size_58 = 2560;
+std::vector<std::vector<access_pattern>> ifm2_pattern_58 = {
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_58 = {8704};
+std::vector<uint32_t> wts_dim_58 = {8704};
+std::vector<uint32_t> wtssv_dim_58 = {1088};
+uint32_t wtssv_size_58 = 1088;
+uint32_t wts_repetition_58 = 1;
+bool has_l1_wts_write_access_pattern_58 = false;
+std::vector<access_pattern> l1_wts_write_pattern_58 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_58 = {
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {1088, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 1088, .wrap = 2} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {1088, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 1088, .wrap = 2} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {1088, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 1088, .wrap = 2} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176, 4}, .tiling_dimension = {1088, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 1088, .wrap = 2} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_58[] = {
+{
+  tiling({.buffer_dimension = {8704, 1}, .tiling_dimension = {4352, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8704, 1}, .tiling_dimension = {4352, 1}, .offset = {4352, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_58[] = {
+{
+  tiling({.buffer_dimension = {8704}, .tiling_dimension = {4352}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8704}, .tiling_dimension = {4352}, .offset = {4352}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_58 = {8, 40, 8, 24};
+std::vector<uint32_t> ofm_bound_58 = {8, 40, 5, 23};
+std::vector<uint32_t> ofmsv_dim_58 = {8, 40, 2, 1};
+uint32_t ofmsv_size_58 = 640;
+uint32_t ofm_repetition_58 = 2;
+bool has_l1_read_access_pattern_58 = false;
+
+std::vector<access_pattern> l1_read_pattern_58 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_58 = {
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 2, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 4, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 6, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 2, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 4, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 6, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 40, 2, 1}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 59
+// LayerName: Conv_94
+std::vector<uint32_t> ifm_dim_59 = {8, 40, 8, 24};
+std::vector<uint32_t> ifm_bound_59 = {8, 40, 5, 23};
+std::vector<uint32_t> ifmsv_dim_59 = {8, 32, 8, 2};
+uint32_t ifmsv_size_59 = 4096;
+uint32_t kernel_iter_59 = 12;
+bool has_l1_write_access_pattern_59 = false;
+std::vector<access_pattern> l1_write_pattern_59 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_59 = {
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 32, 8, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 32, 8, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 32, 8, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 32, 8, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_59 = {17408};
+std::vector<uint32_t> wts_dim_59 = {17408};
+std::vector<uint32_t> wtssv_dim_59 = {2176};
+uint32_t wtssv_size_59 = 2176;
+uint32_t wts_repetition_59 = 1;
+bool has_l1_wts_write_access_pattern_59 = false;
+std::vector<access_pattern> l1_wts_write_pattern_59 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_59 = {
+{
+  tiling({.buffer_dimension = {2176, 8}, .tiling_dimension = {2176, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {2176, 8}, .tiling_dimension = {2176, 1}, .offset = {0, 4}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176, 8}, .tiling_dimension = {2176, 1}, .offset = {0, 1}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {2176, 8}, .tiling_dimension = {2176, 1}, .offset = {0, 5}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176, 8}, .tiling_dimension = {2176, 1}, .offset = {0, 2}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {2176, 8}, .tiling_dimension = {2176, 1}, .offset = {0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176, 8}, .tiling_dimension = {2176, 1}, .offset = {0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {2176, 8}, .tiling_dimension = {2176, 1}, .offset = {0, 7}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_59[] = {
+{
+  tiling({.buffer_dimension = {17408, 1}, .tiling_dimension = {8704, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {17408, 1}, .tiling_dimension = {8704, 1}, .offset = {8704, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_59[] = {
+{
+  tiling({.buffer_dimension = {17408}, .tiling_dimension = {8704}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {17408}, .tiling_dimension = {8704}, .offset = {8704}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_59 = {8, 64, 32, 24};
+std::vector<uint32_t> ofm_bound_59 = {8, 40, 30, 23};
+std::vector<uint32_t> ofmsv_dim_59 = {8, 32, 4, 2};
+uint32_t ofmsv_size_59 = 2048;
+uint32_t ofm_repetition_59 = 1;
+bool has_l1_read_access_pattern_59 = false;
+
+std::vector<access_pattern> l1_read_pattern_59 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_59 = {
+{
+  tiling({.buffer_dimension = {8, 64, 32, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 8, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 12, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 32, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 4, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 8, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 12, 2}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 32, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 4, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 8, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 12, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 32, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 8, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 24}, .tiling_dimension = {8, 32, 4, 2}, .offset = {0, 0, 12, 6}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 2}, {.dimension = 3, .stride = 8, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 60
+// LayerName: Add_96
+std::vector<uint32_t> ifm_dim_60 = {8, 64, 32, 24};
+std::vector<uint32_t> ifm_bound_60 = {8, 40, 30, 23};
+std::vector<uint32_t> ifmsv_dim_60 = {8, 20, 2, 6};
+uint32_t ifmsv_size_60 = 7680;
+uint32_t kernel_iter_60 = 8;
+bool has_l1_write_access_pattern_60 = false;
+std::vector<access_pattern> l1_write_pattern_60 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_60 = {
+{
+  tiling({.buffer_dimension = {8, 64, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 30, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 30, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 30, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 30, 23}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_60 = 0;
+bool has_l1_wts_write_access_pattern_60 = false;
+std::vector<access_pattern> l1_wts_write_pattern_60 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_60 = {};
+
+
+std::vector<uint32_t> ofm_dim_60 = {8, 40, 32, 24};
+std::vector<uint32_t> ofm_bound_60 = {8, 40, 30, 23};
+std::vector<uint32_t> ofmsv_dim_60 = {8, 20, 2, 6};
+uint32_t ofmsv_size_60 = 1920;
+uint32_t ofm_repetition_60 = 1;
+bool has_l1_read_access_pattern_60 = false;
+
+std::vector<access_pattern> l1_read_pattern_60 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_60 = {
+{
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 4, 12}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 6, 12}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 2, 18}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 4, 18}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 6, 18}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 61
+// LayerName: Clip_99
+std::vector<uint32_t> ifm_dim_61 = {8, 40, 32, 24};
+std::vector<uint32_t> ifm_bound_61 = {8, 40, 30, 23};
+std::vector<uint32_t> ifmsv_dim_61 = {8, 20, 2, 6};
+uint32_t ifmsv_size_61 = 7680;
+uint32_t kernel_iter_61 = 8;
+bool has_l1_write_access_pattern_61 = false;
+std::vector<access_pattern> l1_write_pattern_61 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_61 = {
+{
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 30, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 30, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 30, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 30, 23}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_61 = 0;
+bool has_l1_wts_write_access_pattern_61 = false;
+std::vector<access_pattern> l1_wts_write_pattern_61 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_61 = {};
+
+
+std::vector<uint32_t> ofm_dim_61 = {8, 40, 32, 24};
+std::vector<uint32_t> ofm_bound_61 = {8, 40, 30, 23};
+std::vector<uint32_t> ofmsv_dim_61 = {8, 20, 2, 6};
+uint32_t ofmsv_size_61 = 1920;
+uint32_t ofm_repetition_61 = 1;
+bool has_l1_read_access_pattern_61 = false;
+
+std::vector<access_pattern> l1_read_pattern_61 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_61 = {
+{
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 4, 12}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 6, 12}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 2, 18}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 4, 18}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 6, 18}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 62
+// LayerName: Div_101
+std::vector<uint32_t> ifm_dim_62 = {8, 40, 32, 24};
+std::vector<uint32_t> ifm_bound_62 = {8, 40, 30, 23};
+std::vector<uint32_t> ifmsv_dim_62 = {8, 20, 2, 6};
+uint32_t ifmsv_size_62 = 7680;
+uint32_t kernel_iter_62 = 8;
+bool has_l1_write_access_pattern_62 = false;
+std::vector<access_pattern> l1_write_pattern_62 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_62 = {
+{
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 30, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 30, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 30, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 30, 23}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_62 = 0;
+bool has_l1_wts_write_access_pattern_62 = false;
+std::vector<access_pattern> l1_wts_write_pattern_62 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_62 = {};
+
+
+std::vector<uint32_t> ofm_dim_62 = {8, 40, 32, 24};
+std::vector<uint32_t> ofm_bound_62 = {8, 40, 30, 23};
+std::vector<uint32_t> ofmsv_dim_62 = {8, 20, 2, 6};
+uint32_t ofmsv_size_62 = 1920;
+uint32_t ofm_repetition_62 = 1;
+bool has_l1_read_access_pattern_62 = false;
+
+std::vector<access_pattern> l1_read_pattern_62 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_62 = {
+{
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 4, 12}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 6, 12}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 2, 18}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 4, 18}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 6, 18}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 63
+// LayerName: Mul_102
+std::vector<uint32_t> ifm_dim_63 = {8, 40, 30, 12};
+std::vector<uint32_t> ifm_bound_63 = {8, 40, 30, 12};
+std::vector<uint32_t> ifmsv_dim_63 = {8, 20, 2, 3};
+uint32_t ifmsv_size_63 = 3840;
+uint32_t kernel_iter_63 = 16;
+bool has_l1_write_access_pattern_63 = false;
+std::vector<access_pattern> l1_write_pattern_63 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_63 = {
+{
+  tiling({.buffer_dimension = {8, 40, 30, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 30, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 30, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 30, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 30, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 30, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 30, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 30, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_63 = {8, 40, 30, 12};
+std::vector<uint32_t> ifm2_bound_63 = {8, 40, 30, 12};
+std::vector<uint32_t> ifm2sv_dim_63 = {8, 20, 2, 3};
+uint32_t ifm2sv_size_63 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_63 = {
+{
+  tiling({.buffer_dimension = {8, 40, 30, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 30, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 30, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 30, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 30, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 30, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 30, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 30, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1})
+}};
+
+
+uint32_t wtssv_size_63 = 0;
+bool has_l1_wts_write_access_pattern_63 = false;
+std::vector<access_pattern> l1_wts_write_pattern_63 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_63 = {};
+
+
+std::vector<uint32_t> ofm_dim_63 = {8, 40, 32, 12};
+std::vector<uint32_t> ofm_bound_63 = {8, 40, 30, 12};
+std::vector<uint32_t> ofmsv_dim_63 = {8, 20, 2, 3};
+uint32_t ofmsv_size_63 = 960;
+uint32_t ofm_repetition_63 = 1;
+bool has_l1_read_access_pattern_63 = false;
+
+std::vector<access_pattern> l1_read_pattern_63 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_63 = {
+{
+  tiling({.buffer_dimension = {8, 40, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 65
+// LayerName: Conv_103
+std::vector<uint32_t> ifm_dim_65 = {8, 40, 30, 23};
+std::vector<uint32_t> ifm_bound_65 = {8, 40, 30, 23};
+std::vector<uint32_t> ifmsv_dim_65 = {8, 12, 1, 10};
+uint32_t ifmsv_size_65 = 3840;
+uint32_t kernel_iter_65 = 40;
+bool has_l1_write_access_pattern_65 = false;
+std::vector<access_pattern> l1_write_pattern_65 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_65 = {
+{
+  tiling({.buffer_dimension = {8, 40, 30, 23}, .tiling_dimension = {8, 12, 1, 10}, .offset = {0, -1, 0, -1}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 32}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 30, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 30, 23}, .tiling_dimension = {8, 12, 1, 10}, .offset = {0, -1, 0, 7}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 32}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 30, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 30, 23}, .tiling_dimension = {8, 12, 1, 10}, .offset = {0, -1, 0, 15}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 32}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 30, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 30, 23}, .tiling_dimension = {8, 12, 1, 10}, .offset = {0, -1, 0, 23}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 32}, {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 30, 23}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_65 = {4096};
+std::vector<uint32_t> wts_dim_65 = {4096};
+std::vector<uint32_t> wtssv_dim_65 = {128};
+uint32_t wts_repetition_65 = 1;
+uint32_t wtssv_size_65 = 128;
+bool has_l1_wts_write_access_pattern_65 = false;
+std::vector<access_pattern> l1_wts_write_pattern_65 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_65 = {
+{
+  tiling({.buffer_dimension = {4096}, .tiling_dimension = {128}, .offset = {0}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 8} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4096}, .tiling_dimension = {128}, .offset = {128}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 8} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4096}, .tiling_dimension = {128}, .offset = {256}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 8} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4096}, .tiling_dimension = {128}, .offset = {384}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 8} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_65[] = {
+{
+  tiling({.buffer_dimension = {4096, 1}, .tiling_dimension = {2048, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4096, 1}, .tiling_dimension = {2048, 1}, .offset = {2048, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_65[] = {
+{
+  tiling({.buffer_dimension = {4096}, .tiling_dimension = {2048}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4096}, .tiling_dimension = {2048}, .offset = {2048}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_65 = {8, 20, 32, 16};
+std::vector<uint32_t> ofm_bound_65 = {8, 20, 30, 12};
+std::vector<uint32_t> ofmsv_dim_65 = {8, 4, 1, 4};
+uint32_t ofmsv_size_65 = 128;
+uint32_t ofm_repetition_65 = 1;
+bool has_l1_read_access_pattern_65 = false;
+
+std::vector<access_pattern> l1_read_pattern_65 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_65 = {
+{
+  tiling({.buffer_dimension = {8, 20, 32, 16}, .tiling_dimension = {8, 4, 1, 4}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8}, {.dimension = 1, .stride = 4, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 16}, .tiling_dimension = {8, 4, 1, 4}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8}, {.dimension = 1, .stride = 4, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 16}, .tiling_dimension = {8, 4, 1, 4}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8}, {.dimension = 1, .stride = 4, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 16}, .tiling_dimension = {8, 4, 1, 4}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8}, {.dimension = 1, .stride = 4, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 16}, .tiling_dimension = {8, 4, 1, 4}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8}, {.dimension = 1, .stride = 4, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 16}, .tiling_dimension = {8, 4, 1, 4}, .offset = {0, 0, 1, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8}, {.dimension = 1, .stride = 4, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 16}, .tiling_dimension = {8, 4, 1, 4}, .offset = {0, 0, 2, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8}, {.dimension = 1, .stride = 4, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 16}, .tiling_dimension = {8, 4, 1, 4}, .offset = {0, 0, 3, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8}, {.dimension = 1, .stride = 4, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 16}, .tiling_dimension = {8, 4, 1, 4}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8}, {.dimension = 1, .stride = 4, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 16}, .tiling_dimension = {8, 4, 1, 4}, .offset = {0, 0, 1, 8}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8}, {.dimension = 1, .stride = 4, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 16}, .tiling_dimension = {8, 4, 1, 4}, .offset = {0, 0, 2, 8}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8}, {.dimension = 1, .stride = 4, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 16}, .tiling_dimension = {8, 4, 1, 4}, .offset = {0, 0, 3, 8}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8}, {.dimension = 1, .stride = 4, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 16}, .tiling_dimension = {8, 4, 1, 4}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8}, {.dimension = 1, .stride = 4, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 16}, .tiling_dimension = {8, 4, 1, 4}, .offset = {0, 0, 1, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8}, {.dimension = 1, .stride = 4, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 16}, .tiling_dimension = {8, 4, 1, 4}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8}, {.dimension = 1, .stride = 4, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 16}, .tiling_dimension = {8, 4, 1, 4}, .offset = {0, 0, 3, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8}, {.dimension = 1, .stride = 4, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 66
+// LayerName: Add_105
+std::vector<uint32_t> ifm_dim_66 = {8, 20, 32, 16};
+std::vector<uint32_t> ifm_bound_66 = {8, 20, 30, 12};
+std::vector<uint32_t> ifmsv_dim_66 = {8, 20, 4, 3};
+uint32_t ifmsv_size_66 = 7680;
+uint32_t kernel_iter_66 = 2;
+bool has_l1_write_access_pattern_66 = false;
+std::vector<access_pattern> l1_write_pattern_66 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_66 = {
+{
+  tiling({.buffer_dimension = {8, 20, 32, 16}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 30, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 16}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 30, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 16}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 30, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 16}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 30, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_66 = 0;
+bool has_l1_wts_write_access_pattern_66 = false;
+std::vector<access_pattern> l1_wts_write_pattern_66 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_66 = {};
+
+
+std::vector<uint32_t> ofm_dim_66 = {8, 20, 32, 12};
+std::vector<uint32_t> ofm_bound_66 = {8, 20, 30, 12};
+std::vector<uint32_t> ofmsv_dim_66 = {8, 20, 4, 3};
+uint32_t ofmsv_size_66 = 1920;
+uint32_t ofm_repetition_66 = 1;
+bool has_l1_read_access_pattern_66 = false;
+
+std::vector<access_pattern> l1_read_pattern_66 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_66 = {
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 67
+// LayerName: Clip_108
+std::vector<uint32_t> ifm_dim_67 = {8, 20, 32, 12};
+std::vector<uint32_t> ifm_bound_67 = {8, 20, 30, 12};
+std::vector<uint32_t> ifmsv_dim_67 = {8, 20, 4, 3};
+uint32_t ifmsv_size_67 = 7680;
+uint32_t kernel_iter_67 = 2;
+bool has_l1_write_access_pattern_67 = false;
+std::vector<access_pattern> l1_write_pattern_67 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_67 = {
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 30, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 30, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 30, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 30, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_67 = 0;
+bool has_l1_wts_write_access_pattern_67 = false;
+std::vector<access_pattern> l1_wts_write_pattern_67 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_67 = {};
+
+
+std::vector<uint32_t> ofm_dim_67 = {8, 20, 32, 12};
+std::vector<uint32_t> ofm_bound_67 = {8, 20, 30, 12};
+std::vector<uint32_t> ofmsv_dim_67 = {8, 20, 4, 3};
+uint32_t ofmsv_size_67 = 1920;
+uint32_t ofm_repetition_67 = 1;
+bool has_l1_read_access_pattern_67 = false;
+
+std::vector<access_pattern> l1_read_pattern_67 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_67 = {
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 68
+// LayerName: Div_110
+std::vector<uint32_t> ifm_dim_68 = {8, 20, 32, 12};
+std::vector<uint32_t> ifm_bound_68 = {8, 20, 30, 12};
+std::vector<uint32_t> ifmsv_dim_68 = {8, 20, 4, 3};
+uint32_t ifmsv_size_68 = 7680;
+uint32_t kernel_iter_68 = 2;
+bool has_l1_write_access_pattern_68 = false;
+std::vector<access_pattern> l1_write_pattern_68 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_68 = {
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 30, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 30, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 30, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 30, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_68 = 0;
+bool has_l1_wts_write_access_pattern_68 = false;
+std::vector<access_pattern> l1_wts_write_pattern_68 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_68 = {};
+
+
+std::vector<uint32_t> ofm_dim_68 = {8, 20, 32, 12};
+std::vector<uint32_t> ofm_bound_68 = {8, 20, 30, 12};
+std::vector<uint32_t> ofmsv_dim_68 = {8, 20, 4, 3};
+uint32_t ofmsv_size_68 = 1920;
+uint32_t ofm_repetition_68 = 1;
+bool has_l1_read_access_pattern_68 = false;
+
+std::vector<access_pattern> l1_read_pattern_68 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_68 = {
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 69
+// LayerName: Mul_111
+std::vector<uint32_t> ifm_dim_69 = {8, 20, 32, 16};
+std::vector<uint32_t> ifm_bound_69 = {8, 20, 30, 12};
+std::vector<uint32_t> ifmsv_dim_69 = {8, 20, 2, 3};
+uint32_t ifmsv_size_69 = 3840;
+uint32_t kernel_iter_69 = 4;
+bool has_l1_write_access_pattern_69 = false;
+std::vector<access_pattern> l1_write_pattern_69 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_69 = {
+{
+  tiling({.buffer_dimension = {8, 20, 32, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 30, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 30, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 30, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 30, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_69 = {8, 20, 32, 12};
+std::vector<uint32_t> ifm2_bound_69 = {8, 20, 30, 12};
+std::vector<uint32_t> ifm2sv_dim_69 = {8, 20, 2, 3};
+uint32_t ifm2sv_size_69 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_69 = {
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 30, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 30, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 30, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 30, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_69 = 0;
+bool has_l1_wts_write_access_pattern_69 = false;
+std::vector<access_pattern> l1_wts_write_pattern_69 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_69 = {};
+
+
+std::vector<uint32_t> ofm_dim_69 = {8, 20, 32, 12};
+std::vector<uint32_t> ofm_bound_69 = {8, 20, 30, 12};
+std::vector<uint32_t> ofmsv_dim_69 = {8, 20, 2, 3};
+uint32_t ofmsv_size_69 = 960;
+uint32_t ofm_repetition_69 = 1;
+bool has_l1_read_access_pattern_69 = false;
+
+std::vector<access_pattern> l1_read_pattern_69 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_69 = {
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 70
+// LayerName: Conv_112
+std::vector<uint32_t> ifm_dim_70 = {8, 20, 32, 12};
+std::vector<uint32_t> ifm_bound_70 = {8, 20, 30, 12};
+std::vector<uint32_t> ifmsv_dim_70 = {8, 32, 10, 1};
+uint32_t ifmsv_size_70 = 2560;
+uint32_t kernel_iter_70 = 9;
+bool has_l1_write_access_pattern_70 = true;
+std::vector<access_pattern> l1_write_pattern_70 = {tiling({.buffer_dimension = {8, 32, 10, 1}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_70 = {
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 30, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 30, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 30, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 30, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_70 = {24192};
+std::vector<uint32_t> wts_dim_70 = {24192};
+std::vector<uint32_t> wtssv_dim_70 = {2016};
+uint32_t wtssv_size_70 = 2016;
+uint32_t wts_repetition_70 = 1;
+bool has_l1_wts_write_access_pattern_70 = false;
+std::vector<access_pattern> l1_wts_write_pattern_70 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_70 = {
+{
+  tiling({.buffer_dimension = {6048, 4}, .tiling_dimension = {2016, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 2016, .wrap = 3} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {6048, 4}, .tiling_dimension = {2016, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 2016, .wrap = 3} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {6048, 4}, .tiling_dimension = {2016, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 2016, .wrap = 3} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {6048, 4}, .tiling_dimension = {2016, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 2016, .wrap = 3} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_70[] = {
+{
+  tiling({.buffer_dimension = {24192, 1}, .tiling_dimension = {12096, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {24192, 1}, .tiling_dimension = {12096, 1}, .offset = {12096, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_70[] = {
+{
+  tiling({.buffer_dimension = {24192}, .tiling_dimension = {12096}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {24192}, .tiling_dimension = {12096}, .offset = {12096}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_70 = {8, 32, 12, 12};
+std::vector<uint32_t> ofm_bound_70 = {8, 20, 10, 12};
+std::vector<uint32_t> ofmsv_dim_70 = {8, 32, 3, 1};
+uint32_t ofmsv_size_70 = 768;
+uint32_t ofm_repetition_70 = 3;
+bool has_l1_read_access_pattern_70 = false;
+
+std::vector<access_pattern> l1_read_pattern_70 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_70 = {
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 9, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 3, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 6, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 9, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 3, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 6, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 9, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 3, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 9, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 71
+// LayerName: Conv_113
+std::vector<uint32_t> ifm_dim_71 = {8, 32, 12, 12};
+std::vector<uint32_t> ifm_bound_71 = {8, 20, 10, 12};
+std::vector<uint32_t> ifmsv_dim_71 = {8, 32, 10, 1};
+uint32_t ifmsv_size_71 = 2560;
+uint32_t kernel_iter_71 = 6;
+bool has_l1_write_access_pattern_71 = true;
+std::vector<access_pattern> l1_write_pattern_71 = {tiling({.buffer_dimension = {8, 32, 10, 1}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_71 = {
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_71 = {21504};
+std::vector<uint32_t> wts_dim_71 = {21504};
+std::vector<uint32_t> wtssv_dim_71 = {2688};
+uint32_t wtssv_size_71 = 2688;
+uint32_t wts_repetition_71 = 1;
+bool has_l1_wts_write_access_pattern_71 = false;
+std::vector<access_pattern> l1_wts_write_pattern_71 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_71 = {
+{
+  tiling({.buffer_dimension = {2688, 8}, .tiling_dimension = {2688, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {2688, 8}, .tiling_dimension = {2688, 1}, .offset = {0, 4}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2688, 8}, .tiling_dimension = {2688, 1}, .offset = {0, 1}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {2688, 8}, .tiling_dimension = {2688, 1}, .offset = {0, 5}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2688, 8}, .tiling_dimension = {2688, 1}, .offset = {0, 2}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {2688, 8}, .tiling_dimension = {2688, 1}, .offset = {0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2688, 8}, .tiling_dimension = {2688, 1}, .offset = {0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {2688, 8}, .tiling_dimension = {2688, 1}, .offset = {0, 7}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_71[] = {
+{
+  tiling({.buffer_dimension = {21504, 1}, .tiling_dimension = {10752, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {21504, 1}, .tiling_dimension = {10752, 1}, .offset = {10752, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_71[] = {
+{
+  tiling({.buffer_dimension = {21504}, .tiling_dimension = {10752}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {21504}, .tiling_dimension = {10752}, .offset = {10752}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_71 = {8, 32, 32, 12};
+std::vector<uint32_t> ofm_bound_71 = {8, 20, 25, 12};
+std::vector<uint32_t> ofmsv_dim_71 = {8, 32, 4, 1};
+uint32_t ofmsv_size_71 = 1024;
+uint32_t ofm_repetition_71 = 1;
+bool has_l1_read_access_pattern_71 = false;
+
+std::vector<access_pattern> l1_read_pattern_71 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_71 = {
+{
+  tiling({.buffer_dimension = {8, 32, 32, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 32, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 32, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 8, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 32, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 12, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 32, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 32, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 4, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 32, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 8, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 32, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 12, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 32, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 32, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 4, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 32, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 8, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 32, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 12, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 32, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 32, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 32, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 8, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 32, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 12, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 72
+// LayerName: Add_115
+std::vector<uint32_t> ifm_dim_72 = {8, 32, 32, 12};
+std::vector<uint32_t> ifm_bound_72 = {8, 20, 25, 12};
+std::vector<uint32_t> ifmsv_dim_72 = {8, 20, 4, 3};
+uint32_t ifmsv_size_72 = 7680;
+uint32_t kernel_iter_72 = 2;
+bool has_l1_write_access_pattern_72 = false;
+std::vector<access_pattern> l1_write_pattern_72 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_72 = {
+{
+  tiling({.buffer_dimension = {8, 32, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_72 = 0;
+bool has_l1_wts_write_access_pattern_72 = false;
+std::vector<access_pattern> l1_wts_write_pattern_72 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_72 = {};
+
+
+std::vector<uint32_t> ofm_dim_72 = {8, 20, 32, 12};
+std::vector<uint32_t> ofm_bound_72 = {8, 20, 25, 12};
+std::vector<uint32_t> ofmsv_dim_72 = {8, 20, 4, 3};
+uint32_t ofmsv_size_72 = 1920;
+uint32_t ofm_repetition_72 = 1;
+bool has_l1_read_access_pattern_72 = false;
+
+std::vector<access_pattern> l1_read_pattern_72 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_72 = {
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 73
+// LayerName: Clip_118
+std::vector<uint32_t> ifm_dim_73 = {8, 20, 32, 12};
+std::vector<uint32_t> ifm_bound_73 = {8, 20, 25, 12};
+std::vector<uint32_t> ifmsv_dim_73 = {8, 20, 4, 3};
+uint32_t ifmsv_size_73 = 7680;
+uint32_t kernel_iter_73 = 2;
+bool has_l1_write_access_pattern_73 = false;
+std::vector<access_pattern> l1_write_pattern_73 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_73 = {
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_73 = 0;
+bool has_l1_wts_write_access_pattern_73 = false;
+std::vector<access_pattern> l1_wts_write_pattern_73 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_73 = {};
+
+
+std::vector<uint32_t> ofm_dim_73 = {8, 20, 32, 12};
+std::vector<uint32_t> ofm_bound_73 = {8, 20, 25, 12};
+std::vector<uint32_t> ofmsv_dim_73 = {8, 20, 4, 3};
+uint32_t ofmsv_size_73 = 1920;
+uint32_t ofm_repetition_73 = 1;
+bool has_l1_read_access_pattern_73 = false;
+
+std::vector<access_pattern> l1_read_pattern_73 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_73 = {
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 74
+// LayerName: Div_120
+std::vector<uint32_t> ifm_dim_74 = {8, 20, 32, 12};
+std::vector<uint32_t> ifm_bound_74 = {8, 20, 25, 12};
+std::vector<uint32_t> ifmsv_dim_74 = {8, 20, 4, 3};
+uint32_t ifmsv_size_74 = 7680;
+uint32_t kernel_iter_74 = 2;
+bool has_l1_write_access_pattern_74 = false;
+std::vector<access_pattern> l1_write_pattern_74 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_74 = {
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_74 = 0;
+bool has_l1_wts_write_access_pattern_74 = false;
+std::vector<access_pattern> l1_wts_write_pattern_74 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_74 = {};
+
+
+std::vector<uint32_t> ofm_dim_74 = {8, 20, 32, 12};
+std::vector<uint32_t> ofm_bound_74 = {8, 20, 25, 12};
+std::vector<uint32_t> ofmsv_dim_74 = {8, 20, 4, 3};
+uint32_t ofmsv_size_74 = 1920;
+uint32_t ofm_repetition_74 = 1;
+bool has_l1_read_access_pattern_74 = false;
+
+std::vector<access_pattern> l1_read_pattern_74 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_74 = {
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 75
+// LayerName: Mul_121
+std::vector<uint32_t> ifm_dim_75 = {8, 32, 32, 12};
+std::vector<uint32_t> ifm_bound_75 = {8, 20, 25, 12};
+std::vector<uint32_t> ifmsv_dim_75 = {8, 20, 2, 3};
+uint32_t ifmsv_size_75 = 3840;
+uint32_t kernel_iter_75 = 4;
+bool has_l1_write_access_pattern_75 = false;
+std::vector<access_pattern> l1_write_pattern_75 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_75 = {
+{
+  tiling({.buffer_dimension = {8, 32, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_75 = {8, 20, 32, 12};
+std::vector<uint32_t> ifm2_bound_75 = {8, 20, 25, 12};
+std::vector<uint32_t> ifm2sv_dim_75 = {8, 20, 2, 3};
+uint32_t ifm2sv_size_75 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_75 = {
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_75 = 0;
+bool has_l1_wts_write_access_pattern_75 = false;
+std::vector<access_pattern> l1_wts_write_pattern_75 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_75 = {};
+
+
+std::vector<uint32_t> ofm_dim_75 = {8, 20, 32, 12};
+std::vector<uint32_t> ofm_bound_75 = {8, 20, 25, 12};
+std::vector<uint32_t> ofmsv_dim_75 = {8, 20, 2, 3};
+uint32_t ofmsv_size_75 = 960;
+uint32_t ofm_repetition_75 = 1;
+bool has_l1_read_access_pattern_75 = false;
+
+std::vector<access_pattern> l1_read_pattern_75 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_75 = {
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 76
+// LayerName: Conv_122
+std::vector<uint32_t> ifm_dim_76 = {8, 20, 32, 12};
+std::vector<uint32_t> ifm_bound_76 = {8, 20, 25, 12};
+std::vector<uint32_t> ifmsv_dim_76 = {8, 28, 1, 6};
+uint32_t ifmsv_size_76 = 5376;
+uint32_t kernel_iter_76 = 7;
+bool has_l1_write_access_pattern_76 = false;
+std::vector<access_pattern> l1_write_pattern_76 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_76 = {
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, -1}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 28} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 28} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 7}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 28} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 11}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 28} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_76 = {3584};
+std::vector<uint32_t> wts_dim_76 = {3584};
+std::vector<uint32_t> wtssv_dim_76 = {128};
+uint32_t wts_repetition_76 = 1;
+uint32_t wtssv_size_76 = 128;
+bool has_l1_wts_write_access_pattern_76 = false;
+std::vector<access_pattern> l1_wts_write_pattern_76 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_76 = {
+{
+  tiling({.buffer_dimension = {3584}, .tiling_dimension = {128}, .offset = {0}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {3584}, .tiling_dimension = {128}, .offset = {128}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {3584}, .tiling_dimension = {128}, .offset = {256}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {3584}, .tiling_dimension = {128}, .offset = {384}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_76[] = {
+{
+  tiling({.buffer_dimension = {3584, 1}, .tiling_dimension = {1792, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {3584, 1}, .tiling_dimension = {1792, 1}, .offset = {1792, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_76[] = {
+{
+  tiling({.buffer_dimension = {3584}, .tiling_dimension = {1792}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {3584}, .tiling_dimension = {1792}, .offset = {1792}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_76 = {8, 24, 28, 16};
+std::vector<uint32_t> ofm_bound_76 = {8, 20, 25, 12};
+std::vector<uint32_t> ofmsv_dim_76 = {8, 24, 1, 4};
+uint32_t ofmsv_size_76 = 768;
+uint32_t ofm_repetition_76 = 1;
+bool has_l1_read_access_pattern_76 = false;
+
+std::vector<access_pattern> l1_read_pattern_76 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_76 = {
+{
+  tiling({.buffer_dimension = {8, 24, 28, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 7} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 28, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 7} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 28, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 7} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 28, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 7} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 28, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 7} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 28, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 1, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 7} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 28, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 2, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 7} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 28, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 3, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 7} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 28, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 7} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 28, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 1, 8}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 7} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 28, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 2, 8}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 7} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 28, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 3, 8}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 7} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 28, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 7} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 28, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 1, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 7} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 28, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 7} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 28, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 3, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 7} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 77
+// LayerName: Add_124
+std::vector<uint32_t> ifm_dim_77 = {8, 24, 28, 16};
+std::vector<uint32_t> ifm_bound_77 = {8, 20, 25, 12};
+std::vector<uint32_t> ifmsv_dim_77 = {8, 20, 4, 3};
+uint32_t ifmsv_size_77 = 7680;
+uint32_t kernel_iter_77 = 2;
+bool has_l1_write_access_pattern_77 = false;
+std::vector<access_pattern> l1_write_pattern_77 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_77 = {
+{
+  tiling({.buffer_dimension = {8, 24, 28, 16}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 28, 16}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 28, 16}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 28, 16}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_77 = 0;
+bool has_l1_wts_write_access_pattern_77 = false;
+std::vector<access_pattern> l1_wts_write_pattern_77 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_77 = {};
+
+
+std::vector<uint32_t> ofm_dim_77 = {8, 20, 32, 12};
+std::vector<uint32_t> ofm_bound_77 = {8, 20, 25, 12};
+std::vector<uint32_t> ofmsv_dim_77 = {8, 20, 4, 3};
+uint32_t ofmsv_size_77 = 1920;
+uint32_t ofm_repetition_77 = 1;
+bool has_l1_read_access_pattern_77 = false;
+
+std::vector<access_pattern> l1_read_pattern_77 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_77 = {
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 78
+// LayerName: Clip_127
+std::vector<uint32_t> ifm_dim_78 = {8, 20, 32, 12};
+std::vector<uint32_t> ifm_bound_78 = {8, 20, 25, 12};
+std::vector<uint32_t> ifmsv_dim_78 = {8, 20, 4, 3};
+uint32_t ifmsv_size_78 = 7680;
+uint32_t kernel_iter_78 = 2;
+bool has_l1_write_access_pattern_78 = false;
+std::vector<access_pattern> l1_write_pattern_78 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_78 = {
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_78 = 0;
+bool has_l1_wts_write_access_pattern_78 = false;
+std::vector<access_pattern> l1_wts_write_pattern_78 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_78 = {};
+
+
+std::vector<uint32_t> ofm_dim_78 = {8, 20, 32, 12};
+std::vector<uint32_t> ofm_bound_78 = {8, 20, 25, 12};
+std::vector<uint32_t> ofmsv_dim_78 = {8, 20, 4, 3};
+uint32_t ofmsv_size_78 = 1920;
+uint32_t ofm_repetition_78 = 1;
+bool has_l1_read_access_pattern_78 = false;
+
+std::vector<access_pattern> l1_read_pattern_78 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_78 = {
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 79
+// LayerName: Div_129
+std::vector<uint32_t> ifm_dim_79 = {8, 20, 32, 12};
+std::vector<uint32_t> ifm_bound_79 = {8, 20, 25, 12};
+std::vector<uint32_t> ifmsv_dim_79 = {8, 20, 4, 3};
+uint32_t ifmsv_size_79 = 7680;
+uint32_t kernel_iter_79 = 2;
+bool has_l1_write_access_pattern_79 = false;
+std::vector<access_pattern> l1_write_pattern_79 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_79 = {
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_79 = 0;
+bool has_l1_wts_write_access_pattern_79 = false;
+std::vector<access_pattern> l1_wts_write_pattern_79 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_79 = {};
+
+
+std::vector<uint32_t> ofm_dim_79 = {8, 20, 32, 12};
+std::vector<uint32_t> ofm_bound_79 = {8, 20, 25, 12};
+std::vector<uint32_t> ofmsv_dim_79 = {8, 20, 4, 3};
+uint32_t ofmsv_size_79 = 1920;
+uint32_t ofm_repetition_79 = 1;
+bool has_l1_read_access_pattern_79 = false;
+
+std::vector<access_pattern> l1_read_pattern_79 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_79 = {
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 80
+// LayerName: Mul_130
+std::vector<uint32_t> ifm_dim_80 = {8, 24, 28, 16};
+std::vector<uint32_t> ifm_bound_80 = {8, 20, 25, 12};
+std::vector<uint32_t> ifmsv_dim_80 = {8, 20, 2, 3};
+uint32_t ifmsv_size_80 = 3840;
+uint32_t kernel_iter_80 = 4;
+bool has_l1_write_access_pattern_80 = false;
+std::vector<access_pattern> l1_write_pattern_80 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_80 = {
+{
+  tiling({.buffer_dimension = {8, 24, 28, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 28, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 28, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 28, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_80 = {8, 20, 32, 12};
+std::vector<uint32_t> ifm2_bound_80 = {8, 20, 25, 12};
+std::vector<uint32_t> ifm2sv_dim_80 = {8, 20, 2, 3};
+uint32_t ifm2sv_size_80 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_80 = {
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_80 = 0;
+bool has_l1_wts_write_access_pattern_80 = false;
+std::vector<access_pattern> l1_wts_write_pattern_80 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_80 = {};
+
+
+std::vector<uint32_t> ofm_dim_80 = {8, 20, 32, 12};
+std::vector<uint32_t> ofm_bound_80 = {8, 20, 25, 12};
+std::vector<uint32_t> ofmsv_dim_80 = {8, 20, 2, 3};
+uint32_t ofmsv_size_80 = 960;
+uint32_t ofm_repetition_80 = 1;
+bool has_l1_read_access_pattern_80 = false;
+
+std::vector<access_pattern> l1_read_pattern_80 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_80 = {
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 81
+// LayerName: Conv_131
+std::vector<uint32_t> ifm_dim_81 = {8, 20, 32, 12};
+std::vector<uint32_t> ifm_bound_81 = {8, 20, 25, 12};
+std::vector<uint32_t> ifmsv_dim_81 = {8, 32, 13, 1};
+uint32_t ifmsv_size_81 = 3328;
+uint32_t kernel_iter_81 = 6;
+bool has_l1_write_access_pattern_81 = false;
+std::vector<access_pattern> l1_write_pattern_81 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_81 = {
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 32, 13, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 13, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 32, 13, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 13, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 32, 13, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 13, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 32, 12}, .tiling_dimension = {8, 32, 13, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 13, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 25, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_81 = {8, 32, 12, 12};
+std::vector<uint32_t> ifm2_bound_81 = {8, 20, 10, 12};
+std::vector<uint32_t> ifm2sv_dim_81 = {8, 32, 3, 1};
+uint32_t ifm2sv_size_81 = 3072;
+std::vector<std::vector<access_pattern>> ifm2_pattern_81 = {
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_81 = {20736};
+std::vector<uint32_t> wts_dim_81 = {20736};
+std::vector<uint32_t> wtssv_dim_81 = {2592};
+uint32_t wtssv_size_81 = 2592;
+uint32_t wts_repetition_81 = 1;
+bool has_l1_wts_write_access_pattern_81 = false;
+std::vector<access_pattern> l1_wts_write_pattern_81 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_81 = {
+{
+  tiling({.buffer_dimension = {5184, 4}, .tiling_dimension = {2592, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 2592, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {5184, 4}, .tiling_dimension = {2592, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 2592, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {5184, 4}, .tiling_dimension = {2592, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 2592, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {5184, 4}, .tiling_dimension = {2592, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 2592, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_81[] = {
+{
+  tiling({.buffer_dimension = {20736, 1}, .tiling_dimension = {10368, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {20736, 1}, .tiling_dimension = {10368, 1}, .offset = {10368, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_81[] = {
+{
+  tiling({.buffer_dimension = {20736}, .tiling_dimension = {10368}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {20736}, .tiling_dimension = {10368}, .offset = {10368}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_81 = {8, 32, 12, 12};
+std::vector<uint32_t> ofm_bound_81 = {8, 20, 10, 12};
+std::vector<uint32_t> ofmsv_dim_81 = {8, 32, 3, 1};
+uint32_t ofmsv_size_81 = 768;
+uint32_t ofm_repetition_81 = 2;
+bool has_l1_read_access_pattern_81 = false;
+
+std::vector<access_pattern> l1_read_pattern_81 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_81 = {
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 9, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 3, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 6, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 9, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 3, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 6, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 9, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 3, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 9, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 82
+// LayerName: Conv_133
+std::vector<uint32_t> ifm_dim_82 = {8, 32, 12, 12};
+std::vector<uint32_t> ifm_bound_82 = {8, 20, 10, 12};
+std::vector<uint32_t> ifmsv_dim_82 = {8, 8, 10, 3};
+uint32_t ifmsv_size_82 = 1920;
+uint32_t kernel_iter_82 = 3;
+bool has_l1_write_access_pattern_82 = false;
+std::vector<access_pattern> l1_write_pattern_82 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_82 = {
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 8, 10, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 8, 10, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 8, 10, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 8, 10, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_82 = {16128};
+std::vector<uint32_t> wts_dim_82 = {16128};
+std::vector<uint32_t> wtssv_dim_82 = {4032};
+uint32_t wtssv_size_82 = 4032;
+uint32_t wts_repetition_82 = 1;
+bool has_l1_wts_write_access_pattern_82 = false;
+std::vector<access_pattern> l1_wts_write_pattern_82 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_82 = {
+{
+  tiling({.buffer_dimension = {4032, 4}, .tiling_dimension = {4032, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4032, 4}, .tiling_dimension = {4032, 1}, .offset = {0, 1}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4032, 4}, .tiling_dimension = {4032, 1}, .offset = {0, 2}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4032, 4}, .tiling_dimension = {4032, 1}, .offset = {0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_82[] = {
+{
+  tiling({.buffer_dimension = {16128, 1}, .tiling_dimension = {8064, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {16128, 1}, .tiling_dimension = {8064, 1}, .offset = {8064, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_82[] = {
+{
+  tiling({.buffer_dimension = {16128}, .tiling_dimension = {8064}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {16128}, .tiling_dimension = {8064}, .offset = {8064}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_82 = {8, 24, 24, 12};
+std::vector<uint32_t> ofm_bound_82 = {8, 20, 23, 12};
+std::vector<uint32_t> ofmsv_dim_82 = {8, 8, 6, 3};
+uint32_t ofmsv_size_82 = 1152;
+uint32_t ofm_repetition_82 = 1;
+bool has_l1_read_access_pattern_82 = false;
+
+std::vector<access_pattern> l1_read_pattern_82 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_82 = {
+{
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 12, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 18, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 12, 3}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 18, 3}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 12, 6}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 18, 6}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 12, 9}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 18, 9}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 83
+// LayerName: Add_135
+std::vector<uint32_t> ifm_dim_83 = {8, 24, 24, 12};
+std::vector<uint32_t> ifm_bound_83 = {8, 20, 23, 12};
+std::vector<uint32_t> ifmsv_dim_83 = {8, 20, 2, 3};
+uint32_t ifmsv_size_83 = 3840;
+uint32_t kernel_iter_83 = 3;
+bool has_l1_write_access_pattern_83 = false;
+std::vector<access_pattern> l1_write_pattern_83 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_83 = {
+{
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_83 = 0;
+bool has_l1_wts_write_access_pattern_83 = false;
+std::vector<access_pattern> l1_wts_write_pattern_83 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_83 = {};
+
+
+std::vector<uint32_t> ofm_dim_83 = {8, 20, 24, 12};
+std::vector<uint32_t> ofm_bound_83 = {8, 20, 23, 12};
+std::vector<uint32_t> ofmsv_dim_83 = {8, 20, 2, 3};
+uint32_t ofmsv_size_83 = 960;
+uint32_t ofm_repetition_83 = 1;
+bool has_l1_read_access_pattern_83 = false;
+
+std::vector<access_pattern> l1_read_pattern_83 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_83 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 84
+// LayerName: Clip_138
+std::vector<uint32_t> ifm_dim_84 = {8, 20, 24, 12};
+std::vector<uint32_t> ifm_bound_84 = {8, 20, 23, 12};
+std::vector<uint32_t> ifmsv_dim_84 = {8, 20, 2, 3};
+uint32_t ifmsv_size_84 = 3840;
+uint32_t kernel_iter_84 = 3;
+bool has_l1_write_access_pattern_84 = false;
+std::vector<access_pattern> l1_write_pattern_84 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_84 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_84 = 0;
+bool has_l1_wts_write_access_pattern_84 = false;
+std::vector<access_pattern> l1_wts_write_pattern_84 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_84 = {};
+
+
+std::vector<uint32_t> ofm_dim_84 = {8, 20, 24, 12};
+std::vector<uint32_t> ofm_bound_84 = {8, 20, 23, 12};
+std::vector<uint32_t> ofmsv_dim_84 = {8, 20, 2, 3};
+uint32_t ofmsv_size_84 = 960;
+uint32_t ofm_repetition_84 = 1;
+bool has_l1_read_access_pattern_84 = false;
+
+std::vector<access_pattern> l1_read_pattern_84 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_84 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 85
+// LayerName: Div_140
+std::vector<uint32_t> ifm_dim_85 = {8, 20, 24, 12};
+std::vector<uint32_t> ifm_bound_85 = {8, 20, 23, 12};
+std::vector<uint32_t> ifmsv_dim_85 = {8, 20, 2, 3};
+uint32_t ifmsv_size_85 = 3840;
+uint32_t kernel_iter_85 = 3;
+bool has_l1_write_access_pattern_85 = false;
+std::vector<access_pattern> l1_write_pattern_85 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_85 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_85 = 0;
+bool has_l1_wts_write_access_pattern_85 = false;
+std::vector<access_pattern> l1_wts_write_pattern_85 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_85 = {};
+
+
+std::vector<uint32_t> ofm_dim_85 = {8, 20, 24, 12};
+std::vector<uint32_t> ofm_bound_85 = {8, 20, 23, 12};
+std::vector<uint32_t> ofmsv_dim_85 = {8, 20, 2, 3};
+uint32_t ofmsv_size_85 = 960;
+uint32_t ofm_repetition_85 = 1;
+bool has_l1_read_access_pattern_85 = false;
+
+std::vector<access_pattern> l1_read_pattern_85 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_85 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 86
+// LayerName: Mul_141
+std::vector<uint32_t> ifm_dim_86 = {8, 24, 24, 12};
+std::vector<uint32_t> ifm_bound_86 = {8, 20, 23, 12};
+std::vector<uint32_t> ifmsv_dim_86 = {8, 20, 2, 3};
+uint32_t ifmsv_size_86 = 3840;
+uint32_t kernel_iter_86 = 3;
+bool has_l1_write_access_pattern_86 = false;
+std::vector<access_pattern> l1_write_pattern_86 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_86 = {
+{
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_86 = {8, 20, 24, 12};
+std::vector<uint32_t> ifm2_bound_86 = {8, 20, 23, 12};
+std::vector<uint32_t> ifm2sv_dim_86 = {8, 20, 2, 3};
+uint32_t ifm2sv_size_86 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_86 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_86 = 0;
+bool has_l1_wts_write_access_pattern_86 = false;
+std::vector<access_pattern> l1_wts_write_pattern_86 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_86 = {};
+
+
+std::vector<uint32_t> ofm_dim_86 = {8, 20, 24, 12};
+std::vector<uint32_t> ofm_bound_86 = {8, 20, 23, 12};
+std::vector<uint32_t> ofmsv_dim_86 = {8, 20, 2, 3};
+uint32_t ofmsv_size_86 = 960;
+uint32_t ofm_repetition_86 = 1;
+bool has_l1_read_access_pattern_86 = false;
+
+std::vector<access_pattern> l1_read_pattern_86 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_86 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 87
+// LayerName: Conv_142
+std::vector<uint32_t> ifm_dim_87 = {8, 20, 24, 12};
+std::vector<uint32_t> ifm_bound_87 = {8, 20, 23, 12};
+std::vector<uint32_t> ifmsv_dim_87 = {8, 28, 1, 6};
+uint32_t ifmsv_size_87 = 5376;
+uint32_t kernel_iter_87 = 6;
+bool has_l1_write_access_pattern_87 = false;
+std::vector<access_pattern> l1_write_pattern_87 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_87 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, -1}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 24} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 24} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 7}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 24} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 11}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 24} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_87 = {3072};
+std::vector<uint32_t> wts_dim_87 = {3072};
+std::vector<uint32_t> wtssv_dim_87 = {128};
+uint32_t wts_repetition_87 = 1;
+uint32_t wtssv_size_87 = 128;
+bool has_l1_wts_write_access_pattern_87 = false;
+std::vector<access_pattern> l1_wts_write_pattern_87 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_87 = {
+{
+  tiling({.buffer_dimension = {3072}, .tiling_dimension = {128}, .offset = {0}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {3072}, .tiling_dimension = {128}, .offset = {128}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {3072}, .tiling_dimension = {128}, .offset = {256}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {3072}, .tiling_dimension = {128}, .offset = {384}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_87[] = {
+{
+  tiling({.buffer_dimension = {3072, 1}, .tiling_dimension = {1536, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {3072, 1}, .tiling_dimension = {1536, 1}, .offset = {1536, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_87[] = {
+{
+  tiling({.buffer_dimension = {3072}, .tiling_dimension = {1536}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {3072}, .tiling_dimension = {1536}, .offset = {1536}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_87 = {8, 24, 24, 16};
+std::vector<uint32_t> ofm_bound_87 = {8, 20, 23, 12};
+std::vector<uint32_t> ofmsv_dim_87 = {8, 24, 1, 4};
+uint32_t ofmsv_size_87 = 768;
+uint32_t ofm_repetition_87 = 1;
+bool has_l1_read_access_pattern_87 = false;
+
+std::vector<access_pattern> l1_read_pattern_87 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_87 = {
+{
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 1, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 2, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 3, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 1, 8}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 2, 8}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 3, 8}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 1, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 3, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 88
+// LayerName: Add_144
+std::vector<uint32_t> ifm_dim_88 = {8, 24, 24, 16};
+std::vector<uint32_t> ifm_bound_88 = {8, 20, 23, 12};
+std::vector<uint32_t> ifmsv_dim_88 = {8, 20, 2, 3};
+uint32_t ifmsv_size_88 = 3840;
+uint32_t kernel_iter_88 = 3;
+bool has_l1_write_access_pattern_88 = false;
+std::vector<access_pattern> l1_write_pattern_88 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_88 = {
+{
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_88 = 0;
+bool has_l1_wts_write_access_pattern_88 = false;
+std::vector<access_pattern> l1_wts_write_pattern_88 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_88 = {};
+
+
+std::vector<uint32_t> ofm_dim_88 = {8, 20, 24, 12};
+std::vector<uint32_t> ofm_bound_88 = {8, 20, 23, 12};
+std::vector<uint32_t> ofmsv_dim_88 = {8, 20, 2, 3};
+uint32_t ofmsv_size_88 = 960;
+uint32_t ofm_repetition_88 = 1;
+bool has_l1_read_access_pattern_88 = false;
+
+std::vector<access_pattern> l1_read_pattern_88 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_88 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 89
+// LayerName: Clip_147
+std::vector<uint32_t> ifm_dim_89 = {8, 20, 24, 12};
+std::vector<uint32_t> ifm_bound_89 = {8, 20, 23, 12};
+std::vector<uint32_t> ifmsv_dim_89 = {8, 20, 2, 3};
+uint32_t ifmsv_size_89 = 3840;
+uint32_t kernel_iter_89 = 3;
+bool has_l1_write_access_pattern_89 = false;
+std::vector<access_pattern> l1_write_pattern_89 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_89 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_89 = 0;
+bool has_l1_wts_write_access_pattern_89 = false;
+std::vector<access_pattern> l1_wts_write_pattern_89 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_89 = {};
+
+
+std::vector<uint32_t> ofm_dim_89 = {8, 20, 24, 12};
+std::vector<uint32_t> ofm_bound_89 = {8, 20, 23, 12};
+std::vector<uint32_t> ofmsv_dim_89 = {8, 20, 2, 3};
+uint32_t ofmsv_size_89 = 960;
+uint32_t ofm_repetition_89 = 1;
+bool has_l1_read_access_pattern_89 = false;
+
+std::vector<access_pattern> l1_read_pattern_89 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_89 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 90
+// LayerName: Div_149
+std::vector<uint32_t> ifm_dim_90 = {8, 20, 24, 12};
+std::vector<uint32_t> ifm_bound_90 = {8, 20, 23, 12};
+std::vector<uint32_t> ifmsv_dim_90 = {8, 20, 2, 3};
+uint32_t ifmsv_size_90 = 3840;
+uint32_t kernel_iter_90 = 3;
+bool has_l1_write_access_pattern_90 = false;
+std::vector<access_pattern> l1_write_pattern_90 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_90 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_90 = 0;
+bool has_l1_wts_write_access_pattern_90 = false;
+std::vector<access_pattern> l1_wts_write_pattern_90 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_90 = {};
+
+
+std::vector<uint32_t> ofm_dim_90 = {8, 20, 24, 12};
+std::vector<uint32_t> ofm_bound_90 = {8, 20, 23, 12};
+std::vector<uint32_t> ofmsv_dim_90 = {8, 20, 2, 3};
+uint32_t ofmsv_size_90 = 960;
+uint32_t ofm_repetition_90 = 1;
+bool has_l1_read_access_pattern_90 = false;
+
+std::vector<access_pattern> l1_read_pattern_90 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_90 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 91
+// LayerName: Mul_150
+std::vector<uint32_t> ifm_dim_91 = {8, 24, 24, 16};
+std::vector<uint32_t> ifm_bound_91 = {8, 20, 23, 12};
+std::vector<uint32_t> ifmsv_dim_91 = {8, 20, 2, 3};
+uint32_t ifmsv_size_91 = 3840;
+uint32_t kernel_iter_91 = 3;
+bool has_l1_write_access_pattern_91 = false;
+std::vector<access_pattern> l1_write_pattern_91 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_91 = {
+{
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_91 = {8, 20, 24, 12};
+std::vector<uint32_t> ifm2_bound_91 = {8, 20, 23, 12};
+std::vector<uint32_t> ifm2sv_dim_91 = {8, 20, 2, 3};
+uint32_t ifm2sv_size_91 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_91 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_91 = 0;
+bool has_l1_wts_write_access_pattern_91 = false;
+std::vector<access_pattern> l1_wts_write_pattern_91 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_91 = {};
+
+
+std::vector<uint32_t> ofm_dim_91 = {8, 20, 24, 12};
+std::vector<uint32_t> ofm_bound_91 = {8, 20, 23, 12};
+std::vector<uint32_t> ofmsv_dim_91 = {8, 20, 2, 3};
+uint32_t ofmsv_size_91 = 960;
+uint32_t ofm_repetition_91 = 1;
+bool has_l1_read_access_pattern_91 = false;
+
+std::vector<access_pattern> l1_read_pattern_91 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_91 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 92
+// LayerName: Conv_151
+std::vector<uint32_t> ifm_dim_92 = {8, 20, 24, 12};
+std::vector<uint32_t> ifm_bound_92 = {8, 20, 23, 12};
+std::vector<uint32_t> ifmsv_dim_92 = {8, 32, 12, 1};
+uint32_t ifmsv_size_92 = 3072;
+uint32_t kernel_iter_92 = 6;
+bool has_l1_write_access_pattern_92 = false;
+std::vector<access_pattern> l1_write_pattern_92 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_92 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 32, 12, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 32, 12, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 32, 12, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 32, 12, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_92 = {8, 32, 12, 12};
+std::vector<uint32_t> ifm2_bound_92 = {8, 20, 10, 12};
+std::vector<uint32_t> ifm2sv_dim_92 = {8, 32, 3, 1};
+uint32_t ifm2sv_size_92 = 3072;
+std::vector<std::vector<access_pattern>> ifm2_pattern_92 = {
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_92 = {19200};
+std::vector<uint32_t> wts_dim_92 = {19200};
+std::vector<uint32_t> wtssv_dim_92 = {2400};
+uint32_t wtssv_size_92 = 2400;
+uint32_t wts_repetition_92 = 1;
+bool has_l1_wts_write_access_pattern_92 = false;
+std::vector<access_pattern> l1_wts_write_pattern_92 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_92 = {
+{
+  tiling({.buffer_dimension = {4800, 4}, .tiling_dimension = {2400, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 2400, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4800, 4}, .tiling_dimension = {2400, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 2400, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4800, 4}, .tiling_dimension = {2400, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 2400, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4800, 4}, .tiling_dimension = {2400, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 2400, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_92[] = {
+{
+  tiling({.buffer_dimension = {19200, 1}, .tiling_dimension = {9600, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {19200, 1}, .tiling_dimension = {9600, 1}, .offset = {9600, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_92[] = {
+{
+  tiling({.buffer_dimension = {19200}, .tiling_dimension = {9600}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {19200}, .tiling_dimension = {9600}, .offset = {9600}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_92 = {8, 32, 12, 12};
+std::vector<uint32_t> ofm_bound_92 = {8, 20, 10, 12};
+std::vector<uint32_t> ofmsv_dim_92 = {8, 32, 3, 1};
+uint32_t ofmsv_size_92 = 768;
+uint32_t ofm_repetition_92 = 2;
+bool has_l1_read_access_pattern_92 = false;
+
+std::vector<access_pattern> l1_read_pattern_92 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_92 = {
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 9, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 3, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 6, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 9, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 3, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 6, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 9, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 3, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 9, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 93
+// LayerName: Conv_153
+std::vector<uint32_t> ifm_dim_93 = {8, 32, 12, 12};
+std::vector<uint32_t> ifm_bound_93 = {8, 20, 10, 12};
+std::vector<uint32_t> ifmsv_dim_93 = {8, 8, 10, 3};
+uint32_t ifmsv_size_93 = 1920;
+uint32_t kernel_iter_93 = 3;
+bool has_l1_write_access_pattern_93 = false;
+std::vector<access_pattern> l1_write_pattern_93 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_93 = {
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 8, 10, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 8, 10, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 8, 10, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 8, 10, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_93 = {16128};
+std::vector<uint32_t> wts_dim_93 = {16128};
+std::vector<uint32_t> wtssv_dim_93 = {4032};
+uint32_t wtssv_size_93 = 4032;
+uint32_t wts_repetition_93 = 1;
+bool has_l1_wts_write_access_pattern_93 = false;
+std::vector<access_pattern> l1_wts_write_pattern_93 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_93 = {
+{
+  tiling({.buffer_dimension = {4032, 4}, .tiling_dimension = {4032, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4032, 4}, .tiling_dimension = {4032, 1}, .offset = {0, 1}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4032, 4}, .tiling_dimension = {4032, 1}, .offset = {0, 2}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4032, 4}, .tiling_dimension = {4032, 1}, .offset = {0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_93[] = {
+{
+  tiling({.buffer_dimension = {16128, 1}, .tiling_dimension = {8064, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {16128, 1}, .tiling_dimension = {8064, 1}, .offset = {8064, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_93[] = {
+{
+  tiling({.buffer_dimension = {16128}, .tiling_dimension = {8064}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {16128}, .tiling_dimension = {8064}, .offset = {8064}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_93 = {8, 24, 24, 12};
+std::vector<uint32_t> ofm_bound_93 = {8, 20, 23, 12};
+std::vector<uint32_t> ofmsv_dim_93 = {8, 8, 6, 3};
+uint32_t ofmsv_size_93 = 1152;
+uint32_t ofm_repetition_93 = 1;
+bool has_l1_read_access_pattern_93 = false;
+
+std::vector<access_pattern> l1_read_pattern_93 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_93 = {
+{
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 12, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 18, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 12, 3}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 18, 3}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 12, 6}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 18, 6}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 12, 9}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 8, 6, 3}, .offset = {0, 0, 18, 9}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 94
+// LayerName: Add_155
+std::vector<uint32_t> ifm_dim_94 = {8, 24, 24, 12};
+std::vector<uint32_t> ifm_bound_94 = {8, 20, 23, 12};
+std::vector<uint32_t> ifmsv_dim_94 = {8, 20, 2, 3};
+uint32_t ifmsv_size_94 = 3840;
+uint32_t kernel_iter_94 = 3;
+bool has_l1_write_access_pattern_94 = false;
+std::vector<access_pattern> l1_write_pattern_94 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_94 = {
+{
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_94 = 0;
+bool has_l1_wts_write_access_pattern_94 = false;
+std::vector<access_pattern> l1_wts_write_pattern_94 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_94 = {};
+
+
+std::vector<uint32_t> ofm_dim_94 = {8, 20, 24, 12};
+std::vector<uint32_t> ofm_bound_94 = {8, 20, 23, 12};
+std::vector<uint32_t> ofmsv_dim_94 = {8, 20, 2, 3};
+uint32_t ofmsv_size_94 = 960;
+uint32_t ofm_repetition_94 = 1;
+bool has_l1_read_access_pattern_94 = false;
+
+std::vector<access_pattern> l1_read_pattern_94 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_94 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 95
+// LayerName: Clip_158
+std::vector<uint32_t> ifm_dim_95 = {8, 20, 24, 12};
+std::vector<uint32_t> ifm_bound_95 = {8, 20, 23, 12};
+std::vector<uint32_t> ifmsv_dim_95 = {8, 20, 2, 3};
+uint32_t ifmsv_size_95 = 3840;
+uint32_t kernel_iter_95 = 3;
+bool has_l1_write_access_pattern_95 = false;
+std::vector<access_pattern> l1_write_pattern_95 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_95 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_95 = 0;
+bool has_l1_wts_write_access_pattern_95 = false;
+std::vector<access_pattern> l1_wts_write_pattern_95 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_95 = {};
+
+
+std::vector<uint32_t> ofm_dim_95 = {8, 20, 24, 12};
+std::vector<uint32_t> ofm_bound_95 = {8, 20, 23, 12};
+std::vector<uint32_t> ofmsv_dim_95 = {8, 20, 2, 3};
+uint32_t ofmsv_size_95 = 960;
+uint32_t ofm_repetition_95 = 1;
+bool has_l1_read_access_pattern_95 = false;
+
+std::vector<access_pattern> l1_read_pattern_95 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_95 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 96
+// LayerName: Div_160
+std::vector<uint32_t> ifm_dim_96 = {8, 20, 24, 12};
+std::vector<uint32_t> ifm_bound_96 = {8, 20, 23, 12};
+std::vector<uint32_t> ifmsv_dim_96 = {8, 20, 2, 3};
+uint32_t ifmsv_size_96 = 3840;
+uint32_t kernel_iter_96 = 3;
+bool has_l1_write_access_pattern_96 = false;
+std::vector<access_pattern> l1_write_pattern_96 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_96 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_96 = 0;
+bool has_l1_wts_write_access_pattern_96 = false;
+std::vector<access_pattern> l1_wts_write_pattern_96 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_96 = {};
+
+
+std::vector<uint32_t> ofm_dim_96 = {8, 20, 24, 12};
+std::vector<uint32_t> ofm_bound_96 = {8, 20, 23, 12};
+std::vector<uint32_t> ofmsv_dim_96 = {8, 20, 2, 3};
+uint32_t ofmsv_size_96 = 960;
+uint32_t ofm_repetition_96 = 1;
+bool has_l1_read_access_pattern_96 = false;
+
+std::vector<access_pattern> l1_read_pattern_96 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_96 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 97
+// LayerName: Mul_161
+std::vector<uint32_t> ifm_dim_97 = {8, 24, 24, 12};
+std::vector<uint32_t> ifm_bound_97 = {8, 20, 23, 12};
+std::vector<uint32_t> ifmsv_dim_97 = {8, 20, 2, 3};
+uint32_t ifmsv_size_97 = 3840;
+uint32_t kernel_iter_97 = 3;
+bool has_l1_write_access_pattern_97 = false;
+std::vector<access_pattern> l1_write_pattern_97 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_97 = {
+{
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_97 = {8, 20, 24, 12};
+std::vector<uint32_t> ifm2_bound_97 = {8, 20, 23, 12};
+std::vector<uint32_t> ifm2sv_dim_97 = {8, 20, 2, 3};
+uint32_t ifm2sv_size_97 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_97 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_97 = 0;
+bool has_l1_wts_write_access_pattern_97 = false;
+std::vector<access_pattern> l1_wts_write_pattern_97 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_97 = {};
+
+
+std::vector<uint32_t> ofm_dim_97 = {8, 20, 24, 12};
+std::vector<uint32_t> ofm_bound_97 = {8, 20, 23, 12};
+std::vector<uint32_t> ofmsv_dim_97 = {8, 20, 2, 3};
+uint32_t ofmsv_size_97 = 960;
+uint32_t ofm_repetition_97 = 1;
+bool has_l1_read_access_pattern_97 = false;
+
+std::vector<access_pattern> l1_read_pattern_97 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_97 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 98
+// LayerName: Conv_162
+std::vector<uint32_t> ifm_dim_98 = {8, 20, 24, 12};
+std::vector<uint32_t> ifm_bound_98 = {8, 20, 23, 12};
+std::vector<uint32_t> ifmsv_dim_98 = {8, 28, 1, 6};
+uint32_t ifmsv_size_98 = 5376;
+uint32_t kernel_iter_98 = 6;
+bool has_l1_write_access_pattern_98 = false;
+std::vector<access_pattern> l1_write_pattern_98 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_98 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, -1}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 24} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 24} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 7}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 24} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 11}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 24} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_98 = {3072};
+std::vector<uint32_t> wts_dim_98 = {3072};
+std::vector<uint32_t> wtssv_dim_98 = {128};
+uint32_t wts_repetition_98 = 1;
+uint32_t wtssv_size_98 = 128;
+bool has_l1_wts_write_access_pattern_98 = false;
+std::vector<access_pattern> l1_wts_write_pattern_98 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_98 = {
+{
+  tiling({.buffer_dimension = {3072}, .tiling_dimension = {128}, .offset = {0}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {3072}, .tiling_dimension = {128}, .offset = {128}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {3072}, .tiling_dimension = {128}, .offset = {256}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {3072}, .tiling_dimension = {128}, .offset = {384}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_98[] = {
+{
+  tiling({.buffer_dimension = {3072, 1}, .tiling_dimension = {1536, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {3072, 1}, .tiling_dimension = {1536, 1}, .offset = {1536, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_98[] = {
+{
+  tiling({.buffer_dimension = {3072}, .tiling_dimension = {1536}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {3072}, .tiling_dimension = {1536}, .offset = {1536}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_98 = {8, 24, 24, 16};
+std::vector<uint32_t> ofm_bound_98 = {8, 20, 23, 12};
+std::vector<uint32_t> ofmsv_dim_98 = {8, 24, 1, 4};
+uint32_t ofmsv_size_98 = 768;
+uint32_t ofm_repetition_98 = 1;
+bool has_l1_read_access_pattern_98 = false;
+
+std::vector<access_pattern> l1_read_pattern_98 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_98 = {
+{
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 1, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 2, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 3, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 1, 8}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 2, 8}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 3, 8}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 1, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 3, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 99
+// LayerName: Add_164
+std::vector<uint32_t> ifm_dim_99 = {8, 24, 24, 16};
+std::vector<uint32_t> ifm_bound_99 = {8, 20, 23, 12};
+std::vector<uint32_t> ifmsv_dim_99 = {8, 20, 2, 3};
+uint32_t ifmsv_size_99 = 3840;
+uint32_t kernel_iter_99 = 3;
+bool has_l1_write_access_pattern_99 = false;
+std::vector<access_pattern> l1_write_pattern_99 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_99 = {
+{
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_99 = 0;
+bool has_l1_wts_write_access_pattern_99 = false;
+std::vector<access_pattern> l1_wts_write_pattern_99 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_99 = {};
+
+
+std::vector<uint32_t> ofm_dim_99 = {8, 20, 24, 12};
+std::vector<uint32_t> ofm_bound_99 = {8, 20, 23, 12};
+std::vector<uint32_t> ofmsv_dim_99 = {8, 20, 2, 3};
+uint32_t ofmsv_size_99 = 960;
+uint32_t ofm_repetition_99 = 1;
+bool has_l1_read_access_pattern_99 = false;
+
+std::vector<access_pattern> l1_read_pattern_99 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_99 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 100
+// LayerName: Clip_167
+std::vector<uint32_t> ifm_dim_100 = {8, 20, 24, 12};
+std::vector<uint32_t> ifm_bound_100 = {8, 20, 23, 12};
+std::vector<uint32_t> ifmsv_dim_100 = {8, 20, 2, 3};
+uint32_t ifmsv_size_100 = 3840;
+uint32_t kernel_iter_100 = 3;
+bool has_l1_write_access_pattern_100 = false;
+std::vector<access_pattern> l1_write_pattern_100 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_100 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_100 = 0;
+bool has_l1_wts_write_access_pattern_100 = false;
+std::vector<access_pattern> l1_wts_write_pattern_100 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_100 = {};
+
+
+std::vector<uint32_t> ofm_dim_100 = {8, 20, 24, 12};
+std::vector<uint32_t> ofm_bound_100 = {8, 20, 23, 12};
+std::vector<uint32_t> ofmsv_dim_100 = {8, 20, 2, 3};
+uint32_t ofmsv_size_100 = 960;
+uint32_t ofm_repetition_100 = 1;
+bool has_l1_read_access_pattern_100 = false;
+
+std::vector<access_pattern> l1_read_pattern_100 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_100 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 101
+// LayerName: Div_169
+std::vector<uint32_t> ifm_dim_101 = {8, 20, 24, 12};
+std::vector<uint32_t> ifm_bound_101 = {8, 20, 23, 12};
+std::vector<uint32_t> ifmsv_dim_101 = {8, 20, 2, 3};
+uint32_t ifmsv_size_101 = 3840;
+uint32_t kernel_iter_101 = 3;
+bool has_l1_write_access_pattern_101 = false;
+std::vector<access_pattern> l1_write_pattern_101 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_101 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_101 = 0;
+bool has_l1_wts_write_access_pattern_101 = false;
+std::vector<access_pattern> l1_wts_write_pattern_101 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_101 = {};
+
+
+std::vector<uint32_t> ofm_dim_101 = {8, 20, 24, 12};
+std::vector<uint32_t> ofm_bound_101 = {8, 20, 23, 12};
+std::vector<uint32_t> ofmsv_dim_101 = {8, 20, 2, 3};
+uint32_t ofmsv_size_101 = 960;
+uint32_t ofm_repetition_101 = 1;
+bool has_l1_read_access_pattern_101 = false;
+
+std::vector<access_pattern> l1_read_pattern_101 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_101 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 102
+// LayerName: Mul_170
+std::vector<uint32_t> ifm_dim_102 = {8, 24, 24, 16};
+std::vector<uint32_t> ifm_bound_102 = {8, 20, 23, 12};
+std::vector<uint32_t> ifmsv_dim_102 = {8, 20, 2, 3};
+uint32_t ifmsv_size_102 = 3840;
+uint32_t kernel_iter_102 = 3;
+bool has_l1_write_access_pattern_102 = false;
+std::vector<access_pattern> l1_write_pattern_102 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_102 = {
+{
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 24, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_102 = {8, 20, 24, 12};
+std::vector<uint32_t> ifm2_bound_102 = {8, 20, 23, 12};
+std::vector<uint32_t> ifm2sv_dim_102 = {8, 20, 2, 3};
+uint32_t ifm2sv_size_102 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_102 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 12} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_102 = 0;
+bool has_l1_wts_write_access_pattern_102 = false;
+std::vector<access_pattern> l1_wts_write_pattern_102 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_102 = {};
+
+
+std::vector<uint32_t> ofm_dim_102 = {8, 20, 24, 12};
+std::vector<uint32_t> ofm_bound_102 = {8, 20, 23, 12};
+std::vector<uint32_t> ofmsv_dim_102 = {8, 20, 2, 3};
+uint32_t ofmsv_size_102 = 960;
+uint32_t ofm_repetition_102 = 1;
+bool has_l1_read_access_pattern_102 = false;
+
+std::vector<access_pattern> l1_read_pattern_102 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_102 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 103
+// LayerName: Conv_171
+std::vector<uint32_t> ifm_dim_103 = {8, 20, 24, 12};
+std::vector<uint32_t> ifm_bound_103 = {8, 20, 23, 12};
+std::vector<uint32_t> ifmsv_dim_103 = {8, 32, 12, 1};
+uint32_t ifmsv_size_103 = 3072;
+uint32_t kernel_iter_103 = 6;
+bool has_l1_write_access_pattern_103 = false;
+std::vector<access_pattern> l1_write_pattern_103 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_103 = {
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 32, 12, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 32, 12, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 32, 12, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 24, 12}, .tiling_dimension = {8, 32, 12, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 23, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_103 = {8, 32, 12, 12};
+std::vector<uint32_t> ifm2_bound_103 = {8, 20, 10, 12};
+std::vector<uint32_t> ifm2sv_dim_103 = {8, 32, 3, 1};
+uint32_t ifm2sv_size_103 = 3072;
+std::vector<std::vector<access_pattern>> ifm2_pattern_103 = {
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_103 = {19200};
+std::vector<uint32_t> wts_dim_103 = {19200};
+std::vector<uint32_t> wtssv_dim_103 = {2400};
+uint32_t wtssv_size_103 = 2400;
+uint32_t wts_repetition_103 = 1;
+bool has_l1_wts_write_access_pattern_103 = false;
+std::vector<access_pattern> l1_wts_write_pattern_103 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_103 = {
+{
+  tiling({.buffer_dimension = {4800, 4}, .tiling_dimension = {2400, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 2400, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4800, 4}, .tiling_dimension = {2400, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 2400, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4800, 4}, .tiling_dimension = {2400, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 2400, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4800, 4}, .tiling_dimension = {2400, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 2400, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_103[] = {
+{
+  tiling({.buffer_dimension = {19200, 1}, .tiling_dimension = {9600, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {19200, 1}, .tiling_dimension = {9600, 1}, .offset = {9600, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_103[] = {
+{
+  tiling({.buffer_dimension = {19200}, .tiling_dimension = {9600}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {19200}, .tiling_dimension = {9600}, .offset = {9600}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_103 = {8, 32, 12, 12};
+std::vector<uint32_t> ofm_bound_103 = {8, 20, 10, 12};
+std::vector<uint32_t> ofmsv_dim_103 = {8, 32, 3, 1};
+uint32_t ofmsv_size_103 = 768;
+uint32_t ofm_repetition_103 = 2;
+bool has_l1_read_access_pattern_103 = false;
+
+std::vector<access_pattern> l1_read_pattern_103 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_103 = {
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 9, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 3, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 6, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 9, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 3, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 6, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 9, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 3, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 9, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 104
+// LayerName: Conv_173
+std::vector<uint32_t> ifm_dim_104 = {8, 32, 12, 12};
+std::vector<uint32_t> ifm_bound_104 = {8, 20, 10, 12};
+std::vector<uint32_t> ifmsv_dim_104 = {8, 32, 10, 1};
+uint32_t ifmsv_size_104 = 2560;
+uint32_t kernel_iter_104 = 9;
+bool has_l1_write_access_pattern_104 = true;
+std::vector<access_pattern> l1_write_pattern_104 = {tiling({.buffer_dimension = {8, 32, 10, 1}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_104 = {
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 12, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {8, 20, 10, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_104 = {40320};
+std::vector<uint32_t> wts_dim_104 = {40320};
+std::vector<uint32_t> wtssv_dim_104 = {3360};
+uint32_t wtssv_size_104 = 3360;
+uint32_t wts_repetition_104 = 1;
+bool has_l1_wts_write_access_pattern_104 = false;
+std::vector<access_pattern> l1_wts_write_pattern_104 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_104 = {
+{
+  tiling({.buffer_dimension = {3360, 12}, .tiling_dimension = {3360, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {3360, 12}, .tiling_dimension = {3360, 1}, .offset = {0, 4}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {3360, 12}, .tiling_dimension = {3360, 1}, .offset = {0, 8}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {3360, 12}, .tiling_dimension = {3360, 1}, .offset = {0, 1}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {3360, 12}, .tiling_dimension = {3360, 1}, .offset = {0, 5}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {3360, 12}, .tiling_dimension = {3360, 1}, .offset = {0, 9}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {3360, 12}, .tiling_dimension = {3360, 1}, .offset = {0, 2}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {3360, 12}, .tiling_dimension = {3360, 1}, .offset = {0, 6}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {3360, 12}, .tiling_dimension = {3360, 1}, .offset = {0, 10}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {3360, 12}, .tiling_dimension = {3360, 1}, .offset = {0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {3360, 12}, .tiling_dimension = {3360, 1}, .offset = {0, 7}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {3360, 12}, .tiling_dimension = {3360, 1}, .offset = {0, 11}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_104[] = {
+{
+  tiling({.buffer_dimension = {40320, 1}, .tiling_dimension = {20160, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {40320, 1}, .tiling_dimension = {20160, 1}, .offset = {20160, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_104[] = {
+{
+  tiling({.buffer_dimension = {40320}, .tiling_dimension = {20160}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {40320}, .tiling_dimension = {20160}, .offset = {20160}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_104 = {8, 32, 60, 12};
+std::vector<uint32_t> ofm_bound_104 = {8, 20, 60, 12};
+std::vector<uint32_t> ofmsv_dim_104 = {8, 32, 5, 1};
+uint32_t ofmsv_size_104 = 1280;
+uint32_t ofm_repetition_104 = 1;
+bool has_l1_read_access_pattern_104 = false;
+
+std::vector<access_pattern> l1_read_pattern_104 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_104 = {
+{
+  tiling({.buffer_dimension = {8, 32, 60, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 60, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 5, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 60, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 10, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 60, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 15, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 60, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 60, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 5, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 60, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 10, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 60, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 15, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 60, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 60, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 5, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 60, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 10, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 60, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 15, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 60, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 60, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 5, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 60, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 10, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 60, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 15, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 105
+// LayerName: Add_175
+std::vector<uint32_t> ifm_dim_105 = {8, 32, 60, 12};
+std::vector<uint32_t> ifm_bound_105 = {8, 20, 60, 12};
+std::vector<uint32_t> ifmsv_dim_105 = {8, 20, 4, 3};
+uint32_t ifmsv_size_105 = 7680;
+uint32_t kernel_iter_105 = 4;
+bool has_l1_write_access_pattern_105 = false;
+std::vector<access_pattern> l1_write_pattern_105 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_105 = {
+{
+  tiling({.buffer_dimension = {8, 32, 60, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 60, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 60, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 60, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_105 = 0;
+bool has_l1_wts_write_access_pattern_105 = false;
+std::vector<access_pattern> l1_wts_write_pattern_105 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_105 = {};
+
+
+std::vector<uint32_t> ofm_dim_105 = {8, 20, 64, 12};
+std::vector<uint32_t> ofm_bound_105 = {8, 20, 60, 12};
+std::vector<uint32_t> ofmsv_dim_105 = {8, 20, 4, 3};
+uint32_t ofmsv_size_105 = 1920;
+uint32_t ofm_repetition_105 = 1;
+bool has_l1_read_access_pattern_105 = false;
+
+std::vector<access_pattern> l1_read_pattern_105 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_105 = {
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 106
+// LayerName: Clip_178
+std::vector<uint32_t> ifm_dim_106 = {8, 20, 64, 12};
+std::vector<uint32_t> ifm_bound_106 = {8, 20, 60, 12};
+std::vector<uint32_t> ifmsv_dim_106 = {8, 20, 4, 3};
+uint32_t ifmsv_size_106 = 7680;
+uint32_t kernel_iter_106 = 4;
+bool has_l1_write_access_pattern_106 = false;
+std::vector<access_pattern> l1_write_pattern_106 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_106 = {
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_106 = 0;
+bool has_l1_wts_write_access_pattern_106 = false;
+std::vector<access_pattern> l1_wts_write_pattern_106 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_106 = {};
+
+
+std::vector<uint32_t> ofm_dim_106 = {8, 20, 64, 12};
+std::vector<uint32_t> ofm_bound_106 = {8, 20, 60, 12};
+std::vector<uint32_t> ofmsv_dim_106 = {8, 20, 4, 3};
+uint32_t ofmsv_size_106 = 1920;
+uint32_t ofm_repetition_106 = 1;
+bool has_l1_read_access_pattern_106 = false;
+
+std::vector<access_pattern> l1_read_pattern_106 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_106 = {
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 107
+// LayerName: Div_180
+std::vector<uint32_t> ifm_dim_107 = {8, 20, 64, 12};
+std::vector<uint32_t> ifm_bound_107 = {8, 20, 60, 12};
+std::vector<uint32_t> ifmsv_dim_107 = {8, 20, 4, 3};
+uint32_t ifmsv_size_107 = 7680;
+uint32_t kernel_iter_107 = 4;
+bool has_l1_write_access_pattern_107 = false;
+std::vector<access_pattern> l1_write_pattern_107 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_107 = {
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_107 = 0;
+bool has_l1_wts_write_access_pattern_107 = false;
+std::vector<access_pattern> l1_wts_write_pattern_107 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_107 = {};
+
+
+std::vector<uint32_t> ofm_dim_107 = {8, 20, 64, 12};
+std::vector<uint32_t> ofm_bound_107 = {8, 20, 60, 12};
+std::vector<uint32_t> ofmsv_dim_107 = {8, 20, 4, 3};
+uint32_t ofmsv_size_107 = 1920;
+uint32_t ofm_repetition_107 = 1;
+bool has_l1_read_access_pattern_107 = false;
+
+std::vector<access_pattern> l1_read_pattern_107 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_107 = {
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 108
+// LayerName: Mul_181
+std::vector<uint32_t> ifm_dim_108 = {8, 32, 60, 12};
+std::vector<uint32_t> ifm_bound_108 = {8, 20, 60, 12};
+std::vector<uint32_t> ifmsv_dim_108 = {8, 20, 2, 3};
+uint32_t ifmsv_size_108 = 3840;
+uint32_t kernel_iter_108 = 8;
+bool has_l1_write_access_pattern_108 = false;
+std::vector<access_pattern> l1_write_pattern_108 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_108 = {
+{
+  tiling({.buffer_dimension = {8, 32, 60, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 32} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 60, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 32} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 60, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 32} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 60, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 32} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_108 = {8, 20, 64, 12};
+std::vector<uint32_t> ifm2_bound_108 = {8, 20, 60, 12};
+std::vector<uint32_t> ifm2sv_dim_108 = {8, 20, 2, 3};
+uint32_t ifm2sv_size_108 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_108 = {
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 32} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 32} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 32} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 32} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_108 = 0;
+bool has_l1_wts_write_access_pattern_108 = false;
+std::vector<access_pattern> l1_wts_write_pattern_108 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_108 = {};
+
+
+std::vector<uint32_t> ofm_dim_108 = {8, 20, 64, 12};
+std::vector<uint32_t> ofm_bound_108 = {8, 20, 60, 12};
+std::vector<uint32_t> ofmsv_dim_108 = {8, 20, 2, 3};
+uint32_t ofmsv_size_108 = 960;
+uint32_t ofm_repetition_108 = 1;
+bool has_l1_read_access_pattern_108 = false;
+
+std::vector<access_pattern> l1_read_pattern_108 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_108 = {
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 109
+// LayerName: Conv_182
+std::vector<uint32_t> ifm_dim_109 = {8, 20, 64, 12};
+std::vector<uint32_t> ifm_bound_109 = {8, 20, 60, 12};
+std::vector<uint32_t> ifmsv_dim_109 = {8, 28, 1, 6};
+uint32_t ifmsv_size_109 = 5376;
+uint32_t kernel_iter_109 = 15;
+bool has_l1_write_access_pattern_109 = false;
+std::vector<access_pattern> l1_write_pattern_109 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_109 = {
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, -1}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 60} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 60} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 7}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 60} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 11}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 60} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_109 = {7680};
+std::vector<uint32_t> wts_dim_109 = {7680};
+std::vector<uint32_t> wtssv_dim_109 = {128};
+uint32_t wts_repetition_109 = 1;
+uint32_t wtssv_size_109 = 128;
+bool has_l1_wts_write_access_pattern_109 = false;
+std::vector<access_pattern> l1_wts_write_pattern_109 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_109 = {
+{
+  tiling({.buffer_dimension = {7680}, .tiling_dimension = {128}, .offset = {0}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 15} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {7680}, .tiling_dimension = {128}, .offset = {128}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 15} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {7680}, .tiling_dimension = {128}, .offset = {256}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 15} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {7680}, .tiling_dimension = {128}, .offset = {384}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 15} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_109[] = {
+{
+  tiling({.buffer_dimension = {7680, 1}, .tiling_dimension = {3840, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {7680, 1}, .tiling_dimension = {3840, 1}, .offset = {3840, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_109[] = {
+{
+  tiling({.buffer_dimension = {7680}, .tiling_dimension = {3840}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {7680}, .tiling_dimension = {3840}, .offset = {3840}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_109 = {8, 24, 60, 16};
+std::vector<uint32_t> ofm_bound_109 = {8, 20, 60, 12};
+std::vector<uint32_t> ofmsv_dim_109 = {8, 24, 1, 4};
+uint32_t ofmsv_size_109 = 768;
+uint32_t ofm_repetition_109 = 1;
+bool has_l1_read_access_pattern_109 = false;
+
+std::vector<access_pattern> l1_read_pattern_109 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_109 = {
+{
+  tiling({.buffer_dimension = {8, 24, 60, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 15} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 60, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 15} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 60, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 15} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 60, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 15} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 60, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 15} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 60, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 1, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 15} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 60, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 2, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 15} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 60, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 3, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 15} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 60, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 15} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 60, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 1, 8}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 15} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 60, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 2, 8}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 15} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 60, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 3, 8}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 15} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 60, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 15} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 60, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 1, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 15} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 60, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 15} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 60, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 3, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 15} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 110
+// LayerName: Add_184
+std::vector<uint32_t> ifm_dim_110 = {8, 24, 60, 16};
+std::vector<uint32_t> ifm_bound_110 = {8, 20, 60, 12};
+std::vector<uint32_t> ifmsv_dim_110 = {8, 20, 4, 3};
+uint32_t ifmsv_size_110 = 7680;
+uint32_t kernel_iter_110 = 4;
+bool has_l1_write_access_pattern_110 = false;
+std::vector<access_pattern> l1_write_pattern_110 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_110 = {
+{
+  tiling({.buffer_dimension = {8, 24, 60, 16}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 60, 16}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 60, 16}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 60, 16}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_110 = 0;
+bool has_l1_wts_write_access_pattern_110 = false;
+std::vector<access_pattern> l1_wts_write_pattern_110 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_110 = {};
+
+
+std::vector<uint32_t> ofm_dim_110 = {8, 20, 64, 12};
+std::vector<uint32_t> ofm_bound_110 = {8, 20, 60, 12};
+std::vector<uint32_t> ofmsv_dim_110 = {8, 20, 4, 3};
+uint32_t ofmsv_size_110 = 1920;
+uint32_t ofm_repetition_110 = 1;
+bool has_l1_read_access_pattern_110 = false;
+
+std::vector<access_pattern> l1_read_pattern_110 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_110 = {
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 111
+// LayerName: Clip_187
+std::vector<uint32_t> ifm_dim_111 = {8, 20, 64, 12};
+std::vector<uint32_t> ifm_bound_111 = {8, 20, 60, 12};
+std::vector<uint32_t> ifmsv_dim_111 = {8, 20, 4, 3};
+uint32_t ifmsv_size_111 = 7680;
+uint32_t kernel_iter_111 = 4;
+bool has_l1_write_access_pattern_111 = false;
+std::vector<access_pattern> l1_write_pattern_111 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_111 = {
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_111 = 0;
+bool has_l1_wts_write_access_pattern_111 = false;
+std::vector<access_pattern> l1_wts_write_pattern_111 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_111 = {};
+
+
+std::vector<uint32_t> ofm_dim_111 = {8, 20, 64, 12};
+std::vector<uint32_t> ofm_bound_111 = {8, 20, 60, 12};
+std::vector<uint32_t> ofmsv_dim_111 = {8, 20, 4, 3};
+uint32_t ofmsv_size_111 = 1920;
+uint32_t ofm_repetition_111 = 1;
+bool has_l1_read_access_pattern_111 = false;
+
+std::vector<access_pattern> l1_read_pattern_111 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_111 = {
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 112
+// LayerName: Div_189
+std::vector<uint32_t> ifm_dim_112 = {8, 20, 64, 12};
+std::vector<uint32_t> ifm_bound_112 = {8, 20, 60, 12};
+std::vector<uint32_t> ifmsv_dim_112 = {8, 20, 4, 3};
+uint32_t ifmsv_size_112 = 7680;
+uint32_t kernel_iter_112 = 4;
+bool has_l1_write_access_pattern_112 = false;
+std::vector<access_pattern> l1_write_pattern_112 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_112 = {
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 16} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_112 = 0;
+bool has_l1_wts_write_access_pattern_112 = false;
+std::vector<access_pattern> l1_wts_write_pattern_112 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_112 = {};
+
+
+std::vector<uint32_t> ofm_dim_112 = {8, 20, 64, 12};
+std::vector<uint32_t> ofm_bound_112 = {8, 20, 60, 12};
+std::vector<uint32_t> ofmsv_dim_112 = {8, 20, 4, 3};
+uint32_t ofmsv_size_112 = 1920;
+uint32_t ofm_repetition_112 = 1;
+bool has_l1_read_access_pattern_112 = false;
+
+std::vector<access_pattern> l1_read_pattern_112 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_112 = {
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 113
+// LayerName: Mul_190
+std::vector<uint32_t> ifm_dim_113 = {8, 24, 60, 16};
+std::vector<uint32_t> ifm_bound_113 = {8, 20, 60, 12};
+std::vector<uint32_t> ifmsv_dim_113 = {8, 20, 2, 3};
+uint32_t ifmsv_size_113 = 3840;
+uint32_t kernel_iter_113 = 8;
+bool has_l1_write_access_pattern_113 = false;
+std::vector<access_pattern> l1_write_pattern_113 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_113 = {
+{
+  tiling({.buffer_dimension = {8, 24, 60, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 32} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 60, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 32} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 60, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 32} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 60, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 32} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_113 = {8, 20, 64, 12};
+std::vector<uint32_t> ifm2_bound_113 = {8, 20, 60, 12};
+std::vector<uint32_t> ifm2sv_dim_113 = {8, 20, 2, 3};
+uint32_t ifm2sv_size_113 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_113 = {
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 32} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 32} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 32} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 32} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_113 = 0;
+bool has_l1_wts_write_access_pattern_113 = false;
+std::vector<access_pattern> l1_wts_write_pattern_113 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_113 = {};
+
+
+std::vector<uint32_t> ofm_dim_113 = {8, 20, 64, 12};
+std::vector<uint32_t> ofm_bound_113 = {8, 20, 60, 12};
+std::vector<uint32_t> ofmsv_dim_113 = {8, 20, 2, 3};
+uint32_t ofmsv_size_113 = 960;
+uint32_t ofm_repetition_113 = 1;
+bool has_l1_read_access_pattern_113 = false;
+
+std::vector<access_pattern> l1_read_pattern_113 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_113 = {
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 115
+// LayerName: Generated-#26
+std::vector<uint32_t> ifm_dim_115 = {8, 240, 60, 1};
+std::vector<uint32_t> ifm_bound_115 = {8, 240, 60, 1};
+std::vector<uint32_t> ifmsv_dim_115 = {8, 48, 5, 1};
+uint32_t ifmsv_size_115 = 7680;
+uint32_t kernel_iter_115 = 15;
+bool has_l1_write_access_pattern_115 = false;
+std::vector<access_pattern> l1_write_pattern_115 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_115 = {
+{
+  tiling({.buffer_dimension = {8, 240, 60, 1}, .tiling_dimension = {8, 48, 5, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 5, .wrap = 4}, {.dimension = 1, .stride = 48, .wrap = 5}, {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 240, 60, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 240, 60, 1}, .tiling_dimension = {8, 48, 5, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 5, .wrap = 4}, {.dimension = 1, .stride = 48, .wrap = 5}, {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 240, 60, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 240, 60, 1}, .tiling_dimension = {8, 48, 5, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 5, .wrap = 4}, {.dimension = 1, .stride = 48, .wrap = 5}, {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 240, 60, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 240, 60, 1}, .tiling_dimension = {8, 48, 5, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 5, .wrap = 4}, {.dimension = 1, .stride = 48, .wrap = 5}, {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 240, 60, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_115 = 0;
+bool has_l1_wts_write_access_pattern_115 = false;
+std::vector<access_pattern> l1_wts_write_pattern_115 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_115 = {};
+
+
+std::vector<uint32_t> ofm_dim_115 = {8, 1, 60, 4};
+std::vector<uint32_t> ofm_bound_115 = {8, 1, 60, 1};
+std::vector<uint32_t> ofmsv_dim_115 = {8, 1, 5, 1};
+uint32_t ofmsv_size_115 = 40;
+uint32_t ofm_repetition_115 = 5;
+bool has_l1_read_access_pattern_115 = false;
+std::vector<access_pattern> l1_read_pattern_115 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ofm_pattern_115 = {
+{
+  tiling({.buffer_dimension = {8, 1, 60, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 60, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 5, 0}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 60, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 10, 0}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 60, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 15, 0}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 60, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 60, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 5, 1}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 60, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 10, 1}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 60, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 15, 1}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 60, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 60, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 5, 2}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 60, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 10, 2}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 60, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 15, 2}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 60, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 60, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 5, 3}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 60, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 10, 3}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 60, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 15, 3}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 116
+// LayerName: Conv_192
+std::vector<uint32_t> ifm_dim_116 = {8, 1, 60, 4};
+std::vector<uint32_t> ifm_bound_116 = {8, 1, 60, 1};
+std::vector<uint32_t> ifmsv_dim_116 = {8, 8, 15, 1};
+uint32_t ifmsv_size_116 = 960;
+uint32_t kernel_iter_116 = 4;
+bool has_l1_write_access_pattern_116 = false;
+std::vector<access_pattern> l1_write_pattern_116 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_116 = {
+{
+  tiling({.buffer_dimension = {8, 1, 60, 4}, .tiling_dimension = {8, 8, 15, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 15, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 60, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 60, 4}, .tiling_dimension = {8, 8, 15, 1}, .offset = {0, 8, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 15, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 60, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 60, 4}, .tiling_dimension = {8, 8, 15, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 15, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 60, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 60, 4}, .tiling_dimension = {8, 8, 15, 1}, .offset = {0, 24, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 15, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 60, 1}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_116 = {63488};
+std::vector<uint32_t> wts_dim_116 = {63488};
+std::vector<uint32_t> wtssv_dim_116 = {3968};
+uint32_t wtssv_size_116 = 3968;
+uint32_t wts_repetition_116 = 1;
+bool has_l1_wts_write_access_pattern_116 = false;
+std::vector<access_pattern> l1_wts_write_pattern_116 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_116 = {
+{
+  tiling({.buffer_dimension = {15872, 4}, .tiling_dimension = {3968, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 3968, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {15872, 4}, .tiling_dimension = {3968, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 3968, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {15872, 4}, .tiling_dimension = {3968, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 3968, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {15872, 4}, .tiling_dimension = {3968, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 3968, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_116[] = {
+{
+  tiling({.buffer_dimension = {63488, 1}, .tiling_dimension = {31744, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {63488, 1}, .tiling_dimension = {31744, 1}, .offset = {31744, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_116[] = {
+{
+  tiling({.buffer_dimension = {63488}, .tiling_dimension = {31744}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {63488}, .tiling_dimension = {31744}, .offset = {31744}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_116 = {8, 32, 16, 1};
+std::vector<uint32_t> ofm_bound_116 = {8, 1, 15, 1};
+std::vector<uint32_t> ofmsv_dim_116 = {8, 8, 4, 1};
+uint32_t ofmsv_size_116 = 256;
+uint32_t ofm_repetition_116 = 4;
+bool has_l1_read_access_pattern_116 = false;
+
+std::vector<access_pattern> l1_read_pattern_116 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_116 = {
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 0, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 0, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 8, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 8, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 8, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 8, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 16, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 16, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 16, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 24, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 24, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 24, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 24, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 117
+// LayerName: Conv_194
+std::vector<uint32_t> ifm_dim_117 = {8, 32, 16, 1};
+std::vector<uint32_t> ifm_bound_117 = {8, 1, 15, 1};
+std::vector<uint32_t> ifmsv_dim_117 = {8, 8, 15, 1};
+uint32_t ifmsv_size_117 = 960;
+uint32_t kernel_iter_117 = 4;
+bool has_l1_write_access_pattern_117 = false;
+std::vector<access_pattern> l1_write_pattern_117 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_117 = {
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 15, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 4, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 15, 1}, .offset = {0, 8, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 4, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 15, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 4, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 1}, .tiling_dimension = {8, 8, 15, 1}, .offset = {0, 24, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 4, .boundary_dimension = {8, 1, 15, 1}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_117 = {63488};
+std::vector<uint32_t> wts_dim_117 = {63488};
+std::vector<uint32_t> wtssv_dim_117 = {3968};
+uint32_t wtssv_size_117 = 3968;
+uint32_t wts_repetition_117 = 1;
+bool has_l1_wts_write_access_pattern_117 = false;
+std::vector<access_pattern> l1_wts_write_pattern_117 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_117 = {
+{
+  tiling({.buffer_dimension = {3968, 16}, .tiling_dimension = {3968, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 1, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {3968, 16}, .tiling_dimension = {3968, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 1, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {3968, 16}, .tiling_dimension = {3968, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 1, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {3968, 16}, .tiling_dimension = {3968, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 1, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_117[] = {
+{
+  tiling({.buffer_dimension = {63488, 1}, .tiling_dimension = {31744, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {63488, 1}, .tiling_dimension = {31744, 1}, .offset = {31744, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_117[] = {
+{
+  tiling({.buffer_dimension = {63488}, .tiling_dimension = {31744}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {63488}, .tiling_dimension = {31744}, .offset = {31744}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_117 = {8, 32, 64, 1};
+std::vector<uint32_t> ofm_bound_117 = {8, 1, 60, 1};
+std::vector<uint32_t> ofmsv_dim_117 = {8, 8, 4, 1};
+uint32_t ofmsv_size_117 = 256;
+uint32_t ofm_repetition_117 = 1;
+bool has_l1_read_access_pattern_117 = false;
+
+std::vector<access_pattern> l1_read_pattern_117 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_117 = {
+{
+  tiling({.buffer_dimension = {8, 32, 64, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 64, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 64, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 0, 8, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 64, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 0, 12, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 64, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 8, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 64, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 8, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 64, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 8, 8, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 64, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 8, 12, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 64, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 64, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 16, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 64, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 16, 8, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 64, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 16, 12, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 64, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 24, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 64, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 24, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 64, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 24, 8, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 64, 1}, .tiling_dimension = {8, 8, 4, 1}, .offset = {0, 24, 12, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 118
+// LayerName: Add_196
+std::vector<uint32_t> ifm_dim_118 = {8, 32, 64, 1};
+std::vector<uint32_t> ifm_bound_118 = {8, 1, 60, 1};
+std::vector<uint32_t> ifmsv_dim_118 = {8, 1, 16, 3};
+uint32_t ifmsv_size_118 = 1536;
+uint32_t kernel_iter_118 = 1;
+bool has_l1_write_access_pattern_118 = false;
+std::vector<access_pattern> l1_write_pattern_118 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_118 = {
+{
+  tiling({.buffer_dimension = {8, 32, 64, 1}, .tiling_dimension = {8, 1, 16, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 60, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 64, 1}, .tiling_dimension = {8, 1, 16, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 60, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 64, 1}, .tiling_dimension = {8, 1, 16, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 60, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 64, 1}, .tiling_dimension = {8, 1, 16, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 60, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_118 = 0;
+bool has_l1_wts_write_access_pattern_118 = false;
+std::vector<access_pattern> l1_wts_write_pattern_118 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_118 = {};
+
+
+std::vector<uint32_t> ofm_dim_118 = {8, 1, 64, 12};
+std::vector<uint32_t> ofm_bound_118 = {8, 1, 60, 1};
+std::vector<uint32_t> ofmsv_dim_118 = {8, 1, 16, 3};
+uint32_t ofmsv_size_118 = 384;
+uint32_t ofm_repetition_118 = 1;
+bool has_l1_read_access_pattern_118 = false;
+
+std::vector<access_pattern> l1_read_pattern_118 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_118 = {
+{
+  tiling({.buffer_dimension = {8, 1, 64, 12}, .tiling_dimension = {8, 1, 16, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 12}, .tiling_dimension = {8, 1, 16, 3}, .offset = {0, 0, 16, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 12}, .tiling_dimension = {8, 1, 16, 3}, .offset = {0, 0, 32, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 12}, .tiling_dimension = {8, 1, 16, 3}, .offset = {0, 0, 48, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 64, 12}, .tiling_dimension = {8, 1, 16, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 12}, .tiling_dimension = {8, 1, 16, 3}, .offset = {0, 0, 16, 3}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 12}, .tiling_dimension = {8, 1, 16, 3}, .offset = {0, 0, 32, 3}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 12}, .tiling_dimension = {8, 1, 16, 3}, .offset = {0, 0, 48, 3}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 64, 12}, .tiling_dimension = {8, 1, 16, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 12}, .tiling_dimension = {8, 1, 16, 3}, .offset = {0, 0, 16, 6}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 12}, .tiling_dimension = {8, 1, 16, 3}, .offset = {0, 0, 32, 6}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 12}, .tiling_dimension = {8, 1, 16, 3}, .offset = {0, 0, 48, 6}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 64, 12}, .tiling_dimension = {8, 1, 16, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 12}, .tiling_dimension = {8, 1, 16, 3}, .offset = {0, 0, 16, 9}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 12}, .tiling_dimension = {8, 1, 16, 3}, .offset = {0, 0, 32, 9}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 12}, .tiling_dimension = {8, 1, 16, 3}, .offset = {0, 0, 48, 9}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 119
+// LayerName: Clip_199
+std::vector<uint32_t> ifm_dim_119 = {8, 1, 64, 12};
+std::vector<uint32_t> ifm_bound_119 = {8, 1, 60, 1};
+std::vector<uint32_t> ifmsv_dim_119 = {8, 1, 16, 2};
+uint32_t ifmsv_size_119 = 1024;
+uint32_t kernel_iter_119 = 1;
+bool has_l1_write_access_pattern_119 = false;
+std::vector<access_pattern> l1_write_pattern_119 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_119 = {
+{
+  tiling({.buffer_dimension = {8, 1, 64, 12}, .tiling_dimension = {8, 1, 16, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 60, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 64, 12}, .tiling_dimension = {8, 1, 16, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 60, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 64, 12}, .tiling_dimension = {8, 1, 16, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 60, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 64, 12}, .tiling_dimension = {8, 1, 16, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 60, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_119 = 0;
+bool has_l1_wts_write_access_pattern_119 = false;
+std::vector<access_pattern> l1_wts_write_pattern_119 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_119 = {};
+
+
+std::vector<uint32_t> ofm_dim_119 = {8, 1, 64, 8};
+std::vector<uint32_t> ofm_bound_119 = {8, 1, 60, 1};
+std::vector<uint32_t> ofmsv_dim_119 = {8, 1, 16, 2};
+uint32_t ofmsv_size_119 = 256;
+uint32_t ofm_repetition_119 = 1;
+bool has_l1_read_access_pattern_119 = false;
+
+std::vector<access_pattern> l1_read_pattern_119 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_119 = {
+{
+  tiling({.buffer_dimension = {8, 1, 64, 8}, .tiling_dimension = {8, 1, 16, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 8}, .tiling_dimension = {8, 1, 16, 2}, .offset = {0, 0, 16, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 8}, .tiling_dimension = {8, 1, 16, 2}, .offset = {0, 0, 32, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 8}, .tiling_dimension = {8, 1, 16, 2}, .offset = {0, 0, 48, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 64, 8}, .tiling_dimension = {8, 1, 16, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 8}, .tiling_dimension = {8, 1, 16, 2}, .offset = {0, 0, 16, 2}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 8}, .tiling_dimension = {8, 1, 16, 2}, .offset = {0, 0, 32, 2}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 8}, .tiling_dimension = {8, 1, 16, 2}, .offset = {0, 0, 48, 2}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 64, 8}, .tiling_dimension = {8, 1, 16, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 8}, .tiling_dimension = {8, 1, 16, 2}, .offset = {0, 0, 16, 4}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 8}, .tiling_dimension = {8, 1, 16, 2}, .offset = {0, 0, 32, 4}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 8}, .tiling_dimension = {8, 1, 16, 2}, .offset = {0, 0, 48, 4}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 64, 8}, .tiling_dimension = {8, 1, 16, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 8}, .tiling_dimension = {8, 1, 16, 2}, .offset = {0, 0, 16, 6}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 8}, .tiling_dimension = {8, 1, 16, 2}, .offset = {0, 0, 32, 6}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 8}, .tiling_dimension = {8, 1, 16, 2}, .offset = {0, 0, 48, 6}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 120
+// LayerName: Div_201
+std::vector<uint32_t> ifm_dim_120 = {8, 1, 64, 8};
+std::vector<uint32_t> ifm_bound_120 = {8, 1, 60, 1};
+std::vector<uint32_t> ifmsv_dim_120 = {8, 1, 16, 4};
+uint32_t ifmsv_size_120 = 2048;
+uint32_t kernel_iter_120 = 1;
+bool has_l1_write_access_pattern_120 = false;
+std::vector<access_pattern> l1_write_pattern_120 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_120 = {
+{
+  tiling({.buffer_dimension = {8, 1, 64, 8}, .tiling_dimension = {8, 1, 16, 4}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 60, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 64, 8}, .tiling_dimension = {8, 1, 16, 4}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 60, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 64, 8}, .tiling_dimension = {8, 1, 16, 4}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 60, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 64, 8}, .tiling_dimension = {8, 1, 16, 4}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 16, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 60, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_120 = 0;
+bool has_l1_wts_write_access_pattern_120 = false;
+std::vector<access_pattern> l1_wts_write_pattern_120 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_120 = {};
+
+
+std::vector<uint32_t> ofm_dim_120 = {8, 1, 64, 16};
+std::vector<uint32_t> ofm_bound_120 = {8, 1, 60, 1};
+std::vector<uint32_t> ofmsv_dim_120 = {8, 1, 16, 4};
+uint32_t ofmsv_size_120 = 512;
+uint32_t ofm_repetition_120 = 1;
+bool has_l1_read_access_pattern_120 = false;
+
+std::vector<access_pattern> l1_read_pattern_120 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_120 = {
+{
+  tiling({.buffer_dimension = {8, 1, 64, 16}, .tiling_dimension = {8, 1, 16, 4}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 16}, .tiling_dimension = {8, 1, 16, 4}, .offset = {0, 0, 16, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 16}, .tiling_dimension = {8, 1, 16, 4}, .offset = {0, 0, 32, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 16}, .tiling_dimension = {8, 1, 16, 4}, .offset = {0, 0, 48, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 64, 16}, .tiling_dimension = {8, 1, 16, 4}, .offset = {0, 0, 0, 4}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 16}, .tiling_dimension = {8, 1, 16, 4}, .offset = {0, 0, 16, 4}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 16}, .tiling_dimension = {8, 1, 16, 4}, .offset = {0, 0, 32, 4}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 16}, .tiling_dimension = {8, 1, 16, 4}, .offset = {0, 0, 48, 4}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 64, 16}, .tiling_dimension = {8, 1, 16, 4}, .offset = {0, 0, 0, 8}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 16}, .tiling_dimension = {8, 1, 16, 4}, .offset = {0, 0, 16, 8}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 16}, .tiling_dimension = {8, 1, 16, 4}, .offset = {0, 0, 32, 8}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 16}, .tiling_dimension = {8, 1, 16, 4}, .offset = {0, 0, 48, 8}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 64, 16}, .tiling_dimension = {8, 1, 16, 4}, .offset = {0, 0, 0, 12}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 16}, .tiling_dimension = {8, 1, 16, 4}, .offset = {0, 0, 16, 12}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 16}, .tiling_dimension = {8, 1, 16, 4}, .offset = {0, 0, 32, 12}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 64, 16}, .tiling_dimension = {8, 1, 16, 4}, .offset = {0, 0, 48, 12}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 122
+// LayerName: Mul_202
+std::vector<uint32_t> ifm_dim_122 = {8, 20, 60, 12};
+std::vector<uint32_t> ifm_bound_122 = {8, 20, 60, 12};
+std::vector<uint32_t> ifmsv_dim_122 = {8, 20, 2, 3};
+uint32_t ifmsv_size_122 = 3840;
+uint32_t kernel_iter_122 = 8;
+bool has_l1_write_access_pattern_122 = false;
+std::vector<access_pattern> l1_write_pattern_122 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_122 = {
+{
+  tiling({.buffer_dimension = {8, 20, 60, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 32} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 60, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 32} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 60, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 32} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 60, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 32} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_122 = {8, 20, 64, 12};
+std::vector<uint32_t> ifm2_bound_122 = {8, 20, 60, 12};
+std::vector<uint32_t> ifm2sv_dim_122 = {8, 20, 2, 3};
+uint32_t ifm2sv_size_122 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_122 = {
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 32} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 32} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 32} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 32} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_122 = 0;
+bool has_l1_wts_write_access_pattern_122 = false;
+std::vector<access_pattern> l1_wts_write_pattern_122 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_122 = {};
+
+
+std::vector<uint32_t> ofm_dim_122 = {8, 20, 64, 12};
+std::vector<uint32_t> ofm_bound_122 = {8, 20, 60, 12};
+std::vector<uint32_t> ofmsv_dim_122 = {8, 20, 2, 3};
+uint32_t ofmsv_size_122 = 960;
+uint32_t ofm_repetition_122 = 1;
+bool has_l1_read_access_pattern_122 = false;
+
+std::vector<access_pattern> l1_read_pattern_122 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_122 = {
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 123
+// LayerName: Conv_203
+std::vector<uint32_t> ifm_dim_123 = {8, 20, 64, 12};
+std::vector<uint32_t> ifm_bound_123 = {8, 20, 60, 12};
+std::vector<uint32_t> ifmsv_dim_123 = {8, 32, 12, 1};
+uint32_t ifmsv_size_123 = 3072;
+uint32_t kernel_iter_123 = 15;
+bool has_l1_write_access_pattern_123 = true;
+std::vector<access_pattern> l1_write_pattern_123 = {tiling({.buffer_dimension = {8, 32, 12, 1}, .tiling_dimension = {8, 20, 12, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_123 = {
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 12, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 5}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 12, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 5}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 12, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 5}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 64, 12}, .tiling_dimension = {8, 20, 12, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 5}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 60, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_123 = {64000};
+std::vector<uint32_t> wts_dim_123 = {64000};
+std::vector<uint32_t> wtssv_dim_123 = {3200};
+uint32_t wtssv_size_123 = 3200;
+uint32_t wts_repetition_123 = 1;
+bool has_l1_wts_write_access_pattern_123 = false;
+std::vector<access_pattern> l1_wts_write_pattern_123 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_123 = {
+{
+  tiling({.buffer_dimension = {16000, 4}, .tiling_dimension = {3200, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 3200, .wrap = 5} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {16000, 4}, .tiling_dimension = {3200, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 3200, .wrap = 5} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {16000, 4}, .tiling_dimension = {3200, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 3200, .wrap = 5} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {16000, 4}, .tiling_dimension = {3200, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 3200, .wrap = 5} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_123[] = {
+{
+  tiling({.buffer_dimension = {64000, 1}, .tiling_dimension = {32000, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {64000, 1}, .tiling_dimension = {32000, 1}, .offset = {32000, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_123[] = {
+{
+  tiling({.buffer_dimension = {64000}, .tiling_dimension = {32000}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {64000}, .tiling_dimension = {32000}, .offset = {32000}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_123 = {8, 32, 16, 12};
+std::vector<uint32_t> ofm_bound_123 = {8, 20, 14, 12};
+std::vector<uint32_t> ofmsv_dim_123 = {8, 32, 4, 1};
+uint32_t ofmsv_size_123 = 1024;
+uint32_t ofm_repetition_123 = 5;
+bool has_l1_read_access_pattern_123 = false;
+
+std::vector<access_pattern> l1_read_pattern_123 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_123 = {
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 8, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 12, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 4, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 8, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 12, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 4, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 8, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 12, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 8, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 12, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 124
+// LayerName: Conv_204
+std::vector<uint32_t> ifm_dim_124 = {8, 32, 16, 12};
+std::vector<uint32_t> ifm_bound_124 = {8, 20, 14, 12};
+std::vector<uint32_t> ifmsv_dim_124 = {8, 32, 8, 1};
+uint32_t ifmsv_size_124 = 2048;
+uint32_t kernel_iter_124 = 18;
+bool has_l1_write_access_pattern_124 = true;
+std::vector<access_pattern> l1_write_pattern_124 = {tiling({.buffer_dimension = {8, 32, 8, 1}, .tiling_dimension = {8, 20, 8, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_124 = {
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 20, 8, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {8, 20, 14, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 20, 8, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {8, 20, 14, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 20, 8, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {8, 20, 14, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 20, 8, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {8, 20, 14, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_124 = {91392};
+std::vector<uint32_t> wts_dim_124 = {91392};
+std::vector<uint32_t> wtssv_dim_124 = {3808};
+uint32_t wtssv_size_124 = 3808;
+uint32_t wts_repetition_124 = 1;
+bool has_l1_wts_write_access_pattern_124 = false;
+std::vector<access_pattern> l1_wts_write_pattern_124 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_124 = {
+{
+  tiling({.buffer_dimension = {7616, 12}, .tiling_dimension = {3808, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 3808, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {7616, 12}, .tiling_dimension = {3808, 1}, .offset = {0, 4}, .tile_traversal = { {.dimension = 0, .stride = 3808, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {7616, 12}, .tiling_dimension = {3808, 1}, .offset = {0, 8}, .tile_traversal = { {.dimension = 0, .stride = 3808, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {7616, 12}, .tiling_dimension = {3808, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 3808, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {7616, 12}, .tiling_dimension = {3808, 1}, .offset = {0, 5}, .tile_traversal = { {.dimension = 0, .stride = 3808, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {7616, 12}, .tiling_dimension = {3808, 1}, .offset = {0, 9}, .tile_traversal = { {.dimension = 0, .stride = 3808, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {7616, 12}, .tiling_dimension = {3808, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 3808, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {7616, 12}, .tiling_dimension = {3808, 1}, .offset = {0, 6}, .tile_traversal = { {.dimension = 0, .stride = 3808, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {7616, 12}, .tiling_dimension = {3808, 1}, .offset = {0, 10}, .tile_traversal = { {.dimension = 0, .stride = 3808, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {7616, 12}, .tiling_dimension = {3808, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 3808, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {7616, 12}, .tiling_dimension = {3808, 1}, .offset = {0, 7}, .tile_traversal = { {.dimension = 0, .stride = 3808, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {7616, 12}, .tiling_dimension = {3808, 1}, .offset = {0, 11}, .tile_traversal = { {.dimension = 0, .stride = 3808, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_124[] = {
+{
+  tiling({.buffer_dimension = {91392, 1}, .tiling_dimension = {45696, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {91392, 1}, .tiling_dimension = {45696, 1}, .offset = {45696, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_124[] = {
+{
+  tiling({.buffer_dimension = {91392}, .tiling_dimension = {45696}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {91392}, .tiling_dimension = {45696}, .offset = {45696}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_124 = {8, 32, 84, 12};
+std::vector<uint32_t> ofm_bound_124 = {8, 20, 84, 12};
+std::vector<uint32_t> ofmsv_dim_124 = {8, 32, 7, 1};
+uint32_t ofmsv_size_124 = 1792;
+uint32_t ofm_repetition_124 = 2;
+bool has_l1_read_access_pattern_124 = false;
+
+std::vector<access_pattern> l1_read_pattern_124 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_124 = {
+{
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 7, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 14, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 21, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 7, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 14, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 21, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 7, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 14, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 21, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 7, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 14, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 21, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 125
+// LayerName: Add_206
+std::vector<uint32_t> ifm_dim_125 = {8, 32, 84, 12};
+std::vector<uint32_t> ifm_bound_125 = {8, 20, 84, 12};
+std::vector<uint32_t> ifmsv_dim_125 = {8, 20, 2, 3};
+uint32_t ifmsv_size_125 = 3840;
+uint32_t kernel_iter_125 = 11;
+bool has_l1_write_access_pattern_125 = false;
+std::vector<access_pattern> l1_write_pattern_125 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_125 = {
+{
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_125 = 0;
+bool has_l1_wts_write_access_pattern_125 = false;
+std::vector<access_pattern> l1_wts_write_pattern_125 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_125 = {};
+
+
+std::vector<uint32_t> ofm_dim_125 = {8, 20, 88, 12};
+std::vector<uint32_t> ofm_bound_125 = {8, 20, 84, 12};
+std::vector<uint32_t> ofmsv_dim_125 = {8, 20, 2, 3};
+uint32_t ofmsv_size_125 = 960;
+uint32_t ofm_repetition_125 = 1;
+bool has_l1_read_access_pattern_125 = false;
+
+std::vector<access_pattern> l1_read_pattern_125 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_125 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 126
+// LayerName: Clip_209
+std::vector<uint32_t> ifm_dim_126 = {8, 20, 88, 12};
+std::vector<uint32_t> ifm_bound_126 = {8, 20, 84, 12};
+std::vector<uint32_t> ifmsv_dim_126 = {8, 20, 2, 3};
+uint32_t ifmsv_size_126 = 3840;
+uint32_t kernel_iter_126 = 11;
+bool has_l1_write_access_pattern_126 = false;
+std::vector<access_pattern> l1_write_pattern_126 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_126 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_126 = 0;
+bool has_l1_wts_write_access_pattern_126 = false;
+std::vector<access_pattern> l1_wts_write_pattern_126 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_126 = {};
+
+
+std::vector<uint32_t> ofm_dim_126 = {8, 20, 88, 12};
+std::vector<uint32_t> ofm_bound_126 = {8, 20, 84, 12};
+std::vector<uint32_t> ofmsv_dim_126 = {8, 20, 2, 3};
+uint32_t ofmsv_size_126 = 960;
+uint32_t ofm_repetition_126 = 1;
+bool has_l1_read_access_pattern_126 = false;
+
+std::vector<access_pattern> l1_read_pattern_126 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_126 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 127
+// LayerName: Div_211
+std::vector<uint32_t> ifm_dim_127 = {8, 20, 88, 12};
+std::vector<uint32_t> ifm_bound_127 = {8, 20, 84, 12};
+std::vector<uint32_t> ifmsv_dim_127 = {8, 20, 2, 3};
+uint32_t ifmsv_size_127 = 3840;
+uint32_t kernel_iter_127 = 11;
+bool has_l1_write_access_pattern_127 = false;
+std::vector<access_pattern> l1_write_pattern_127 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_127 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_127 = 0;
+bool has_l1_wts_write_access_pattern_127 = false;
+std::vector<access_pattern> l1_wts_write_pattern_127 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_127 = {};
+
+
+std::vector<uint32_t> ofm_dim_127 = {8, 20, 88, 12};
+std::vector<uint32_t> ofm_bound_127 = {8, 20, 84, 12};
+std::vector<uint32_t> ofmsv_dim_127 = {8, 20, 2, 3};
+uint32_t ofmsv_size_127 = 960;
+uint32_t ofm_repetition_127 = 1;
+bool has_l1_read_access_pattern_127 = false;
+
+std::vector<access_pattern> l1_read_pattern_127 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_127 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 128
+// LayerName: Mul_212
+std::vector<uint32_t> ifm_dim_128 = {8, 32, 84, 12};
+std::vector<uint32_t> ifm_bound_128 = {8, 20, 84, 12};
+std::vector<uint32_t> ifmsv_dim_128 = {8, 20, 2, 3};
+uint32_t ifmsv_size_128 = 3840;
+uint32_t kernel_iter_128 = 11;
+bool has_l1_write_access_pattern_128 = false;
+std::vector<access_pattern> l1_write_pattern_128 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_128 = {
+{
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_128 = {8, 20, 88, 12};
+std::vector<uint32_t> ifm2_bound_128 = {8, 20, 84, 12};
+std::vector<uint32_t> ifm2sv_dim_128 = {8, 20, 2, 3};
+uint32_t ifm2sv_size_128 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_128 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_128 = 0;
+bool has_l1_wts_write_access_pattern_128 = false;
+std::vector<access_pattern> l1_wts_write_pattern_128 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_128 = {};
+
+
+std::vector<uint32_t> ofm_dim_128 = {8, 20, 88, 12};
+std::vector<uint32_t> ofm_bound_128 = {8, 20, 84, 12};
+std::vector<uint32_t> ofmsv_dim_128 = {8, 20, 2, 3};
+uint32_t ofmsv_size_128 = 960;
+uint32_t ofm_repetition_128 = 1;
+bool has_l1_read_access_pattern_128 = false;
+
+std::vector<access_pattern> l1_read_pattern_128 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_128 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 129
+// LayerName: Conv_213
+std::vector<uint32_t> ifm_dim_129 = {8, 20, 88, 12};
+std::vector<uint32_t> ifm_bound_129 = {8, 20, 84, 12};
+std::vector<uint32_t> ifmsv_dim_129 = {8, 28, 1, 6};
+uint32_t ifmsv_size_129 = 5376;
+uint32_t kernel_iter_129 = 21;
+bool has_l1_write_access_pattern_129 = false;
+std::vector<access_pattern> l1_write_pattern_129 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_129 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, -1}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 84} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 84} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 7}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 84} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 28, 1, 6}, .offset = {0, -1, 0, 11}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 84} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_129 = {10752};
+std::vector<uint32_t> wts_dim_129 = {10752};
+std::vector<uint32_t> wtssv_dim_129 = {128};
+uint32_t wts_repetition_129 = 1;
+uint32_t wtssv_size_129 = 128;
+bool has_l1_wts_write_access_pattern_129 = false;
+std::vector<access_pattern> l1_wts_write_pattern_129 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_129 = {
+{
+  tiling({.buffer_dimension = {10752}, .tiling_dimension = {128}, .offset = {0}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 21} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {10752}, .tiling_dimension = {128}, .offset = {128}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 21} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {10752}, .tiling_dimension = {128}, .offset = {256}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 21} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {10752}, .tiling_dimension = {128}, .offset = {384}, .tile_traversal = { {.dimension = 0, .stride = 512, .wrap = 21} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_129[] = {
+{
+  tiling({.buffer_dimension = {10752, 1}, .tiling_dimension = {5376, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {10752, 1}, .tiling_dimension = {5376, 1}, .offset = {5376, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_129[] = {
+{
+  tiling({.buffer_dimension = {10752}, .tiling_dimension = {5376}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {10752}, .tiling_dimension = {5376}, .offset = {5376}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_129 = {8, 24, 84, 16};
+std::vector<uint32_t> ofm_bound_129 = {8, 20, 84, 12};
+std::vector<uint32_t> ofmsv_dim_129 = {8, 24, 1, 4};
+uint32_t ofmsv_size_129 = 768;
+uint32_t ofm_repetition_129 = 1;
+bool has_l1_read_access_pattern_129 = false;
+
+std::vector<access_pattern> l1_read_pattern_129 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_129 = {
+{
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 1, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 2, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 3, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 1, 8}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 2, 8}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 3, 8}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 1, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 24, 1, 4}, .offset = {0, 0, 3, 12}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 130
+// LayerName: Add_215
+std::vector<uint32_t> ifm_dim_130 = {8, 24, 84, 16};
+std::vector<uint32_t> ifm_bound_130 = {8, 20, 84, 12};
+std::vector<uint32_t> ifmsv_dim_130 = {8, 20, 2, 3};
+uint32_t ifmsv_size_130 = 3840;
+uint32_t kernel_iter_130 = 11;
+bool has_l1_write_access_pattern_130 = false;
+std::vector<access_pattern> l1_write_pattern_130 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_130 = {
+{
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_130 = 0;
+bool has_l1_wts_write_access_pattern_130 = false;
+std::vector<access_pattern> l1_wts_write_pattern_130 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_130 = {};
+
+
+std::vector<uint32_t> ofm_dim_130 = {8, 20, 88, 12};
+std::vector<uint32_t> ofm_bound_130 = {8, 20, 84, 12};
+std::vector<uint32_t> ofmsv_dim_130 = {8, 20, 2, 3};
+uint32_t ofmsv_size_130 = 960;
+uint32_t ofm_repetition_130 = 1;
+bool has_l1_read_access_pattern_130 = false;
+
+std::vector<access_pattern> l1_read_pattern_130 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_130 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 131
+// LayerName: Clip_218
+std::vector<uint32_t> ifm_dim_131 = {8, 20, 88, 12};
+std::vector<uint32_t> ifm_bound_131 = {8, 20, 84, 12};
+std::vector<uint32_t> ifmsv_dim_131 = {8, 20, 2, 3};
+uint32_t ifmsv_size_131 = 3840;
+uint32_t kernel_iter_131 = 11;
+bool has_l1_write_access_pattern_131 = false;
+std::vector<access_pattern> l1_write_pattern_131 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_131 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_131 = 0;
+bool has_l1_wts_write_access_pattern_131 = false;
+std::vector<access_pattern> l1_wts_write_pattern_131 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_131 = {};
+
+
+std::vector<uint32_t> ofm_dim_131 = {8, 20, 88, 12};
+std::vector<uint32_t> ofm_bound_131 = {8, 20, 84, 12};
+std::vector<uint32_t> ofmsv_dim_131 = {8, 20, 2, 3};
+uint32_t ofmsv_size_131 = 960;
+uint32_t ofm_repetition_131 = 1;
+bool has_l1_read_access_pattern_131 = false;
+
+std::vector<access_pattern> l1_read_pattern_131 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_131 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 132
+// LayerName: Div_220
+std::vector<uint32_t> ifm_dim_132 = {8, 20, 88, 12};
+std::vector<uint32_t> ifm_bound_132 = {8, 20, 84, 12};
+std::vector<uint32_t> ifmsv_dim_132 = {8, 20, 2, 3};
+uint32_t ifmsv_size_132 = 3840;
+uint32_t kernel_iter_132 = 11;
+bool has_l1_write_access_pattern_132 = false;
+std::vector<access_pattern> l1_write_pattern_132 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_132 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_132 = 0;
+bool has_l1_wts_write_access_pattern_132 = false;
+std::vector<access_pattern> l1_wts_write_pattern_132 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_132 = {};
+
+
+std::vector<uint32_t> ofm_dim_132 = {8, 20, 88, 12};
+std::vector<uint32_t> ofm_bound_132 = {8, 20, 84, 12};
+std::vector<uint32_t> ofmsv_dim_132 = {8, 20, 2, 3};
+uint32_t ofmsv_size_132 = 960;
+uint32_t ofm_repetition_132 = 1;
+bool has_l1_read_access_pattern_132 = false;
+
+std::vector<access_pattern> l1_read_pattern_132 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_132 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 133
+// LayerName: Mul_221
+std::vector<uint32_t> ifm_dim_133 = {8, 24, 84, 16};
+std::vector<uint32_t> ifm_bound_133 = {8, 20, 84, 12};
+std::vector<uint32_t> ifmsv_dim_133 = {8, 20, 2, 3};
+uint32_t ifmsv_size_133 = 3840;
+uint32_t kernel_iter_133 = 11;
+bool has_l1_write_access_pattern_133 = false;
+std::vector<access_pattern> l1_write_pattern_133 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_133 = {
+{
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_133 = {8, 20, 88, 12};
+std::vector<uint32_t> ifm2_bound_133 = {8, 20, 84, 12};
+std::vector<uint32_t> ifm2sv_dim_133 = {8, 20, 2, 3};
+uint32_t ifm2sv_size_133 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_133 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_133 = 0;
+bool has_l1_wts_write_access_pattern_133 = false;
+std::vector<access_pattern> l1_wts_write_pattern_133 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_133 = {};
+
+
+std::vector<uint32_t> ofm_dim_133 = {8, 20, 88, 12};
+std::vector<uint32_t> ofm_bound_133 = {8, 20, 84, 12};
+std::vector<uint32_t> ofmsv_dim_133 = {8, 20, 2, 3};
+uint32_t ofmsv_size_133 = 960;
+uint32_t ofm_repetition_133 = 1;
+bool has_l1_read_access_pattern_133 = false;
+
+std::vector<access_pattern> l1_read_pattern_133 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_133 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 135
+// LayerName: Generated-#32
+std::vector<uint32_t> ifm_dim_135 = {8, 240, 84, 1};
+std::vector<uint32_t> ifm_bound_135 = {8, 240, 84, 1};
+std::vector<uint32_t> ifmsv_dim_135 = {8, 32, 7, 1};
+uint32_t ifmsv_size_135 = 7168;
+uint32_t kernel_iter_135 = 24;
+bool has_l1_write_access_pattern_135 = false;
+std::vector<access_pattern> l1_write_pattern_135 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_135 = {
+{
+  tiling({.buffer_dimension = {8, 240, 84, 1}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 7, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 8}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 240, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 240, 84, 1}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 7, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 8}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 240, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 240, 84, 1}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 7, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 8}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 240, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 240, 84, 1}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 7, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 8}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 240, 84, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_135 = 0;
+bool has_l1_wts_write_access_pattern_135 = false;
+std::vector<access_pattern> l1_wts_write_pattern_135 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_135 = {};
+
+
+std::vector<uint32_t> ofm_dim_135 = {8, 1, 84, 4};
+std::vector<uint32_t> ofm_bound_135 = {8, 1, 84, 1};
+std::vector<uint32_t> ofmsv_dim_135 = {8, 1, 7, 1};
+uint32_t ofmsv_size_135 = 56;
+uint32_t ofm_repetition_135 = 8;
+bool has_l1_read_access_pattern_135 = false;
+std::vector<access_pattern> l1_read_pattern_135 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ofm_pattern_135 = {
+{
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 7, 0}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 14, 0}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 21, 0}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 7, 1}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 14, 1}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 21, 1}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 7, 2}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 14, 2}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 21, 2}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 7, 3}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 14, 3}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 21, 3}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 136
+// LayerName: Conv_223
+std::vector<uint32_t> ifm_dim_136 = {8, 1, 84, 4};
+std::vector<uint32_t> ifm_bound_136 = {8, 1, 84, 1};
+std::vector<uint32_t> ifmsv_dim_136 = {8, 8, 12, 1};
+uint32_t ifmsv_size_136 = 768;
+uint32_t kernel_iter_136 = 7;
+bool has_l1_write_access_pattern_136 = false;
+std::vector<access_pattern> l1_write_pattern_136 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_136 = {
+{
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 8, 12, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 8, 12, 1}, .offset = {0, 8, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 8, 12, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 8, 12, 1}, .offset = {0, 24, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_136 = {134400};
+std::vector<uint32_t> wts_dim_136 = {134400};
+std::vector<uint32_t> wtssv_dim_136 = {4800};
+uint32_t wtssv_size_136 = 4800;
+uint32_t wts_repetition_136 = 1;
+bool has_l1_wts_write_access_pattern_136 = false;
+std::vector<access_pattern> l1_wts_write_pattern_136 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_136 = {
+{
+  tiling({.buffer_dimension = {33600, 4}, .tiling_dimension = {4800, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 4800, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {33600, 4}, .tiling_dimension = {4800, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 4800, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {33600, 4}, .tiling_dimension = {4800, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 4800, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {33600, 4}, .tiling_dimension = {4800, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 4800, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_136[] = {
+{
+  tiling({.buffer_dimension = {134400, 1}, .tiling_dimension = {67200, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {134400, 1}, .tiling_dimension = {67200, 1}, .offset = {67200, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_136[] = {
+{
+  tiling({.buffer_dimension = {134400}, .tiling_dimension = {67200}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {134400}, .tiling_dimension = {67200}, .offset = {67200}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_136 = {8, 32, 24, 1};
+std::vector<uint32_t> ofm_bound_136 = {8, 1, 21, 1};
+std::vector<uint32_t> ofmsv_dim_136 = {8, 8, 6, 1};
+uint32_t ofmsv_size_136 = 384;
+uint32_t ofm_repetition_136 = 7;
+bool has_l1_read_access_pattern_136 = false;
+
+std::vector<access_pattern> l1_read_pattern_136 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_136 = {
+{
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 0, 6, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 0, 12, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 0, 18, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 8, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 8, 6, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 8, 12, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 8, 18, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 16, 6, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 16, 12, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 16, 18, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 24, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 24, 6, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 24, 12, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 24, 18, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 137
+// LayerName: Conv_225
+std::vector<uint32_t> ifm_dim_137 = {8, 32, 24, 1};
+std::vector<uint32_t> ifm_bound_137 = {8, 1, 21, 1};
+std::vector<uint32_t> ifmsv_dim_137 = {8, 16, 21, 1};
+uint32_t ifmsv_size_137 = 2688;
+uint32_t kernel_iter_137 = 11;
+bool has_l1_write_access_pattern_137 = false;
+std::vector<access_pattern> l1_write_pattern_137 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_137 = {
+{
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 16, 21, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 11, .boundary_dimension = {8, 1, 21, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 16, 21, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 11, .boundary_dimension = {8, 1, 21, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 16, 21, 1}, .offset = {0, 32, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 11, .boundary_dimension = {8, 1, 21, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 16, 21, 1}, .offset = {0, 48, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 11, .boundary_dimension = {8, 1, 21, 1}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_137 = {121088};
+std::vector<uint32_t> wts_dim_137 = {121088};
+std::vector<uint32_t> wtssv_dim_137 = {2752};
+uint32_t wtssv_size_137 = 2752;
+uint32_t wts_repetition_137 = 1;
+bool has_l1_wts_write_access_pattern_137 = false;
+std::vector<access_pattern> l1_wts_write_pattern_137 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_137 = {
+{
+  tiling({.buffer_dimension = {2752, 44}, .tiling_dimension = {2752, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 1, .stride = 4, .wrap = 11} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2752, 44}, .tiling_dimension = {2752, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 1, .stride = 4, .wrap = 11} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2752, 44}, .tiling_dimension = {2752, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 1, .stride = 4, .wrap = 11} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2752, 44}, .tiling_dimension = {2752, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 1, .stride = 4, .wrap = 11} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_137[] = {
+{
+  tiling({.buffer_dimension = {121088, 1}, .tiling_dimension = {60544, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {121088, 1}, .tiling_dimension = {60544, 1}, .offset = {60544, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_137[] = {
+{
+  tiling({.buffer_dimension = {121088}, .tiling_dimension = {60544}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {121088}, .tiling_dimension = {60544}, .offset = {60544}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_137 = {8, 64, 88, 1};
+std::vector<uint32_t> ofm_bound_137 = {8, 1, 84, 1};
+std::vector<uint32_t> ofmsv_dim_137 = {8, 16, 2, 1};
+uint32_t ofmsv_size_137 = 256;
+uint32_t ofm_repetition_137 = 1;
+bool has_l1_read_access_pattern_137 = false;
+
+std::vector<access_pattern> l1_read_pattern_137 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_137 = {
+{
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 138
+// LayerName: Add_227
+std::vector<uint32_t> ifm_dim_138 = {8, 64, 88, 1};
+std::vector<uint32_t> ifm_bound_138 = {8, 1, 84, 1};
+std::vector<uint32_t> ifmsv_dim_138 = {8, 1, 24, 2};
+uint32_t ifmsv_size_138 = 1536;
+uint32_t kernel_iter_138 = 1;
+bool has_l1_write_access_pattern_138 = false;
+std::vector<access_pattern> l1_write_pattern_138 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_138 = {
+{
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_138 = 0;
+bool has_l1_wts_write_access_pattern_138 = false;
+std::vector<access_pattern> l1_wts_write_pattern_138 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_138 = {};
+
+
+std::vector<uint32_t> ofm_dim_138 = {8, 1, 96, 8};
+std::vector<uint32_t> ofm_bound_138 = {8, 1, 84, 1};
+std::vector<uint32_t> ofmsv_dim_138 = {8, 1, 24, 2};
+uint32_t ofmsv_size_138 = 384;
+uint32_t ofm_repetition_138 = 1;
+bool has_l1_read_access_pattern_138 = false;
+
+std::vector<access_pattern> l1_read_pattern_138 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_138 = {
+{
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 24, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 48, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 72, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 24, 2}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 48, 2}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 72, 2}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 24, 4}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 48, 4}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 72, 4}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 24, 6}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 48, 6}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 72, 6}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 139
+// LayerName: Clip_230
+std::vector<uint32_t> ifm_dim_139 = {8, 1, 96, 8};
+std::vector<uint32_t> ifm_bound_139 = {8, 1, 84, 1};
+std::vector<uint32_t> ifmsv_dim_139 = {8, 1, 32, 1};
+uint32_t ifmsv_size_139 = 1024;
+uint32_t kernel_iter_139 = 1;
+bool has_l1_write_access_pattern_139 = false;
+std::vector<access_pattern> l1_write_pattern_139 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_139 = {
+{
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_139 = 0;
+bool has_l1_wts_write_access_pattern_139 = false;
+std::vector<access_pattern> l1_wts_write_pattern_139 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_139 = {};
+
+
+std::vector<uint32_t> ofm_dim_139 = {8, 1, 128, 4};
+std::vector<uint32_t> ofm_bound_139 = {8, 1, 84, 1};
+std::vector<uint32_t> ofmsv_dim_139 = {8, 1, 32, 1};
+uint32_t ofmsv_size_139 = 256;
+uint32_t ofm_repetition_139 = 1;
+bool has_l1_read_access_pattern_139 = false;
+
+std::vector<access_pattern> l1_read_pattern_139 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_139 = {
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 32, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 64, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 96, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 32, 1}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 64, 1}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 96, 1}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 32, 2}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 64, 2}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 96, 2}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 32, 3}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 64, 3}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 96, 3}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 140
+// LayerName: Div_232
+std::vector<uint32_t> ifm_dim_140 = {8, 1, 128, 4};
+std::vector<uint32_t> ifm_bound_140 = {8, 1, 84, 1};
+std::vector<uint32_t> ifmsv_dim_140 = {8, 1, 32, 2};
+uint32_t ifmsv_size_140 = 2048;
+uint32_t kernel_iter_140 = 1;
+bool has_l1_write_access_pattern_140 = false;
+std::vector<access_pattern> l1_write_pattern_140 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_140 = {
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_140 = 0;
+bool has_l1_wts_write_access_pattern_140 = false;
+std::vector<access_pattern> l1_wts_write_pattern_140 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_140 = {};
+
+
+std::vector<uint32_t> ofm_dim_140 = {8, 1, 128, 8};
+std::vector<uint32_t> ofm_bound_140 = {8, 1, 84, 1};
+std::vector<uint32_t> ofmsv_dim_140 = {8, 1, 32, 2};
+uint32_t ofmsv_size_140 = 512;
+uint32_t ofm_repetition_140 = 1;
+bool has_l1_read_access_pattern_140 = false;
+
+std::vector<access_pattern> l1_read_pattern_140 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_140 = {
+{
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 32, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 64, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 96, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 32, 2}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 64, 2}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 96, 2}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 32, 4}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 64, 4}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 96, 4}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 32, 6}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 64, 6}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 96, 6}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 142
+// LayerName: Mul_233
+std::vector<uint32_t> ifm_dim_142 = {8, 20, 84, 12};
+std::vector<uint32_t> ifm_bound_142 = {8, 20, 84, 12};
+std::vector<uint32_t> ifmsv_dim_142 = {8, 20, 2, 3};
+uint32_t ifmsv_size_142 = 3840;
+uint32_t kernel_iter_142 = 11;
+bool has_l1_write_access_pattern_142 = false;
+std::vector<access_pattern> l1_write_pattern_142 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_142 = {
+{
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_142 = {8, 20, 88, 12};
+std::vector<uint32_t> ifm2_bound_142 = {8, 20, 84, 12};
+std::vector<uint32_t> ifm2sv_dim_142 = {8, 20, 2, 3};
+uint32_t ifm2sv_size_142 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_142 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_142 = 0;
+bool has_l1_wts_write_access_pattern_142 = false;
+std::vector<access_pattern> l1_wts_write_pattern_142 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_142 = {};
+
+
+std::vector<uint32_t> ofm_dim_142 = {8, 20, 88, 12};
+std::vector<uint32_t> ofm_bound_142 = {8, 20, 84, 12};
+std::vector<uint32_t> ofmsv_dim_142 = {8, 20, 2, 3};
+uint32_t ofmsv_size_142 = 960;
+uint32_t ofm_repetition_142 = 1;
+bool has_l1_read_access_pattern_142 = false;
+
+std::vector<access_pattern> l1_read_pattern_142 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_142 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 143
+// LayerName: Conv_234
+std::vector<uint32_t> ifm_dim_143 = {8, 20, 88, 12};
+std::vector<uint32_t> ifm_bound_143 = {8, 20, 84, 12};
+std::vector<uint32_t> ifmsv_dim_143 = {8, 32, 12, 1};
+uint32_t ifmsv_size_143 = 3072;
+uint32_t kernel_iter_143 = 21;
+bool has_l1_write_access_pattern_143 = false;
+std::vector<access_pattern> l1_write_pattern_143 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_143 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 32, 12, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 7}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 32, 12, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 7}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 32, 12, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 7}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 32, 12, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 7}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_143 = {8, 32, 16, 12};
+std::vector<uint32_t> ifm2_bound_143 = {8, 20, 14, 12};
+std::vector<uint32_t> ifm2sv_dim_143 = {8, 32, 4, 1};
+uint32_t ifm2sv_size_143 = 4096;
+std::vector<std::vector<access_pattern>> ifm2_pattern_143 = {
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 14, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 14, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 14, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 14, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_143 = {89600};
+std::vector<uint32_t> wts_dim_143 = {89600};
+std::vector<uint32_t> wtssv_dim_143 = {3200};
+uint32_t wtssv_size_143 = 3200;
+uint32_t wts_repetition_143 = 1;
+bool has_l1_wts_write_access_pattern_143 = false;
+std::vector<access_pattern> l1_wts_write_pattern_143 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_143 = {
+{
+  tiling({.buffer_dimension = {22400, 4}, .tiling_dimension = {3200, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 3200, .wrap = 7} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {22400, 4}, .tiling_dimension = {3200, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 3200, .wrap = 7} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {22400, 4}, .tiling_dimension = {3200, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 3200, .wrap = 7} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {22400, 4}, .tiling_dimension = {3200, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 3200, .wrap = 7} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_143[] = {
+{
+  tiling({.buffer_dimension = {89600, 1}, .tiling_dimension = {44800, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {89600, 1}, .tiling_dimension = {44800, 1}, .offset = {44800, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_143[] = {
+{
+  tiling({.buffer_dimension = {89600}, .tiling_dimension = {44800}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {89600}, .tiling_dimension = {44800}, .offset = {44800}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_143 = {8, 32, 16, 12};
+std::vector<uint32_t> ofm_bound_143 = {8, 20, 14, 12};
+std::vector<uint32_t> ofmsv_dim_143 = {8, 32, 4, 1};
+uint32_t ofmsv_size_143 = 1024;
+uint32_t ofm_repetition_143 = 7;
+bool has_l1_read_access_pattern_143 = false;
+
+std::vector<access_pattern> l1_read_pattern_143 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_143 = {
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 8, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 12, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 4, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 8, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 12, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 4, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 8, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 12, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 8, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 12, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 144
+// LayerName: Conv_236
+std::vector<uint32_t> ifm_dim_144 = {8, 32, 16, 12};
+std::vector<uint32_t> ifm_bound_144 = {8, 20, 14, 12};
+std::vector<uint32_t> ifmsv_dim_144 = {8, 32, 8, 1};
+uint32_t ifmsv_size_144 = 2048;
+uint32_t kernel_iter_144 = 18;
+bool has_l1_write_access_pattern_144 = true;
+std::vector<access_pattern> l1_write_pattern_144 = {tiling({.buffer_dimension = {8, 32, 8, 1}, .tiling_dimension = {8, 20, 8, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_144 = {
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 20, 8, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {8, 20, 14, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 20, 8, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {8, 20, 14, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 20, 8, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {8, 20, 14, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 20, 8, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {8, 20, 14, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_144 = {91392};
+std::vector<uint32_t> wts_dim_144 = {91392};
+std::vector<uint32_t> wtssv_dim_144 = {3808};
+uint32_t wtssv_size_144 = 3808;
+uint32_t wts_repetition_144 = 1;
+bool has_l1_wts_write_access_pattern_144 = false;
+std::vector<access_pattern> l1_wts_write_pattern_144 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_144 = {
+{
+  tiling({.buffer_dimension = {7616, 12}, .tiling_dimension = {3808, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 3808, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {7616, 12}, .tiling_dimension = {3808, 1}, .offset = {0, 4}, .tile_traversal = { {.dimension = 0, .stride = 3808, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {7616, 12}, .tiling_dimension = {3808, 1}, .offset = {0, 8}, .tile_traversal = { {.dimension = 0, .stride = 3808, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {7616, 12}, .tiling_dimension = {3808, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 3808, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {7616, 12}, .tiling_dimension = {3808, 1}, .offset = {0, 5}, .tile_traversal = { {.dimension = 0, .stride = 3808, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {7616, 12}, .tiling_dimension = {3808, 1}, .offset = {0, 9}, .tile_traversal = { {.dimension = 0, .stride = 3808, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {7616, 12}, .tiling_dimension = {3808, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 3808, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {7616, 12}, .tiling_dimension = {3808, 1}, .offset = {0, 6}, .tile_traversal = { {.dimension = 0, .stride = 3808, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {7616, 12}, .tiling_dimension = {3808, 1}, .offset = {0, 10}, .tile_traversal = { {.dimension = 0, .stride = 3808, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {7616, 12}, .tiling_dimension = {3808, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 3808, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {7616, 12}, .tiling_dimension = {3808, 1}, .offset = {0, 7}, .tile_traversal = { {.dimension = 0, .stride = 3808, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {7616, 12}, .tiling_dimension = {3808, 1}, .offset = {0, 11}, .tile_traversal = { {.dimension = 0, .stride = 3808, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_144[] = {
+{
+  tiling({.buffer_dimension = {91392, 1}, .tiling_dimension = {45696, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {91392, 1}, .tiling_dimension = {45696, 1}, .offset = {45696, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_144[] = {
+{
+  tiling({.buffer_dimension = {91392}, .tiling_dimension = {45696}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {91392}, .tiling_dimension = {45696}, .offset = {45696}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_144 = {8, 32, 84, 12};
+std::vector<uint32_t> ofm_bound_144 = {8, 20, 84, 12};
+std::vector<uint32_t> ofmsv_dim_144 = {8, 32, 7, 1};
+uint32_t ofmsv_size_144 = 1792;
+uint32_t ofm_repetition_144 = 2;
+bool has_l1_read_access_pattern_144 = false;
+
+std::vector<access_pattern> l1_read_pattern_144 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_144 = {
+{
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 7, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 14, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 21, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 7, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 14, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 21, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 7, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 14, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 21, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 7, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 14, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 21, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 145
+// LayerName: Add_238
+std::vector<uint32_t> ifm_dim_145 = {8, 32, 84, 12};
+std::vector<uint32_t> ifm_bound_145 = {8, 20, 84, 12};
+std::vector<uint32_t> ifmsv_dim_145 = {8, 20, 2, 3};
+uint32_t ifmsv_size_145 = 3840;
+uint32_t kernel_iter_145 = 11;
+bool has_l1_write_access_pattern_145 = false;
+std::vector<access_pattern> l1_write_pattern_145 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_145 = {
+{
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_145 = 0;
+bool has_l1_wts_write_access_pattern_145 = false;
+std::vector<access_pattern> l1_wts_write_pattern_145 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_145 = {};
+
+
+std::vector<uint32_t> ofm_dim_145 = {8, 20, 88, 12};
+std::vector<uint32_t> ofm_bound_145 = {8, 20, 84, 12};
+std::vector<uint32_t> ofmsv_dim_145 = {8, 20, 2, 3};
+uint32_t ofmsv_size_145 = 960;
+uint32_t ofm_repetition_145 = 1;
+bool has_l1_read_access_pattern_145 = false;
+
+std::vector<access_pattern> l1_read_pattern_145 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_145 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 146
+// LayerName: Clip_241
+std::vector<uint32_t> ifm_dim_146 = {8, 20, 88, 12};
+std::vector<uint32_t> ifm_bound_146 = {8, 20, 84, 12};
+std::vector<uint32_t> ifmsv_dim_146 = {8, 20, 2, 3};
+uint32_t ifmsv_size_146 = 3840;
+uint32_t kernel_iter_146 = 11;
+bool has_l1_write_access_pattern_146 = false;
+std::vector<access_pattern> l1_write_pattern_146 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_146 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_146 = 0;
+bool has_l1_wts_write_access_pattern_146 = false;
+std::vector<access_pattern> l1_wts_write_pattern_146 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_146 = {};
+
+
+std::vector<uint32_t> ofm_dim_146 = {8, 20, 88, 12};
+std::vector<uint32_t> ofm_bound_146 = {8, 20, 84, 12};
+std::vector<uint32_t> ofmsv_dim_146 = {8, 20, 2, 3};
+uint32_t ofmsv_size_146 = 960;
+uint32_t ofm_repetition_146 = 1;
+bool has_l1_read_access_pattern_146 = false;
+
+std::vector<access_pattern> l1_read_pattern_146 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_146 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 147
+// LayerName: Div_243
+std::vector<uint32_t> ifm_dim_147 = {8, 20, 88, 12};
+std::vector<uint32_t> ifm_bound_147 = {8, 20, 84, 12};
+std::vector<uint32_t> ifmsv_dim_147 = {8, 20, 2, 3};
+uint32_t ifmsv_size_147 = 3840;
+uint32_t kernel_iter_147 = 11;
+bool has_l1_write_access_pattern_147 = false;
+std::vector<access_pattern> l1_write_pattern_147 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_147 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_147 = 0;
+bool has_l1_wts_write_access_pattern_147 = false;
+std::vector<access_pattern> l1_wts_write_pattern_147 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_147 = {};
+
+
+std::vector<uint32_t> ofm_dim_147 = {8, 20, 88, 12};
+std::vector<uint32_t> ofm_bound_147 = {8, 20, 84, 12};
+std::vector<uint32_t> ofmsv_dim_147 = {8, 20, 2, 3};
+uint32_t ofmsv_size_147 = 960;
+uint32_t ofm_repetition_147 = 1;
+bool has_l1_read_access_pattern_147 = false;
+
+std::vector<access_pattern> l1_read_pattern_147 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_147 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 148
+// LayerName: Mul_244
+std::vector<uint32_t> ifm_dim_148 = {8, 32, 84, 12};
+std::vector<uint32_t> ifm_bound_148 = {8, 20, 84, 12};
+std::vector<uint32_t> ifmsv_dim_148 = {8, 20, 2, 3};
+uint32_t ifmsv_size_148 = 3840;
+uint32_t kernel_iter_148 = 11;
+bool has_l1_write_access_pattern_148 = false;
+std::vector<access_pattern> l1_write_pattern_148 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_148 = {
+{
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 84, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_148 = {8, 20, 88, 12};
+std::vector<uint32_t> ifm2_bound_148 = {8, 20, 84, 12};
+std::vector<uint32_t> ifm2sv_dim_148 = {8, 20, 2, 3};
+uint32_t ifm2sv_size_148 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_148 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_148 = 0;
+bool has_l1_wts_write_access_pattern_148 = false;
+std::vector<access_pattern> l1_wts_write_pattern_148 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_148 = {};
+
+
+std::vector<uint32_t> ofm_dim_148 = {8, 20, 88, 12};
+std::vector<uint32_t> ofm_bound_148 = {8, 20, 84, 12};
+std::vector<uint32_t> ofmsv_dim_148 = {8, 20, 2, 3};
+uint32_t ofmsv_size_148 = 960;
+uint32_t ofm_repetition_148 = 1;
+bool has_l1_read_access_pattern_148 = false;
+
+std::vector<access_pattern> l1_read_pattern_148 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_148 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 149
+// LayerName: Conv_245
+std::vector<uint32_t> ifm_dim_149 = {8, 20, 88, 12};
+std::vector<uint32_t> ifm_bound_149 = {8, 20, 84, 12};
+std::vector<uint32_t> ifmsv_dim_149 = {8, 16, 1, 10};
+uint32_t ifmsv_size_149 = 5120;
+uint32_t kernel_iter_149 = 126;
+bool has_l1_write_access_pattern_149 = false;
+std::vector<access_pattern> l1_write_pattern_149 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_149 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 16, 1, 10}, .offset = {0, -4, 0, -4}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 84}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 16, 1, 10}, .offset = {0, -4, 0, -2}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 84}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 16, 1, 10}, .offset = {0, -4, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 84}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 16, 1, 10}, .offset = {0, -4, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 84}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_149 = {75264};
+std::vector<uint32_t> wts_dim_149 = {75264};
+std::vector<uint32_t> wtssv_dim_149 = {896};
+uint32_t wts_repetition_149 = 1;
+uint32_t wtssv_size_149 = 896;
+bool has_l1_wts_write_access_pattern_149 = false;
+std::vector<access_pattern> l1_wts_write_pattern_149 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_149 = {
+{
+  tiling({.buffer_dimension = {75264}, .tiling_dimension = {896}, .offset = {0}, .tile_traversal = { {.dimension = 0, .stride = 3584, .wrap = 21} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {75264}, .tiling_dimension = {896}, .offset = {896}, .tile_traversal = { {.dimension = 0, .stride = 3584, .wrap = 21} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {75264}, .tiling_dimension = {896}, .offset = {1792}, .tile_traversal = { {.dimension = 0, .stride = 3584, .wrap = 21} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {75264}, .tiling_dimension = {896}, .offset = {2688}, .tile_traversal = { {.dimension = 0, .stride = 3584, .wrap = 21} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_149[] = {
+{
+  tiling({.buffer_dimension = {75264, 1}, .tiling_dimension = {37632, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {75264, 1}, .tiling_dimension = {37632, 1}, .offset = {37632, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_149[] = {
+{
+  tiling({.buffer_dimension = {75264}, .tiling_dimension = {37632}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {75264}, .tiling_dimension = {37632}, .offset = {37632}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_149 = {8, 24, 84, 16};
+std::vector<uint32_t> ofm_bound_149 = {8, 20, 84, 12};
+std::vector<uint32_t> ofmsv_dim_149 = {8, 8, 1, 2};
+uint32_t ofmsv_size_149 = 128;
+uint32_t ofm_repetition_149 = 1;
+bool has_l1_read_access_pattern_149 = false;
+
+std::vector<access_pattern> l1_read_pattern_149 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_149 = {
+{
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 1, 2}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 2, 2}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 3, 2}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 1, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 2, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 3, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 1, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 3, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 21}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 150
+// LayerName: Add_247
+std::vector<uint32_t> ifm_dim_150 = {8, 24, 84, 16};
+std::vector<uint32_t> ifm_bound_150 = {8, 20, 84, 12};
+std::vector<uint32_t> ifmsv_dim_150 = {8, 20, 2, 3};
+uint32_t ifmsv_size_150 = 3840;
+uint32_t kernel_iter_150 = 11;
+bool has_l1_write_access_pattern_150 = false;
+std::vector<access_pattern> l1_write_pattern_150 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_150 = {
+{
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_150 = 0;
+bool has_l1_wts_write_access_pattern_150 = false;
+std::vector<access_pattern> l1_wts_write_pattern_150 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_150 = {};
+
+
+std::vector<uint32_t> ofm_dim_150 = {8, 20, 88, 12};
+std::vector<uint32_t> ofm_bound_150 = {8, 20, 84, 12};
+std::vector<uint32_t> ofmsv_dim_150 = {8, 20, 2, 3};
+uint32_t ofmsv_size_150 = 960;
+uint32_t ofm_repetition_150 = 1;
+bool has_l1_read_access_pattern_150 = false;
+
+std::vector<access_pattern> l1_read_pattern_150 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_150 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 151
+// LayerName: Clip_250
+std::vector<uint32_t> ifm_dim_151 = {8, 20, 88, 12};
+std::vector<uint32_t> ifm_bound_151 = {8, 20, 84, 12};
+std::vector<uint32_t> ifmsv_dim_151 = {8, 20, 2, 3};
+uint32_t ifmsv_size_151 = 3840;
+uint32_t kernel_iter_151 = 11;
+bool has_l1_write_access_pattern_151 = false;
+std::vector<access_pattern> l1_write_pattern_151 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_151 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_151 = 0;
+bool has_l1_wts_write_access_pattern_151 = false;
+std::vector<access_pattern> l1_wts_write_pattern_151 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_151 = {};
+
+
+std::vector<uint32_t> ofm_dim_151 = {8, 20, 88, 12};
+std::vector<uint32_t> ofm_bound_151 = {8, 20, 84, 12};
+std::vector<uint32_t> ofmsv_dim_151 = {8, 20, 2, 3};
+uint32_t ofmsv_size_151 = 960;
+uint32_t ofm_repetition_151 = 1;
+bool has_l1_read_access_pattern_151 = false;
+
+std::vector<access_pattern> l1_read_pattern_151 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_151 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 152
+// LayerName: Div_252
+std::vector<uint32_t> ifm_dim_152 = {8, 20, 88, 12};
+std::vector<uint32_t> ifm_bound_152 = {8, 20, 84, 12};
+std::vector<uint32_t> ifmsv_dim_152 = {8, 20, 2, 3};
+uint32_t ifmsv_size_152 = 3840;
+uint32_t kernel_iter_152 = 11;
+bool has_l1_write_access_pattern_152 = false;
+std::vector<access_pattern> l1_write_pattern_152 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_152 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_152 = 0;
+bool has_l1_wts_write_access_pattern_152 = false;
+std::vector<access_pattern> l1_wts_write_pattern_152 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_152 = {};
+
+
+std::vector<uint32_t> ofm_dim_152 = {8, 20, 88, 12};
+std::vector<uint32_t> ofm_bound_152 = {8, 20, 84, 12};
+std::vector<uint32_t> ofmsv_dim_152 = {8, 20, 2, 3};
+uint32_t ofmsv_size_152 = 960;
+uint32_t ofm_repetition_152 = 1;
+bool has_l1_read_access_pattern_152 = false;
+
+std::vector<access_pattern> l1_read_pattern_152 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_152 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 153
+// LayerName: Mul_253
+std::vector<uint32_t> ifm_dim_153 = {8, 24, 84, 16};
+std::vector<uint32_t> ifm_bound_153 = {8, 20, 84, 12};
+std::vector<uint32_t> ifmsv_dim_153 = {8, 20, 2, 3};
+uint32_t ifmsv_size_153 = 3840;
+uint32_t kernel_iter_153 = 11;
+bool has_l1_write_access_pattern_153 = false;
+std::vector<access_pattern> l1_write_pattern_153 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_153 = {
+{
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 84, 16}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_153 = {8, 20, 88, 12};
+std::vector<uint32_t> ifm2_bound_153 = {8, 20, 84, 12};
+std::vector<uint32_t> ifm2sv_dim_153 = {8, 20, 2, 3};
+uint32_t ifm2sv_size_153 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_153 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_153 = 0;
+bool has_l1_wts_write_access_pattern_153 = false;
+std::vector<access_pattern> l1_wts_write_pattern_153 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_153 = {};
+
+
+std::vector<uint32_t> ofm_dim_153 = {8, 20, 88, 12};
+std::vector<uint32_t> ofm_bound_153 = {8, 20, 84, 12};
+std::vector<uint32_t> ofmsv_dim_153 = {8, 20, 2, 3};
+uint32_t ofmsv_size_153 = 960;
+uint32_t ofm_repetition_153 = 1;
+bool has_l1_read_access_pattern_153 = false;
+
+std::vector<access_pattern> l1_read_pattern_153 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_153 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 155
+// LayerName: Generated-#38
+std::vector<uint32_t> ifm_dim_155 = {8, 240, 84, 1};
+std::vector<uint32_t> ifm_bound_155 = {8, 240, 84, 1};
+std::vector<uint32_t> ifmsv_dim_155 = {8, 32, 7, 1};
+uint32_t ifmsv_size_155 = 7168;
+uint32_t kernel_iter_155 = 24;
+bool has_l1_write_access_pattern_155 = false;
+std::vector<access_pattern> l1_write_pattern_155 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_155 = {
+{
+  tiling({.buffer_dimension = {8, 240, 84, 1}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 7, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 8}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 240, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 240, 84, 1}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 7, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 8}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 240, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 240, 84, 1}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 7, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 8}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 240, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 240, 84, 1}, .tiling_dimension = {8, 32, 7, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 7, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 8}, {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 240, 84, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_155 = 0;
+bool has_l1_wts_write_access_pattern_155 = false;
+std::vector<access_pattern> l1_wts_write_pattern_155 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_155 = {};
+
+
+std::vector<uint32_t> ofm_dim_155 = {8, 1, 84, 4};
+std::vector<uint32_t> ofm_bound_155 = {8, 1, 84, 1};
+std::vector<uint32_t> ofmsv_dim_155 = {8, 1, 7, 1};
+uint32_t ofmsv_size_155 = 56;
+uint32_t ofm_repetition_155 = 8;
+bool has_l1_read_access_pattern_155 = false;
+std::vector<access_pattern> l1_read_pattern_155 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ofm_pattern_155 = {
+{
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 7, 0}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 14, 0}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 21, 0}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 7, 1}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 14, 1}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 21, 1}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 7, 2}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 14, 2}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 21, 2}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 7, 3}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 14, 3}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 1, 7, 1}, .offset = {0, 0, 21, 3}, .tile_traversal = { {.dimension = 2, .stride = 28, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 156
+// LayerName: Conv_255
+std::vector<uint32_t> ifm_dim_156 = {8, 1, 84, 4};
+std::vector<uint32_t> ifm_bound_156 = {8, 1, 84, 1};
+std::vector<uint32_t> ifmsv_dim_156 = {8, 8, 12, 1};
+uint32_t ifmsv_size_156 = 768;
+uint32_t kernel_iter_156 = 7;
+bool has_l1_write_access_pattern_156 = false;
+std::vector<access_pattern> l1_write_pattern_156 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_156 = {
+{
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 8, 12, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 8, 12, 1}, .offset = {0, 8, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 8, 12, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 84, 4}, .tiling_dimension = {8, 8, 12, 1}, .offset = {0, 24, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_156 = {134400};
+std::vector<uint32_t> wts_dim_156 = {134400};
+std::vector<uint32_t> wtssv_dim_156 = {4800};
+uint32_t wtssv_size_156 = 4800;
+uint32_t wts_repetition_156 = 1;
+bool has_l1_wts_write_access_pattern_156 = false;
+std::vector<access_pattern> l1_wts_write_pattern_156 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_156 = {
+{
+  tiling({.buffer_dimension = {33600, 4}, .tiling_dimension = {4800, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 4800, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {33600, 4}, .tiling_dimension = {4800, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 4800, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {33600, 4}, .tiling_dimension = {4800, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 4800, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {33600, 4}, .tiling_dimension = {4800, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 4800, .wrap = 7} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_156[] = {
+{
+  tiling({.buffer_dimension = {134400, 1}, .tiling_dimension = {67200, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {134400, 1}, .tiling_dimension = {67200, 1}, .offset = {67200, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_156[] = {
+{
+  tiling({.buffer_dimension = {134400}, .tiling_dimension = {67200}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {134400}, .tiling_dimension = {67200}, .offset = {67200}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_156 = {8, 32, 24, 1};
+std::vector<uint32_t> ofm_bound_156 = {8, 1, 21, 1};
+std::vector<uint32_t> ofmsv_dim_156 = {8, 8, 6, 1};
+uint32_t ofmsv_size_156 = 384;
+uint32_t ofm_repetition_156 = 7;
+bool has_l1_read_access_pattern_156 = false;
+
+std::vector<access_pattern> l1_read_pattern_156 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_156 = {
+{
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 0, 6, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 0, 12, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 0, 18, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 8, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 8, 6, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 8, 12, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 8, 18, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 16, 6, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 16, 12, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 16, 18, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 24, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 24, 6, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 24, 12, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 24, 18, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 157
+// LayerName: Conv_257
+std::vector<uint32_t> ifm_dim_157 = {8, 32, 24, 1};
+std::vector<uint32_t> ifm_bound_157 = {8, 1, 21, 1};
+std::vector<uint32_t> ifmsv_dim_157 = {8, 16, 21, 1};
+uint32_t ifmsv_size_157 = 2688;
+uint32_t kernel_iter_157 = 11;
+bool has_l1_write_access_pattern_157 = false;
+std::vector<access_pattern> l1_write_pattern_157 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_157 = {
+{
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 16, 21, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 11, .boundary_dimension = {8, 1, 21, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 16, 21, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 11, .boundary_dimension = {8, 1, 21, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 16, 21, 1}, .offset = {0, 32, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 11, .boundary_dimension = {8, 1, 21, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 1}, .tiling_dimension = {8, 16, 21, 1}, .offset = {0, 48, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 11, .boundary_dimension = {8, 1, 21, 1}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_157 = {121088};
+std::vector<uint32_t> wts_dim_157 = {121088};
+std::vector<uint32_t> wtssv_dim_157 = {2752};
+uint32_t wtssv_size_157 = 2752;
+uint32_t wts_repetition_157 = 1;
+bool has_l1_wts_write_access_pattern_157 = false;
+std::vector<access_pattern> l1_wts_write_pattern_157 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_157 = {
+{
+  tiling({.buffer_dimension = {2752, 44}, .tiling_dimension = {2752, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 1, .stride = 4, .wrap = 11} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2752, 44}, .tiling_dimension = {2752, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 1, .stride = 4, .wrap = 11} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2752, 44}, .tiling_dimension = {2752, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 1, .stride = 4, .wrap = 11} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2752, 44}, .tiling_dimension = {2752, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 1, .stride = 4, .wrap = 11} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_157[] = {
+{
+  tiling({.buffer_dimension = {121088, 1}, .tiling_dimension = {60544, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {121088, 1}, .tiling_dimension = {60544, 1}, .offset = {60544, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_157[] = {
+{
+  tiling({.buffer_dimension = {121088}, .tiling_dimension = {60544}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {121088}, .tiling_dimension = {60544}, .offset = {60544}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_157 = {8, 64, 88, 1};
+std::vector<uint32_t> ofm_bound_157 = {8, 1, 84, 1};
+std::vector<uint32_t> ofmsv_dim_157 = {8, 16, 2, 1};
+uint32_t ofmsv_size_157 = 256;
+uint32_t ofm_repetition_157 = 1;
+bool has_l1_read_access_pattern_157 = false;
+
+std::vector<access_pattern> l1_read_pattern_157 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_157 = {
+{
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 158
+// LayerName: Add_259
+std::vector<uint32_t> ifm_dim_158 = {8, 64, 88, 1};
+std::vector<uint32_t> ifm_bound_158 = {8, 1, 84, 1};
+std::vector<uint32_t> ifmsv_dim_158 = {8, 1, 24, 2};
+uint32_t ifmsv_size_158 = 1536;
+uint32_t kernel_iter_158 = 1;
+bool has_l1_write_access_pattern_158 = false;
+std::vector<access_pattern> l1_write_pattern_158 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_158 = {
+{
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 88, 1}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_158 = 0;
+bool has_l1_wts_write_access_pattern_158 = false;
+std::vector<access_pattern> l1_wts_write_pattern_158 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_158 = {};
+
+
+std::vector<uint32_t> ofm_dim_158 = {8, 1, 96, 8};
+std::vector<uint32_t> ofm_bound_158 = {8, 1, 84, 1};
+std::vector<uint32_t> ofmsv_dim_158 = {8, 1, 24, 2};
+uint32_t ofmsv_size_158 = 384;
+uint32_t ofm_repetition_158 = 1;
+bool has_l1_read_access_pattern_158 = false;
+
+std::vector<access_pattern> l1_read_pattern_158 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_158 = {
+{
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 24, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 48, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 72, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 24, 2}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 48, 2}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 72, 2}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 24, 4}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 48, 4}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 72, 4}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 24, 6}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 48, 6}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 24, 2}, .offset = {0, 0, 72, 6}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 159
+// LayerName: Clip_262
+std::vector<uint32_t> ifm_dim_159 = {8, 1, 96, 8};
+std::vector<uint32_t> ifm_bound_159 = {8, 1, 84, 1};
+std::vector<uint32_t> ifmsv_dim_159 = {8, 1, 32, 1};
+uint32_t ifmsv_size_159 = 1024;
+uint32_t kernel_iter_159 = 1;
+bool has_l1_write_access_pattern_159 = false;
+std::vector<access_pattern> l1_write_pattern_159 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_159 = {
+{
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 96, 8}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_159 = 0;
+bool has_l1_wts_write_access_pattern_159 = false;
+std::vector<access_pattern> l1_wts_write_pattern_159 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_159 = {};
+
+
+std::vector<uint32_t> ofm_dim_159 = {8, 1, 128, 4};
+std::vector<uint32_t> ofm_bound_159 = {8, 1, 84, 1};
+std::vector<uint32_t> ofmsv_dim_159 = {8, 1, 32, 1};
+uint32_t ofmsv_size_159 = 256;
+uint32_t ofm_repetition_159 = 1;
+bool has_l1_read_access_pattern_159 = false;
+
+std::vector<access_pattern> l1_read_pattern_159 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_159 = {
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 32, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 64, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 96, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 32, 1}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 64, 1}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 96, 1}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 32, 2}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 64, 2}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 96, 2}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 32, 3}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 64, 3}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 96, 3}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 160
+// LayerName: Div_264
+std::vector<uint32_t> ifm_dim_160 = {8, 1, 128, 4};
+std::vector<uint32_t> ifm_bound_160 = {8, 1, 84, 1};
+std::vector<uint32_t> ifmsv_dim_160 = {8, 1, 32, 2};
+uint32_t ifmsv_size_160 = 2048;
+uint32_t kernel_iter_160 = 1;
+bool has_l1_write_access_pattern_160 = false;
+std::vector<access_pattern> l1_write_pattern_160 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_160 = {
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 84, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_160 = 0;
+bool has_l1_wts_write_access_pattern_160 = false;
+std::vector<access_pattern> l1_wts_write_pattern_160 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_160 = {};
+
+
+std::vector<uint32_t> ofm_dim_160 = {8, 1, 128, 8};
+std::vector<uint32_t> ofm_bound_160 = {8, 1, 84, 1};
+std::vector<uint32_t> ofmsv_dim_160 = {8, 1, 32, 2};
+uint32_t ofmsv_size_160 = 512;
+uint32_t ofm_repetition_160 = 1;
+bool has_l1_read_access_pattern_160 = false;
+
+std::vector<access_pattern> l1_read_pattern_160 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_160 = {
+{
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 32, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 64, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 96, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 32, 2}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 64, 2}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 96, 2}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 32, 4}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 64, 4}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 96, 4}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 32, 6}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 64, 6}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 96, 6}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 162
+// LayerName: Mul_265
+std::vector<uint32_t> ifm_dim_162 = {8, 20, 84, 12};
+std::vector<uint32_t> ifm_bound_162 = {8, 20, 84, 12};
+std::vector<uint32_t> ifmsv_dim_162 = {8, 20, 2, 3};
+uint32_t ifmsv_size_162 = 3840;
+uint32_t kernel_iter_162 = 11;
+bool has_l1_write_access_pattern_162 = false;
+std::vector<access_pattern> l1_write_pattern_162 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_162 = {
+{
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 84, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_162 = {8, 20, 88, 12};
+std::vector<uint32_t> ifm2_bound_162 = {8, 20, 84, 12};
+std::vector<uint32_t> ifm2sv_dim_162 = {8, 20, 2, 3};
+uint32_t ifm2sv_size_162 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_162 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 44} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_162 = 0;
+bool has_l1_wts_write_access_pattern_162 = false;
+std::vector<access_pattern> l1_wts_write_pattern_162 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_162 = {};
+
+
+std::vector<uint32_t> ofm_dim_162 = {8, 20, 88, 12};
+std::vector<uint32_t> ofm_bound_162 = {8, 20, 84, 12};
+std::vector<uint32_t> ofmsv_dim_162 = {8, 20, 2, 3};
+uint32_t ofmsv_size_162 = 960;
+uint32_t ofm_repetition_162 = 1;
+bool has_l1_read_access_pattern_162 = false;
+
+std::vector<access_pattern> l1_read_pattern_162 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_162 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 11} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 163
+// LayerName: Conv_266
+std::vector<uint32_t> ifm_dim_163 = {8, 20, 88, 12};
+std::vector<uint32_t> ifm_bound_163 = {8, 20, 84, 12};
+std::vector<uint32_t> ifmsv_dim_163 = {8, 32, 10, 1};
+uint32_t ifmsv_size_163 = 2560;
+uint32_t kernel_iter_163 = 27;
+bool has_l1_write_access_pattern_163 = true;
+std::vector<access_pattern> l1_write_pattern_163 = {tiling({.buffer_dimension = {8, 32, 10, 1}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_163 = {
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 9}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 9}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 9}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 88, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 9}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 84, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_163 = {120960};
+std::vector<uint32_t> wts_dim_163 = {120960};
+std::vector<uint32_t> wtssv_dim_163 = {3360};
+uint32_t wtssv_size_163 = 3360;
+uint32_t wts_repetition_163 = 1;
+bool has_l1_wts_write_access_pattern_163 = false;
+std::vector<access_pattern> l1_wts_write_pattern_163 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_163 = {
+{
+  tiling({.buffer_dimension = {30240, 4}, .tiling_dimension = {3360, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 9} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {30240, 4}, .tiling_dimension = {3360, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 9} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {30240, 4}, .tiling_dimension = {3360, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 9} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {30240, 4}, .tiling_dimension = {3360, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 9} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_163[] = {
+{
+  tiling({.buffer_dimension = {120960, 1}, .tiling_dimension = {60480, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {120960, 1}, .tiling_dimension = {60480, 1}, .offset = {60480, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_163[] = {
+{
+  tiling({.buffer_dimension = {120960}, .tiling_dimension = {60480}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {120960}, .tiling_dimension = {60480}, .offset = {60480}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_163 = {8, 32, 20, 12};
+std::vector<uint32_t> ofm_bound_163 = {8, 20, 20, 12};
+std::vector<uint32_t> ofmsv_dim_163 = {8, 32, 5, 1};
+uint32_t ofmsv_size_163 = 1280;
+uint32_t ofm_repetition_163 = 9;
+bool has_l1_read_access_pattern_163 = false;
+
+std::vector<access_pattern> l1_read_pattern_163 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_163 = {
+{
+  tiling({.buffer_dimension = {8, 32, 20, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 20, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 5, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 20, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 10, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 20, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 15, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 20, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 20, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 5, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 20, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 10, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 20, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 15, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 20, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 20, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 5, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 20, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 10, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 20, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 15, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 20, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 20, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 5, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 20, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 10, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 20, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 15, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 164
+// LayerName: Conv_267
+std::vector<uint32_t> ifm_dim_164 = {8, 32, 20, 12};
+std::vector<uint32_t> ifm_bound_164 = {8, 20, 20, 12};
+std::vector<uint32_t> ifmsv_dim_164 = {8, 32, 10, 1};
+uint32_t ifmsv_size_164 = 2560;
+uint32_t kernel_iter_164 = 36;
+bool has_l1_write_access_pattern_164 = true;
+std::vector<access_pattern> l1_write_pattern_164 = {tiling({.buffer_dimension = {8, 32, 10, 1}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_164 = {
+{
+  tiling({.buffer_dimension = {8, 32, 20, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {8, 20, 20, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 20, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {8, 20, 20, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 20, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {8, 20, 20, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 20, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {8, 20, 20, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_164 = {161280};
+std::vector<uint32_t> wts_dim_164 = {161280};
+std::vector<uint32_t> wtssv_dim_164 = {3360};
+uint32_t wtssv_size_164 = 3360;
+uint32_t wts_repetition_164 = 1;
+bool has_l1_wts_write_access_pattern_164 = false;
+std::vector<access_pattern> l1_wts_write_pattern_164 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_164 = {
+{
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 4}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 8}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 12}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 16}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 20}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 5}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 9}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 13}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 17}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 21}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 6}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 10}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 14}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 18}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 22}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 7}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 11}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 15}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 19}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 23}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_164[] = {
+{
+  tiling({.buffer_dimension = {161280, 1}, .tiling_dimension = {80640, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {161280, 1}, .tiling_dimension = {80640, 1}, .offset = {80640, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_164[] = {
+{
+  tiling({.buffer_dimension = {161280}, .tiling_dimension = {80640}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {161280}, .tiling_dimension = {80640}, .offset = {80640}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_164 = {8, 32, 120, 12};
+std::vector<uint32_t> ofm_bound_164 = {8, 20, 120, 12};
+std::vector<uint32_t> ofmsv_dim_164 = {8, 32, 5, 1};
+uint32_t ofmsv_size_164 = 1280;
+uint32_t ofm_repetition_164 = 2;
+bool has_l1_read_access_pattern_164 = false;
+
+std::vector<access_pattern> l1_read_pattern_164 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_164 = {
+{
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 5, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 10, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 15, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 5, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 10, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 15, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 5, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 10, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 15, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 5, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 10, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 15, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 165
+// LayerName: Add_269
+std::vector<uint32_t> ifm_dim_165 = {8, 32, 120, 12};
+std::vector<uint32_t> ifm_bound_165 = {8, 20, 120, 12};
+std::vector<uint32_t> ifmsv_dim_165 = {8, 20, 10, 1};
+uint32_t ifmsv_size_165 = 6400;
+uint32_t kernel_iter_165 = 9;
+bool has_l1_write_access_pattern_165 = false;
+std::vector<access_pattern> l1_write_pattern_165 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_165 = {
+{
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_165 = 0;
+bool has_l1_wts_write_access_pattern_165 = false;
+std::vector<access_pattern> l1_wts_write_pattern_165 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_165 = {};
+
+
+std::vector<uint32_t> ofm_dim_165 = {8, 20, 120, 12};
+std::vector<uint32_t> ofm_bound_165 = {8, 20, 120, 12};
+std::vector<uint32_t> ofmsv_dim_165 = {8, 20, 10, 1};
+uint32_t ofmsv_size_165 = 1600;
+uint32_t ofm_repetition_165 = 1;
+bool has_l1_read_access_pattern_165 = false;
+
+std::vector<access_pattern> l1_read_pattern_165 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_165 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 166
+// LayerName: Clip_272
+std::vector<uint32_t> ifm_dim_166 = {8, 20, 120, 12};
+std::vector<uint32_t> ifm_bound_166 = {8, 20, 120, 12};
+std::vector<uint32_t> ifmsv_dim_166 = {8, 20, 10, 1};
+uint32_t ifmsv_size_166 = 6400;
+uint32_t kernel_iter_166 = 9;
+bool has_l1_write_access_pattern_166 = false;
+std::vector<access_pattern> l1_write_pattern_166 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_166 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_166 = 0;
+bool has_l1_wts_write_access_pattern_166 = false;
+std::vector<access_pattern> l1_wts_write_pattern_166 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_166 = {};
+
+
+std::vector<uint32_t> ofm_dim_166 = {8, 20, 120, 12};
+std::vector<uint32_t> ofm_bound_166 = {8, 20, 120, 12};
+std::vector<uint32_t> ofmsv_dim_166 = {8, 20, 10, 1};
+uint32_t ofmsv_size_166 = 1600;
+uint32_t ofm_repetition_166 = 1;
+bool has_l1_read_access_pattern_166 = false;
+
+std::vector<access_pattern> l1_read_pattern_166 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_166 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 167
+// LayerName: Div_274
+std::vector<uint32_t> ifm_dim_167 = {8, 20, 120, 12};
+std::vector<uint32_t> ifm_bound_167 = {8, 20, 120, 12};
+std::vector<uint32_t> ifmsv_dim_167 = {8, 20, 10, 1};
+uint32_t ifmsv_size_167 = 6400;
+uint32_t kernel_iter_167 = 9;
+bool has_l1_write_access_pattern_167 = false;
+std::vector<access_pattern> l1_write_pattern_167 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_167 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_167 = 0;
+bool has_l1_wts_write_access_pattern_167 = false;
+std::vector<access_pattern> l1_wts_write_pattern_167 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_167 = {};
+
+
+std::vector<uint32_t> ofm_dim_167 = {8, 20, 120, 12};
+std::vector<uint32_t> ofm_bound_167 = {8, 20, 120, 12};
+std::vector<uint32_t> ofmsv_dim_167 = {8, 20, 10, 1};
+uint32_t ofmsv_size_167 = 1600;
+uint32_t ofm_repetition_167 = 1;
+bool has_l1_read_access_pattern_167 = false;
+
+std::vector<access_pattern> l1_read_pattern_167 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_167 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 168
+// LayerName: Mul_275
+std::vector<uint32_t> ifm_dim_168 = {8, 20, 120, 6};
+std::vector<uint32_t> ifm_bound_168 = {8, 20, 120, 6};
+std::vector<uint32_t> ifmsv_dim_168 = {8, 20, 3, 2};
+uint32_t ifmsv_size_168 = 3840;
+uint32_t kernel_iter_168 = 20;
+bool has_l1_write_access_pattern_168 = false;
+std::vector<access_pattern> l1_write_pattern_168 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_168 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_168 = {8, 20, 120, 6};
+std::vector<uint32_t> ifm2_bound_168 = {8, 20, 120, 6};
+std::vector<uint32_t> ifm2sv_dim_168 = {8, 20, 3, 2};
+uint32_t ifm2sv_size_168 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_168 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_168 = 0;
+bool has_l1_wts_write_access_pattern_168 = false;
+std::vector<access_pattern> l1_wts_write_pattern_168 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_168 = {};
+
+
+std::vector<uint32_t> ofm_dim_168 = {8, 20, 120, 8};
+std::vector<uint32_t> ofm_bound_168 = {8, 20, 120, 6};
+std::vector<uint32_t> ofmsv_dim_168 = {8, 20, 3, 2};
+uint32_t ofmsv_size_168 = 960;
+uint32_t ofm_repetition_168 = 1;
+bool has_l1_read_access_pattern_168 = false;
+
+std::vector<access_pattern> l1_read_pattern_168 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_168 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 9, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 3, 2}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 6, 2}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 9, 2}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 3, 4}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 6, 4}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 9, 4}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 3, 6}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 9, 6}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 169
+// LayerName: Conv_276
+std::vector<uint32_t> ifm_dim_169 = {8, 20, 120, 12};
+std::vector<uint32_t> ifm_bound_169 = {8, 20, 120, 12};
+std::vector<uint32_t> ifmsv_dim_169 = {8, 16, 1, 10};
+uint32_t ifmsv_size_169 = 5120;
+uint32_t kernel_iter_169 = 180;
+bool has_l1_write_access_pattern_169 = false;
+std::vector<access_pattern> l1_write_pattern_169 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_169 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 16, 1, 10}, .offset = {0, -4, 0, -4}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 120}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 16, 1, 10}, .offset = {0, -4, 0, -2}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 120}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 16, 1, 10}, .offset = {0, -4, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 120}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 16, 1, 10}, .offset = {0, -4, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 120}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_169 = {107520};
+std::vector<uint32_t> wts_dim_169 = {107520};
+std::vector<uint32_t> wtssv_dim_169 = {896};
+uint32_t wts_repetition_169 = 1;
+uint32_t wtssv_size_169 = 896;
+bool has_l1_wts_write_access_pattern_169 = false;
+std::vector<access_pattern> l1_wts_write_pattern_169 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_169 = {
+{
+  tiling({.buffer_dimension = {107520}, .tiling_dimension = {896}, .offset = {0}, .tile_traversal = { {.dimension = 0, .stride = 3584, .wrap = 30} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {107520}, .tiling_dimension = {896}, .offset = {896}, .tile_traversal = { {.dimension = 0, .stride = 3584, .wrap = 30} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {107520}, .tiling_dimension = {896}, .offset = {1792}, .tile_traversal = { {.dimension = 0, .stride = 3584, .wrap = 30} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {107520}, .tiling_dimension = {896}, .offset = {2688}, .tile_traversal = { {.dimension = 0, .stride = 3584, .wrap = 30} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_169[] = {
+{
+  tiling({.buffer_dimension = {107520, 1}, .tiling_dimension = {53760, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {107520, 1}, .tiling_dimension = {53760, 1}, .offset = {53760, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_169[] = {
+{
+  tiling({.buffer_dimension = {107520}, .tiling_dimension = {53760}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {107520}, .tiling_dimension = {53760}, .offset = {53760}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_169 = {8, 24, 120, 16};
+std::vector<uint32_t> ofm_bound_169 = {8, 20, 120, 12};
+std::vector<uint32_t> ofmsv_dim_169 = {8, 8, 1, 2};
+uint32_t ofmsv_size_169 = 128;
+uint32_t ofm_repetition_169 = 1;
+bool has_l1_read_access_pattern_169 = false;
+
+std::vector<access_pattern> l1_read_pattern_169 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_169 = {
+{
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 1, 2}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 2, 2}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 3, 2}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 1, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 2, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 3, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 1, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 3, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 170
+// LayerName: Add_278
+std::vector<uint32_t> ifm_dim_170 = {8, 24, 120, 16};
+std::vector<uint32_t> ifm_bound_170 = {8, 20, 120, 12};
+std::vector<uint32_t> ifmsv_dim_170 = {8, 20, 10, 1};
+uint32_t ifmsv_size_170 = 6400;
+uint32_t kernel_iter_170 = 9;
+bool has_l1_write_access_pattern_170 = false;
+std::vector<access_pattern> l1_write_pattern_170 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_170 = {
+{
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_170 = 0;
+bool has_l1_wts_write_access_pattern_170 = false;
+std::vector<access_pattern> l1_wts_write_pattern_170 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_170 = {};
+
+
+std::vector<uint32_t> ofm_dim_170 = {8, 20, 120, 12};
+std::vector<uint32_t> ofm_bound_170 = {8, 20, 120, 12};
+std::vector<uint32_t> ofmsv_dim_170 = {8, 20, 10, 1};
+uint32_t ofmsv_size_170 = 1600;
+uint32_t ofm_repetition_170 = 1;
+bool has_l1_read_access_pattern_170 = false;
+
+std::vector<access_pattern> l1_read_pattern_170 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_170 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 171
+// LayerName: Clip_281
+std::vector<uint32_t> ifm_dim_171 = {8, 20, 120, 12};
+std::vector<uint32_t> ifm_bound_171 = {8, 20, 120, 12};
+std::vector<uint32_t> ifmsv_dim_171 = {8, 20, 10, 1};
+uint32_t ifmsv_size_171 = 6400;
+uint32_t kernel_iter_171 = 9;
+bool has_l1_write_access_pattern_171 = false;
+std::vector<access_pattern> l1_write_pattern_171 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_171 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_171 = 0;
+bool has_l1_wts_write_access_pattern_171 = false;
+std::vector<access_pattern> l1_wts_write_pattern_171 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_171 = {};
+
+
+std::vector<uint32_t> ofm_dim_171 = {8, 20, 120, 12};
+std::vector<uint32_t> ofm_bound_171 = {8, 20, 120, 12};
+std::vector<uint32_t> ofmsv_dim_171 = {8, 20, 10, 1};
+uint32_t ofmsv_size_171 = 1600;
+uint32_t ofm_repetition_171 = 1;
+bool has_l1_read_access_pattern_171 = false;
+
+std::vector<access_pattern> l1_read_pattern_171 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_171 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 172
+// LayerName: Div_283
+std::vector<uint32_t> ifm_dim_172 = {8, 20, 120, 12};
+std::vector<uint32_t> ifm_bound_172 = {8, 20, 120, 12};
+std::vector<uint32_t> ifmsv_dim_172 = {8, 20, 10, 1};
+uint32_t ifmsv_size_172 = 6400;
+uint32_t kernel_iter_172 = 9;
+bool has_l1_write_access_pattern_172 = false;
+std::vector<access_pattern> l1_write_pattern_172 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_172 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_172 = 0;
+bool has_l1_wts_write_access_pattern_172 = false;
+std::vector<access_pattern> l1_wts_write_pattern_172 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_172 = {};
+
+
+std::vector<uint32_t> ofm_dim_172 = {8, 20, 120, 12};
+std::vector<uint32_t> ofm_bound_172 = {8, 20, 120, 12};
+std::vector<uint32_t> ofmsv_dim_172 = {8, 20, 10, 1};
+uint32_t ofmsv_size_172 = 1600;
+uint32_t ofm_repetition_172 = 1;
+bool has_l1_read_access_pattern_172 = false;
+
+std::vector<access_pattern> l1_read_pattern_172 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_172 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 173
+// LayerName: Mul_284
+std::vector<uint32_t> ifm_dim_173 = {8, 20, 120, 6};
+std::vector<uint32_t> ifm_bound_173 = {8, 20, 120, 6};
+std::vector<uint32_t> ifmsv_dim_173 = {8, 20, 3, 2};
+uint32_t ifmsv_size_173 = 3840;
+uint32_t kernel_iter_173 = 20;
+bool has_l1_write_access_pattern_173 = false;
+std::vector<access_pattern> l1_write_pattern_173 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_173 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_173 = {8, 20, 120, 6};
+std::vector<uint32_t> ifm2_bound_173 = {8, 20, 120, 6};
+std::vector<uint32_t> ifm2sv_dim_173 = {8, 20, 3, 2};
+uint32_t ifm2sv_size_173 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_173 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_173 = 0;
+bool has_l1_wts_write_access_pattern_173 = false;
+std::vector<access_pattern> l1_wts_write_pattern_173 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_173 = {};
+
+
+std::vector<uint32_t> ofm_dim_173 = {8, 20, 120, 8};
+std::vector<uint32_t> ofm_bound_173 = {8, 20, 120, 6};
+std::vector<uint32_t> ofmsv_dim_173 = {8, 20, 3, 2};
+uint32_t ofmsv_size_173 = 960;
+uint32_t ofm_repetition_173 = 1;
+bool has_l1_read_access_pattern_173 = false;
+
+std::vector<access_pattern> l1_read_pattern_173 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_173 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 9, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 3, 2}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 6, 2}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 9, 2}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 3, 4}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 6, 4}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 9, 4}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 3, 6}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 9, 6}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 175
+// LayerName: Generated-#44
+std::vector<uint32_t> ifm_dim_175 = {8, 240, 120, 1};
+std::vector<uint32_t> ifm_bound_175 = {8, 240, 120, 1};
+std::vector<uint32_t> ifmsv_dim_175 = {8, 48, 5, 1};
+uint32_t ifmsv_size_175 = 7680;
+uint32_t kernel_iter_175 = 30;
+bool has_l1_write_access_pattern_175 = false;
+std::vector<access_pattern> l1_write_pattern_175 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_175 = {
+{
+  tiling({.buffer_dimension = {8, 240, 120, 1}, .tiling_dimension = {8, 48, 5, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 5, .wrap = 4}, {.dimension = 1, .stride = 48, .wrap = 5}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 240, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 240, 120, 1}, .tiling_dimension = {8, 48, 5, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 5, .wrap = 4}, {.dimension = 1, .stride = 48, .wrap = 5}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 240, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 240, 120, 1}, .tiling_dimension = {8, 48, 5, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 5, .wrap = 4}, {.dimension = 1, .stride = 48, .wrap = 5}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 240, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 240, 120, 1}, .tiling_dimension = {8, 48, 5, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 5, .wrap = 4}, {.dimension = 1, .stride = 48, .wrap = 5}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 240, 120, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_175 = 0;
+bool has_l1_wts_write_access_pattern_175 = false;
+std::vector<access_pattern> l1_wts_write_pattern_175 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_175 = {};
+
+
+std::vector<uint32_t> ofm_dim_175 = {8, 1, 120, 4};
+std::vector<uint32_t> ofm_bound_175 = {8, 1, 120, 1};
+std::vector<uint32_t> ofmsv_dim_175 = {8, 1, 5, 1};
+uint32_t ofmsv_size_175 = 40;
+uint32_t ofm_repetition_175 = 5;
+bool has_l1_read_access_pattern_175 = false;
+std::vector<access_pattern> l1_read_pattern_175 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ofm_pattern_175 = {
+{
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 5, 0}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 10, 0}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 15, 0}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 5, 1}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 10, 1}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 15, 1}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 5, 2}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 10, 2}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 15, 2}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 5, 3}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 10, 3}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 15, 3}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 176
+// LayerName: Conv_286
+std::vector<uint32_t> ifm_dim_176 = {8, 1, 120, 4};
+std::vector<uint32_t> ifm_bound_176 = {8, 1, 120, 1};
+std::vector<uint32_t> ifmsv_dim_176 = {8, 16, 24, 1};
+uint32_t ifmsv_size_176 = 3072;
+uint32_t kernel_iter_176 = 20;
+bool has_l1_write_access_pattern_176 = false;
+std::vector<access_pattern> l1_write_pattern_176 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_176 = {
+{
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 16, 24, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = -1, .repetition = 4, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 16, 24, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = -1, .repetition = 4, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 16, 24, 1}, .offset = {0, 32, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = -1, .repetition = 4, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 16, 24, 1}, .offset = {0, 48, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = -1, .repetition = 4, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_176 = {250880};
+std::vector<uint32_t> wts_dim_176 = {250880};
+std::vector<uint32_t> wtssv_dim_176 = {3136};
+uint32_t wtssv_size_176 = 3136;
+uint32_t wts_repetition_176 = 1;
+bool has_l1_wts_write_access_pattern_176 = false;
+std::vector<access_pattern> l1_wts_write_pattern_176 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_176 = {
+{
+  tiling({.buffer_dimension = {15680, 16}, .tiling_dimension = {3136, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 3136, .wrap = 5}, {.dimension = 1, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {15680, 16}, .tiling_dimension = {3136, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 3136, .wrap = 5}, {.dimension = 1, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {15680, 16}, .tiling_dimension = {3136, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 3136, .wrap = 5}, {.dimension = 1, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {15680, 16}, .tiling_dimension = {3136, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 3136, .wrap = 5}, {.dimension = 1, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_176[] = {
+{
+  tiling({.buffer_dimension = {250880, 1}, .tiling_dimension = {125440, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {250880, 1}, .tiling_dimension = {125440, 1}, .offset = {125440, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_176[] = {
+{
+  tiling({.buffer_dimension = {250880}, .tiling_dimension = {125440}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {250880}, .tiling_dimension = {125440}, .offset = {125440}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_176 = {8, 64, 32, 1};
+std::vector<uint32_t> ofm_bound_176 = {8, 1, 30, 1};
+std::vector<uint32_t> ofmsv_dim_176 = {8, 16, 2, 1};
+uint32_t ofmsv_size_176 = 256;
+uint32_t ofm_repetition_176 = 5;
+bool has_l1_read_access_pattern_176 = false;
+
+std::vector<access_pattern> l1_read_pattern_176 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_176 = {
+{
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 177
+// LayerName: Conv_288
+std::vector<uint32_t> ifm_dim_177 = {8, 64, 32, 1};
+std::vector<uint32_t> ifm_bound_177 = {8, 1, 30, 1};
+std::vector<uint32_t> ifmsv_dim_177 = {8, 8, 10, 1};
+uint32_t ifmsv_size_177 = 640;
+uint32_t kernel_iter_177 = 15;
+bool has_l1_write_access_pattern_177 = false;
+std::vector<access_pattern> l1_write_pattern_177 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_177 = {
+{
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 8, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 3} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {8, 1, 30, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 8, 10, 1}, .offset = {0, 8, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 3} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {8, 1, 30, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 8, 10, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 3} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {8, 1, 30, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 8, 10, 1}, .offset = {0, 24, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 3} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {8, 1, 30, 1}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_177 = {241920};
+std::vector<uint32_t> wts_dim_177 = {241920};
+std::vector<uint32_t> wtssv_dim_177 = {4032};
+uint32_t wtssv_size_177 = 4032;
+uint32_t wts_repetition_177 = 1;
+bool has_l1_wts_write_access_pattern_177 = false;
+std::vector<access_pattern> l1_wts_write_pattern_177 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_177 = {
+{
+  tiling({.buffer_dimension = {12096, 20}, .tiling_dimension = {4032, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 4032, .wrap = 3}, {.dimension = 1, .stride = 4, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {12096, 20}, .tiling_dimension = {4032, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 4032, .wrap = 3}, {.dimension = 1, .stride = 4, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {12096, 20}, .tiling_dimension = {4032, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 4032, .wrap = 3}, {.dimension = 1, .stride = 4, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {12096, 20}, .tiling_dimension = {4032, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 4032, .wrap = 3}, {.dimension = 1, .stride = 4, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_177[] = {
+{
+  tiling({.buffer_dimension = {241920, 1}, .tiling_dimension = {120960, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {241920, 1}, .tiling_dimension = {120960, 1}, .offset = {120960, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_177[] = {
+{
+  tiling({.buffer_dimension = {241920}, .tiling_dimension = {120960}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {241920}, .tiling_dimension = {120960}, .offset = {120960}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_177 = {8, 32, 120, 1};
+std::vector<uint32_t> ofm_bound_177 = {8, 1, 120, 1};
+std::vector<uint32_t> ofmsv_dim_177 = {8, 8, 6, 1};
+uint32_t ofmsv_size_177 = 384;
+uint32_t ofm_repetition_177 = 3;
+bool has_l1_read_access_pattern_177 = false;
+
+std::vector<access_pattern> l1_read_pattern_177 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_177 = {
+{
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 0, 12, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 0, 18, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 8, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 8, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 8, 12, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 8, 18, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 16, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 16, 12, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 16, 18, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 24, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 24, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 24, 12, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 24, 18, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 178
+// LayerName: Add_290
+std::vector<uint32_t> ifm_dim_178 = {8, 32, 120, 1};
+std::vector<uint32_t> ifm_bound_178 = {8, 1, 120, 1};
+std::vector<uint32_t> ifmsv_dim_178 = {8, 1, 48, 1};
+uint32_t ifmsv_size_178 = 1536;
+uint32_t kernel_iter_178 = 1;
+bool has_l1_write_access_pattern_178 = false;
+std::vector<access_pattern> l1_write_pattern_178 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_178 = {
+{
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 48, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 48, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 48, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 48, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_178 = 0;
+bool has_l1_wts_write_access_pattern_178 = false;
+std::vector<access_pattern> l1_wts_write_pattern_178 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_178 = {};
+
+
+std::vector<uint32_t> ofm_dim_178 = {8, 1, 192, 4};
+std::vector<uint32_t> ofm_bound_178 = {8, 1, 120, 1};
+std::vector<uint32_t> ofmsv_dim_178 = {8, 1, 48, 1};
+uint32_t ofmsv_size_178 = 384;
+uint32_t ofm_repetition_178 = 1;
+bool has_l1_read_access_pattern_178 = false;
+
+std::vector<access_pattern> l1_read_pattern_178 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_178 = {
+{
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 48, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 96, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 144, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 48, 1}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 96, 1}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 144, 1}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 48, 2}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 96, 2}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 144, 2}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 48, 3}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 96, 3}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 144, 3}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 179
+// LayerName: Clip_293
+std::vector<uint32_t> ifm_dim_179 = {8, 1, 192, 4};
+std::vector<uint32_t> ifm_bound_179 = {8, 1, 120, 1};
+std::vector<uint32_t> ifmsv_dim_179 = {8, 1, 32, 1};
+uint32_t ifmsv_size_179 = 1024;
+uint32_t kernel_iter_179 = 1;
+bool has_l1_write_access_pattern_179 = false;
+std::vector<access_pattern> l1_write_pattern_179 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_179 = {
+{
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_179 = 0;
+bool has_l1_wts_write_access_pattern_179 = false;
+std::vector<access_pattern> l1_wts_write_pattern_179 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_179 = {};
+
+
+std::vector<uint32_t> ofm_dim_179 = {8, 1, 128, 4};
+std::vector<uint32_t> ofm_bound_179 = {8, 1, 120, 1};
+std::vector<uint32_t> ofmsv_dim_179 = {8, 1, 32, 1};
+uint32_t ofmsv_size_179 = 256;
+uint32_t ofm_repetition_179 = 1;
+bool has_l1_read_access_pattern_179 = false;
+
+std::vector<access_pattern> l1_read_pattern_179 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_179 = {
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 32, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 64, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 96, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 32, 1}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 64, 1}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 96, 1}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 32, 2}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 64, 2}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 96, 2}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 32, 3}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 64, 3}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 96, 3}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 180
+// LayerName: Div_295
+std::vector<uint32_t> ifm_dim_180 = {8, 1, 128, 4};
+std::vector<uint32_t> ifm_bound_180 = {8, 1, 120, 1};
+std::vector<uint32_t> ifmsv_dim_180 = {8, 1, 32, 2};
+uint32_t ifmsv_size_180 = 2048;
+uint32_t kernel_iter_180 = 1;
+bool has_l1_write_access_pattern_180 = false;
+std::vector<access_pattern> l1_write_pattern_180 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_180 = {
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_180 = 0;
+bool has_l1_wts_write_access_pattern_180 = false;
+std::vector<access_pattern> l1_wts_write_pattern_180 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_180 = {};
+
+
+std::vector<uint32_t> ofm_dim_180 = {8, 1, 128, 8};
+std::vector<uint32_t> ofm_bound_180 = {8, 1, 120, 1};
+std::vector<uint32_t> ofmsv_dim_180 = {8, 1, 32, 2};
+uint32_t ofmsv_size_180 = 512;
+uint32_t ofm_repetition_180 = 1;
+bool has_l1_read_access_pattern_180 = false;
+
+std::vector<access_pattern> l1_read_pattern_180 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_180 = {
+{
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 32, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 64, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 96, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 32, 2}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 64, 2}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 96, 2}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 32, 4}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 64, 4}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 96, 4}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 32, 6}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 64, 6}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 96, 6}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 182
+// LayerName: Mul_296
+std::vector<uint32_t> ifm_dim_182 = {8, 20, 120, 12};
+std::vector<uint32_t> ifm_bound_182 = {8, 20, 120, 12};
+std::vector<uint32_t> ifmsv_dim_182 = {8, 20, 2, 3};
+uint32_t ifmsv_size_182 = 3840;
+uint32_t kernel_iter_182 = 15;
+bool has_l1_write_access_pattern_182 = false;
+std::vector<access_pattern> l1_write_pattern_182 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_182 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 60} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 60} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 60} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 60} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_182 = {8, 20, 120, 12};
+std::vector<uint32_t> ifm2_bound_182 = {8, 20, 120, 12};
+std::vector<uint32_t> ifm2sv_dim_182 = {8, 20, 2, 3};
+uint32_t ifm2sv_size_182 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_182 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 60} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 60} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 60} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 60} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_182 = 0;
+bool has_l1_wts_write_access_pattern_182 = false;
+std::vector<access_pattern> l1_wts_write_pattern_182 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_182 = {};
+
+
+std::vector<uint32_t> ofm_dim_182 = {8, 20, 120, 12};
+std::vector<uint32_t> ofm_bound_182 = {8, 20, 120, 12};
+std::vector<uint32_t> ofmsv_dim_182 = {8, 20, 2, 3};
+uint32_t ofmsv_size_182 = 960;
+uint32_t ofm_repetition_182 = 1;
+bool has_l1_read_access_pattern_182 = false;
+
+std::vector<access_pattern> l1_read_pattern_182 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_182 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 183
+// LayerName: Conv_297
+std::vector<uint32_t> ifm_dim_183 = {8, 20, 120, 12};
+std::vector<uint32_t> ifm_bound_183 = {8, 20, 120, 12};
+std::vector<uint32_t> ifmsv_dim_183 = {8, 32, 14, 1};
+uint32_t ifmsv_size_183 = 3584;
+uint32_t kernel_iter_183 = 54;
+bool has_l1_write_access_pattern_183 = false;
+std::vector<access_pattern> l1_write_pattern_183 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_183 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 32, 14, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 14, .wrap = 9}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 32, 14, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 14, .wrap = 9}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 32, 14, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 14, .wrap = 9}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 32, 14, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 14, .wrap = 9}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_183 = {8, 32, 24, 12};
+std::vector<uint32_t> ifm2_bound_183 = {8, 20, 20, 12};
+std::vector<uint32_t> ifm2sv_dim_183 = {8, 32, 3, 1};
+uint32_t ifm2sv_size_183 = 3072;
+std::vector<std::vector<access_pattern>> ifm2_pattern_183 = {
+{
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 20, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 20, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 20, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 20, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_183 = {200448};
+std::vector<uint32_t> wts_dim_183 = {200448};
+std::vector<uint32_t> wtssv_dim_183 = {2784};
+uint32_t wtssv_size_183 = 2784;
+uint32_t wts_repetition_183 = 1;
+bool has_l1_wts_write_access_pattern_183 = false;
+std::vector<access_pattern> l1_wts_write_pattern_183 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_183 = {
+{
+  tiling({.buffer_dimension = {25056, 8}, .tiling_dimension = {2784, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 2784, .wrap = 9} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {25056, 8}, .tiling_dimension = {2784, 1}, .offset = {0, 4}, .tile_traversal = { {.dimension = 0, .stride = 2784, .wrap = 9} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {25056, 8}, .tiling_dimension = {2784, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 2784, .wrap = 9} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {25056, 8}, .tiling_dimension = {2784, 1}, .offset = {0, 5}, .tile_traversal = { {.dimension = 0, .stride = 2784, .wrap = 9} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {25056, 8}, .tiling_dimension = {2784, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 2784, .wrap = 9} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {25056, 8}, .tiling_dimension = {2784, 1}, .offset = {0, 6}, .tile_traversal = { {.dimension = 0, .stride = 2784, .wrap = 9} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {25056, 8}, .tiling_dimension = {2784, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 2784, .wrap = 9} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {25056, 8}, .tiling_dimension = {2784, 1}, .offset = {0, 7}, .tile_traversal = { {.dimension = 0, .stride = 2784, .wrap = 9} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_183[] = {
+{
+  tiling({.buffer_dimension = {200448, 1}, .tiling_dimension = {100224, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {200448, 1}, .tiling_dimension = {100224, 1}, .offset = {100224, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_183[] = {
+{
+  tiling({.buffer_dimension = {200448}, .tiling_dimension = {100224}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {200448}, .tiling_dimension = {100224}, .offset = {100224}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_183 = {8, 32, 24, 12};
+std::vector<uint32_t> ofm_bound_183 = {8, 20, 20, 12};
+std::vector<uint32_t> ofmsv_dim_183 = {8, 32, 3, 1};
+uint32_t ofmsv_size_183 = 768;
+uint32_t ofm_repetition_183 = 9;
+bool has_l1_read_access_pattern_183 = false;
+
+std::vector<access_pattern> l1_read_pattern_183 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_183 = {
+{
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 9, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 3, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 6, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 9, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 3, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 6, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 9, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 3, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 9, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 184
+// LayerName: Conv_299
+std::vector<uint32_t> ifm_dim_184 = {8, 32, 24, 12};
+std::vector<uint32_t> ifm_bound_184 = {8, 20, 20, 12};
+std::vector<uint32_t> ifmsv_dim_184 = {8, 32, 10, 1};
+uint32_t ifmsv_size_184 = 2560;
+uint32_t kernel_iter_184 = 36;
+bool has_l1_write_access_pattern_184 = true;
+std::vector<access_pattern> l1_write_pattern_184 = {tiling({.buffer_dimension = {8, 32, 10, 1}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_184 = {
+{
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {8, 20, 20, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {8, 20, 20, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {8, 20, 20, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {8, 20, 20, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_184 = {161280};
+std::vector<uint32_t> wts_dim_184 = {161280};
+std::vector<uint32_t> wtssv_dim_184 = {3360};
+uint32_t wtssv_size_184 = 3360;
+uint32_t wts_repetition_184 = 1;
+bool has_l1_wts_write_access_pattern_184 = false;
+std::vector<access_pattern> l1_wts_write_pattern_184 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_184 = {
+{
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 4}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 8}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 12}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 16}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 20}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 5}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 9}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 13}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 17}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 21}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 6}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 10}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 14}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 18}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 22}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 7}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 11}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 15}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 19}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 23}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_184[] = {
+{
+  tiling({.buffer_dimension = {161280, 1}, .tiling_dimension = {80640, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {161280, 1}, .tiling_dimension = {80640, 1}, .offset = {80640, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_184[] = {
+{
+  tiling({.buffer_dimension = {161280}, .tiling_dimension = {80640}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {161280}, .tiling_dimension = {80640}, .offset = {80640}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_184 = {8, 32, 120, 12};
+std::vector<uint32_t> ofm_bound_184 = {8, 20, 120, 12};
+std::vector<uint32_t> ofmsv_dim_184 = {8, 32, 5, 1};
+uint32_t ofmsv_size_184 = 1280;
+uint32_t ofm_repetition_184 = 2;
+bool has_l1_read_access_pattern_184 = false;
+
+std::vector<access_pattern> l1_read_pattern_184 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_184 = {
+{
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 5, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 10, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 15, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 5, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 10, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 15, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 5, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 10, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 15, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 5, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 10, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 15, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 185
+// LayerName: Add_301
+std::vector<uint32_t> ifm_dim_185 = {8, 32, 120, 12};
+std::vector<uint32_t> ifm_bound_185 = {8, 20, 120, 12};
+std::vector<uint32_t> ifmsv_dim_185 = {8, 20, 10, 1};
+uint32_t ifmsv_size_185 = 6400;
+uint32_t kernel_iter_185 = 9;
+bool has_l1_write_access_pattern_185 = false;
+std::vector<access_pattern> l1_write_pattern_185 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_185 = {
+{
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_185 = 0;
+bool has_l1_wts_write_access_pattern_185 = false;
+std::vector<access_pattern> l1_wts_write_pattern_185 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_185 = {};
+
+
+std::vector<uint32_t> ofm_dim_185 = {8, 20, 120, 12};
+std::vector<uint32_t> ofm_bound_185 = {8, 20, 120, 12};
+std::vector<uint32_t> ofmsv_dim_185 = {8, 20, 10, 1};
+uint32_t ofmsv_size_185 = 1600;
+uint32_t ofm_repetition_185 = 1;
+bool has_l1_read_access_pattern_185 = false;
+
+std::vector<access_pattern> l1_read_pattern_185 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_185 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 186
+// LayerName: Clip_304
+std::vector<uint32_t> ifm_dim_186 = {8, 20, 120, 12};
+std::vector<uint32_t> ifm_bound_186 = {8, 20, 120, 12};
+std::vector<uint32_t> ifmsv_dim_186 = {8, 20, 10, 1};
+uint32_t ifmsv_size_186 = 6400;
+uint32_t kernel_iter_186 = 9;
+bool has_l1_write_access_pattern_186 = false;
+std::vector<access_pattern> l1_write_pattern_186 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_186 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_186 = 0;
+bool has_l1_wts_write_access_pattern_186 = false;
+std::vector<access_pattern> l1_wts_write_pattern_186 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_186 = {};
+
+
+std::vector<uint32_t> ofm_dim_186 = {8, 20, 120, 12};
+std::vector<uint32_t> ofm_bound_186 = {8, 20, 120, 12};
+std::vector<uint32_t> ofmsv_dim_186 = {8, 20, 10, 1};
+uint32_t ofmsv_size_186 = 1600;
+uint32_t ofm_repetition_186 = 1;
+bool has_l1_read_access_pattern_186 = false;
+
+std::vector<access_pattern> l1_read_pattern_186 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_186 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 187
+// LayerName: Div_306
+std::vector<uint32_t> ifm_dim_187 = {8, 20, 120, 12};
+std::vector<uint32_t> ifm_bound_187 = {8, 20, 120, 12};
+std::vector<uint32_t> ifmsv_dim_187 = {8, 20, 10, 1};
+uint32_t ifmsv_size_187 = 6400;
+uint32_t kernel_iter_187 = 9;
+bool has_l1_write_access_pattern_187 = false;
+std::vector<access_pattern> l1_write_pattern_187 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_187 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_187 = 0;
+bool has_l1_wts_write_access_pattern_187 = false;
+std::vector<access_pattern> l1_wts_write_pattern_187 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_187 = {};
+
+
+std::vector<uint32_t> ofm_dim_187 = {8, 20, 120, 12};
+std::vector<uint32_t> ofm_bound_187 = {8, 20, 120, 12};
+std::vector<uint32_t> ofmsv_dim_187 = {8, 20, 10, 1};
+uint32_t ofmsv_size_187 = 1600;
+uint32_t ofm_repetition_187 = 1;
+bool has_l1_read_access_pattern_187 = false;
+
+std::vector<access_pattern> l1_read_pattern_187 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_187 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 188
+// LayerName: Mul_307
+std::vector<uint32_t> ifm_dim_188 = {8, 20, 120, 6};
+std::vector<uint32_t> ifm_bound_188 = {8, 20, 120, 6};
+std::vector<uint32_t> ifmsv_dim_188 = {8, 20, 3, 2};
+uint32_t ifmsv_size_188 = 3840;
+uint32_t kernel_iter_188 = 20;
+bool has_l1_write_access_pattern_188 = false;
+std::vector<access_pattern> l1_write_pattern_188 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_188 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_188 = {8, 20, 120, 6};
+std::vector<uint32_t> ifm2_bound_188 = {8, 20, 120, 6};
+std::vector<uint32_t> ifm2sv_dim_188 = {8, 20, 3, 2};
+uint32_t ifm2sv_size_188 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_188 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_188 = 0;
+bool has_l1_wts_write_access_pattern_188 = false;
+std::vector<access_pattern> l1_wts_write_pattern_188 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_188 = {};
+
+
+std::vector<uint32_t> ofm_dim_188 = {8, 20, 120, 8};
+std::vector<uint32_t> ofm_bound_188 = {8, 20, 120, 6};
+std::vector<uint32_t> ofmsv_dim_188 = {8, 20, 3, 2};
+uint32_t ofmsv_size_188 = 960;
+uint32_t ofm_repetition_188 = 1;
+bool has_l1_read_access_pattern_188 = false;
+
+std::vector<access_pattern> l1_read_pattern_188 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_188 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 9, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 3, 2}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 6, 2}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 9, 2}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 3, 4}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 6, 4}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 9, 4}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 3, 6}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 9, 6}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 189
+// LayerName: Conv_308
+std::vector<uint32_t> ifm_dim_189 = {8, 20, 120, 12};
+std::vector<uint32_t> ifm_bound_189 = {8, 20, 120, 12};
+std::vector<uint32_t> ifmsv_dim_189 = {8, 16, 1, 10};
+uint32_t ifmsv_size_189 = 5120;
+uint32_t kernel_iter_189 = 180;
+bool has_l1_write_access_pattern_189 = false;
+std::vector<access_pattern> l1_write_pattern_189 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_189 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 16, 1, 10}, .offset = {0, -4, 0, -4}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 120}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 16, 1, 10}, .offset = {0, -4, 0, -2}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 120}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 16, 1, 10}, .offset = {0, -4, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 120}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 16, 1, 10}, .offset = {0, -4, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 120}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_189 = {107520};
+std::vector<uint32_t> wts_dim_189 = {107520};
+std::vector<uint32_t> wtssv_dim_189 = {896};
+uint32_t wts_repetition_189 = 1;
+uint32_t wtssv_size_189 = 896;
+bool has_l1_wts_write_access_pattern_189 = false;
+std::vector<access_pattern> l1_wts_write_pattern_189 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_189 = {
+{
+  tiling({.buffer_dimension = {107520}, .tiling_dimension = {896}, .offset = {0}, .tile_traversal = { {.dimension = 0, .stride = 3584, .wrap = 30} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {107520}, .tiling_dimension = {896}, .offset = {896}, .tile_traversal = { {.dimension = 0, .stride = 3584, .wrap = 30} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {107520}, .tiling_dimension = {896}, .offset = {1792}, .tile_traversal = { {.dimension = 0, .stride = 3584, .wrap = 30} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {107520}, .tiling_dimension = {896}, .offset = {2688}, .tile_traversal = { {.dimension = 0, .stride = 3584, .wrap = 30} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_189[] = {
+{
+  tiling({.buffer_dimension = {107520, 1}, .tiling_dimension = {53760, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {107520, 1}, .tiling_dimension = {53760, 1}, .offset = {53760, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_189[] = {
+{
+  tiling({.buffer_dimension = {107520}, .tiling_dimension = {53760}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {107520}, .tiling_dimension = {53760}, .offset = {53760}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_189 = {8, 24, 120, 16};
+std::vector<uint32_t> ofm_bound_189 = {8, 20, 120, 12};
+std::vector<uint32_t> ofmsv_dim_189 = {8, 8, 1, 2};
+uint32_t ofmsv_size_189 = 128;
+uint32_t ofm_repetition_189 = 1;
+bool has_l1_read_access_pattern_189 = false;
+
+std::vector<access_pattern> l1_read_pattern_189 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_189 = {
+{
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 1, 2}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 2, 2}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 3, 2}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 1, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 2, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 3, 4}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 1, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 8, 1, 2}, .offset = {0, 0, 3, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 30}, {.dimension = 1, .stride = 8, .wrap = 3}, {.dimension = 3, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 190
+// LayerName: Add_310
+std::vector<uint32_t> ifm_dim_190 = {8, 24, 120, 16};
+std::vector<uint32_t> ifm_bound_190 = {8, 20, 120, 12};
+std::vector<uint32_t> ifmsv_dim_190 = {8, 20, 10, 1};
+uint32_t ifmsv_size_190 = 6400;
+uint32_t kernel_iter_190 = 9;
+bool has_l1_write_access_pattern_190 = false;
+std::vector<access_pattern> l1_write_pattern_190 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_190 = {
+{
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 24, 120, 16}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_190 = 0;
+bool has_l1_wts_write_access_pattern_190 = false;
+std::vector<access_pattern> l1_wts_write_pattern_190 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_190 = {};
+
+
+std::vector<uint32_t> ofm_dim_190 = {8, 20, 120, 12};
+std::vector<uint32_t> ofm_bound_190 = {8, 20, 120, 12};
+std::vector<uint32_t> ofmsv_dim_190 = {8, 20, 10, 1};
+uint32_t ofmsv_size_190 = 1600;
+uint32_t ofm_repetition_190 = 1;
+bool has_l1_read_access_pattern_190 = false;
+
+std::vector<access_pattern> l1_read_pattern_190 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_190 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 191
+// LayerName: Clip_313
+std::vector<uint32_t> ifm_dim_191 = {8, 20, 120, 12};
+std::vector<uint32_t> ifm_bound_191 = {8, 20, 120, 12};
+std::vector<uint32_t> ifmsv_dim_191 = {8, 20, 10, 1};
+uint32_t ifmsv_size_191 = 6400;
+uint32_t kernel_iter_191 = 9;
+bool has_l1_write_access_pattern_191 = false;
+std::vector<access_pattern> l1_write_pattern_191 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_191 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_191 = 0;
+bool has_l1_wts_write_access_pattern_191 = false;
+std::vector<access_pattern> l1_wts_write_pattern_191 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_191 = {};
+
+
+std::vector<uint32_t> ofm_dim_191 = {8, 20, 120, 12};
+std::vector<uint32_t> ofm_bound_191 = {8, 20, 120, 12};
+std::vector<uint32_t> ofmsv_dim_191 = {8, 20, 10, 1};
+uint32_t ofmsv_size_191 = 1600;
+uint32_t ofm_repetition_191 = 1;
+bool has_l1_read_access_pattern_191 = false;
+
+std::vector<access_pattern> l1_read_pattern_191 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_191 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 192
+// LayerName: Div_315
+std::vector<uint32_t> ifm_dim_192 = {8, 20, 120, 12};
+std::vector<uint32_t> ifm_bound_192 = {8, 20, 120, 12};
+std::vector<uint32_t> ifmsv_dim_192 = {8, 20, 10, 1};
+uint32_t ifmsv_size_192 = 6400;
+uint32_t kernel_iter_192 = 9;
+bool has_l1_write_access_pattern_192 = false;
+std::vector<access_pattern> l1_write_pattern_192 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_192 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_192 = 0;
+bool has_l1_wts_write_access_pattern_192 = false;
+std::vector<access_pattern> l1_wts_write_pattern_192 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_192 = {};
+
+
+std::vector<uint32_t> ofm_dim_192 = {8, 20, 120, 12};
+std::vector<uint32_t> ofm_bound_192 = {8, 20, 120, 12};
+std::vector<uint32_t> ofmsv_dim_192 = {8, 20, 10, 1};
+uint32_t ofmsv_size_192 = 1600;
+uint32_t ofm_repetition_192 = 1;
+bool has_l1_read_access_pattern_192 = false;
+
+std::vector<access_pattern> l1_read_pattern_192 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_192 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 193
+// LayerName: Mul_316
+std::vector<uint32_t> ifm_dim_193 = {8, 20, 120, 6};
+std::vector<uint32_t> ifm_bound_193 = {8, 20, 120, 6};
+std::vector<uint32_t> ifmsv_dim_193 = {8, 20, 3, 2};
+uint32_t ifmsv_size_193 = 3840;
+uint32_t kernel_iter_193 = 20;
+bool has_l1_write_access_pattern_193 = false;
+std::vector<access_pattern> l1_write_pattern_193 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_193 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_193 = {8, 20, 120, 6};
+std::vector<uint32_t> ifm2_bound_193 = {8, 20, 120, 6};
+std::vector<uint32_t> ifm2sv_dim_193 = {8, 20, 3, 2};
+uint32_t ifm2sv_size_193 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_193 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_193 = 0;
+bool has_l1_wts_write_access_pattern_193 = false;
+std::vector<access_pattern> l1_wts_write_pattern_193 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_193 = {};
+
+
+std::vector<uint32_t> ofm_dim_193 = {8, 20, 120, 8};
+std::vector<uint32_t> ofm_bound_193 = {8, 20, 120, 6};
+std::vector<uint32_t> ofmsv_dim_193 = {8, 20, 3, 2};
+uint32_t ofmsv_size_193 = 960;
+uint32_t ofm_repetition_193 = 1;
+bool has_l1_read_access_pattern_193 = false;
+
+std::vector<access_pattern> l1_read_pattern_193 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_193 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 9, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 3, 2}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 6, 2}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 9, 2}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 3, 4}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 6, 4}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 9, 4}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 3, 6}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 9, 6}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 195
+// LayerName: Generated-#50
+std::vector<uint32_t> ifm_dim_195 = {8, 240, 120, 1};
+std::vector<uint32_t> ifm_bound_195 = {8, 240, 120, 1};
+std::vector<uint32_t> ifmsv_dim_195 = {8, 48, 5, 1};
+uint32_t ifmsv_size_195 = 7680;
+uint32_t kernel_iter_195 = 30;
+bool has_l1_write_access_pattern_195 = false;
+std::vector<access_pattern> l1_write_pattern_195 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_195 = {
+{
+  tiling({.buffer_dimension = {8, 240, 120, 1}, .tiling_dimension = {8, 48, 5, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 5, .wrap = 4}, {.dimension = 1, .stride = 48, .wrap = 5}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 240, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 240, 120, 1}, .tiling_dimension = {8, 48, 5, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 5, .wrap = 4}, {.dimension = 1, .stride = 48, .wrap = 5}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 240, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 240, 120, 1}, .tiling_dimension = {8, 48, 5, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 5, .wrap = 4}, {.dimension = 1, .stride = 48, .wrap = 5}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 240, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 240, 120, 1}, .tiling_dimension = {8, 48, 5, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 5, .wrap = 4}, {.dimension = 1, .stride = 48, .wrap = 5}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 240, 120, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_195 = 0;
+bool has_l1_wts_write_access_pattern_195 = false;
+std::vector<access_pattern> l1_wts_write_pattern_195 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_195 = {};
+
+
+std::vector<uint32_t> ofm_dim_195 = {8, 1, 120, 4};
+std::vector<uint32_t> ofm_bound_195 = {8, 1, 120, 1};
+std::vector<uint32_t> ofmsv_dim_195 = {8, 1, 5, 1};
+uint32_t ofmsv_size_195 = 40;
+uint32_t ofm_repetition_195 = 5;
+bool has_l1_read_access_pattern_195 = false;
+std::vector<access_pattern> l1_read_pattern_195 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ofm_pattern_195 = {
+{
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 5, 0}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 10, 0}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 15, 0}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 5, 1}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 10, 1}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 15, 1}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 5, 2}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 10, 2}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 15, 2}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 5, 3}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 10, 3}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 15, 3}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 196
+// LayerName: Conv_318
+std::vector<uint32_t> ifm_dim_196 = {8, 1, 120, 4};
+std::vector<uint32_t> ifm_bound_196 = {8, 1, 120, 1};
+std::vector<uint32_t> ifmsv_dim_196 = {8, 16, 24, 1};
+uint32_t ifmsv_size_196 = 3072;
+uint32_t kernel_iter_196 = 20;
+bool has_l1_write_access_pattern_196 = false;
+std::vector<access_pattern> l1_write_pattern_196 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_196 = {
+{
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 16, 24, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = -1, .repetition = 4, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 16, 24, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = -1, .repetition = 4, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 16, 24, 1}, .offset = {0, 32, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = -1, .repetition = 4, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 16, 24, 1}, .offset = {0, 48, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = -1, .repetition = 4, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_196 = {250880};
+std::vector<uint32_t> wts_dim_196 = {250880};
+std::vector<uint32_t> wtssv_dim_196 = {3136};
+uint32_t wtssv_size_196 = 3136;
+uint32_t wts_repetition_196 = 1;
+bool has_l1_wts_write_access_pattern_196 = false;
+std::vector<access_pattern> l1_wts_write_pattern_196 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_196 = {
+{
+  tiling({.buffer_dimension = {15680, 16}, .tiling_dimension = {3136, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 3136, .wrap = 5}, {.dimension = 1, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {15680, 16}, .tiling_dimension = {3136, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 3136, .wrap = 5}, {.dimension = 1, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {15680, 16}, .tiling_dimension = {3136, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 3136, .wrap = 5}, {.dimension = 1, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {15680, 16}, .tiling_dimension = {3136, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 3136, .wrap = 5}, {.dimension = 1, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_196[] = {
+{
+  tiling({.buffer_dimension = {250880, 1}, .tiling_dimension = {125440, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {250880, 1}, .tiling_dimension = {125440, 1}, .offset = {125440, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_196[] = {
+{
+  tiling({.buffer_dimension = {250880}, .tiling_dimension = {125440}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {250880}, .tiling_dimension = {125440}, .offset = {125440}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_196 = {8, 64, 32, 1};
+std::vector<uint32_t> ofm_bound_196 = {8, 1, 30, 1};
+std::vector<uint32_t> ofmsv_dim_196 = {8, 16, 2, 1};
+uint32_t ofmsv_size_196 = 256;
+uint32_t ofm_repetition_196 = 5;
+bool has_l1_read_access_pattern_196 = false;
+
+std::vector<access_pattern> l1_read_pattern_196 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_196 = {
+{
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 197
+// LayerName: Conv_320
+std::vector<uint32_t> ifm_dim_197 = {8, 64, 32, 1};
+std::vector<uint32_t> ifm_bound_197 = {8, 1, 30, 1};
+std::vector<uint32_t> ifmsv_dim_197 = {8, 8, 10, 1};
+uint32_t ifmsv_size_197 = 640;
+uint32_t kernel_iter_197 = 15;
+bool has_l1_write_access_pattern_197 = false;
+std::vector<access_pattern> l1_write_pattern_197 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_197 = {
+{
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 8, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 3} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {8, 1, 30, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 8, 10, 1}, .offset = {0, 8, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 3} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {8, 1, 30, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 8, 10, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 3} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {8, 1, 30, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 32, 1}, .tiling_dimension = {8, 8, 10, 1}, .offset = {0, 24, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 3} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {8, 1, 30, 1}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_197 = {241920};
+std::vector<uint32_t> wts_dim_197 = {241920};
+std::vector<uint32_t> wtssv_dim_197 = {4032};
+uint32_t wtssv_size_197 = 4032;
+uint32_t wts_repetition_197 = 1;
+bool has_l1_wts_write_access_pattern_197 = false;
+std::vector<access_pattern> l1_wts_write_pattern_197 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_197 = {
+{
+  tiling({.buffer_dimension = {12096, 20}, .tiling_dimension = {4032, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 4032, .wrap = 3}, {.dimension = 1, .stride = 4, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {12096, 20}, .tiling_dimension = {4032, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 4032, .wrap = 3}, {.dimension = 1, .stride = 4, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {12096, 20}, .tiling_dimension = {4032, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 4032, .wrap = 3}, {.dimension = 1, .stride = 4, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {12096, 20}, .tiling_dimension = {4032, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 4032, .wrap = 3}, {.dimension = 1, .stride = 4, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_197[] = {
+{
+  tiling({.buffer_dimension = {241920, 1}, .tiling_dimension = {120960, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {241920, 1}, .tiling_dimension = {120960, 1}, .offset = {120960, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_197[] = {
+{
+  tiling({.buffer_dimension = {241920}, .tiling_dimension = {120960}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {241920}, .tiling_dimension = {120960}, .offset = {120960}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_197 = {8, 32, 120, 1};
+std::vector<uint32_t> ofm_bound_197 = {8, 1, 120, 1};
+std::vector<uint32_t> ofmsv_dim_197 = {8, 8, 6, 1};
+uint32_t ofmsv_size_197 = 384;
+uint32_t ofm_repetition_197 = 3;
+bool has_l1_read_access_pattern_197 = false;
+
+std::vector<access_pattern> l1_read_pattern_197 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_197 = {
+{
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 0, 12, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 0, 18, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 8, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 8, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 8, 12, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 8, 18, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 16, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 16, 12, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 16, 18, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 24, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 24, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 24, 12, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 8, 6, 1}, .offset = {0, 24, 18, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 198
+// LayerName: Add_322
+std::vector<uint32_t> ifm_dim_198 = {8, 32, 120, 1};
+std::vector<uint32_t> ifm_bound_198 = {8, 1, 120, 1};
+std::vector<uint32_t> ifmsv_dim_198 = {8, 1, 48, 1};
+uint32_t ifmsv_size_198 = 1536;
+uint32_t kernel_iter_198 = 1;
+bool has_l1_write_access_pattern_198 = false;
+std::vector<access_pattern> l1_write_pattern_198 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_198 = {
+{
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 48, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 48, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 48, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 1}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 48, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_198 = 0;
+bool has_l1_wts_write_access_pattern_198 = false;
+std::vector<access_pattern> l1_wts_write_pattern_198 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_198 = {};
+
+
+std::vector<uint32_t> ofm_dim_198 = {8, 1, 192, 4};
+std::vector<uint32_t> ofm_bound_198 = {8, 1, 120, 1};
+std::vector<uint32_t> ofmsv_dim_198 = {8, 1, 48, 1};
+uint32_t ofmsv_size_198 = 384;
+uint32_t ofm_repetition_198 = 1;
+bool has_l1_read_access_pattern_198 = false;
+
+std::vector<access_pattern> l1_read_pattern_198 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_198 = {
+{
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 48, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 96, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 144, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 48, 1}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 96, 1}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 144, 1}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 48, 2}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 96, 2}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 144, 2}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 48, 3}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 96, 3}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 48, 1}, .offset = {0, 0, 144, 3}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 199
+// LayerName: Clip_325
+std::vector<uint32_t> ifm_dim_199 = {8, 1, 192, 4};
+std::vector<uint32_t> ifm_bound_199 = {8, 1, 120, 1};
+std::vector<uint32_t> ifmsv_dim_199 = {8, 1, 32, 1};
+uint32_t ifmsv_size_199 = 1024;
+uint32_t kernel_iter_199 = 1;
+bool has_l1_write_access_pattern_199 = false;
+std::vector<access_pattern> l1_write_pattern_199 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_199 = {
+{
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 192, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_199 = 0;
+bool has_l1_wts_write_access_pattern_199 = false;
+std::vector<access_pattern> l1_wts_write_pattern_199 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_199 = {};
+
+
+std::vector<uint32_t> ofm_dim_199 = {8, 1, 128, 4};
+std::vector<uint32_t> ofm_bound_199 = {8, 1, 120, 1};
+std::vector<uint32_t> ofmsv_dim_199 = {8, 1, 32, 1};
+uint32_t ofmsv_size_199 = 256;
+uint32_t ofm_repetition_199 = 1;
+bool has_l1_read_access_pattern_199 = false;
+
+std::vector<access_pattern> l1_read_pattern_199 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_199 = {
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 32, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 64, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 96, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 32, 1}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 64, 1}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 96, 1}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 32, 2}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 64, 2}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 96, 2}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 32, 3}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 64, 3}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 1}, .offset = {0, 0, 96, 3}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 200
+// LayerName: Div_327
+std::vector<uint32_t> ifm_dim_200 = {8, 1, 128, 4};
+std::vector<uint32_t> ifm_bound_200 = {8, 1, 120, 1};
+std::vector<uint32_t> ifmsv_dim_200 = {8, 1, 32, 2};
+uint32_t ifmsv_size_200 = 2048;
+uint32_t kernel_iter_200 = 1;
+bool has_l1_write_access_pattern_200 = false;
+std::vector<access_pattern> l1_write_pattern_200 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_200 = {
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 4}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 32, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_200 = 0;
+bool has_l1_wts_write_access_pattern_200 = false;
+std::vector<access_pattern> l1_wts_write_pattern_200 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_200 = {};
+
+
+std::vector<uint32_t> ofm_dim_200 = {8, 1, 128, 8};
+std::vector<uint32_t> ofm_bound_200 = {8, 1, 120, 1};
+std::vector<uint32_t> ofmsv_dim_200 = {8, 1, 32, 2};
+uint32_t ofmsv_size_200 = 512;
+uint32_t ofm_repetition_200 = 1;
+bool has_l1_read_access_pattern_200 = false;
+
+std::vector<access_pattern> l1_read_pattern_200 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_200 = {
+{
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 32, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 64, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 96, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 32, 2}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 64, 2}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 96, 2}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 32, 4}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 64, 4}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 96, 4}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 32, 6}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 64, 6}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 128, 8}, .tiling_dimension = {8, 1, 32, 2}, .offset = {0, 0, 96, 6}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 202
+// LayerName: Mul_328
+std::vector<uint32_t> ifm_dim_202 = {8, 20, 120, 12};
+std::vector<uint32_t> ifm_bound_202 = {8, 20, 120, 12};
+std::vector<uint32_t> ifmsv_dim_202 = {8, 20, 2, 3};
+uint32_t ifmsv_size_202 = 3840;
+uint32_t kernel_iter_202 = 15;
+bool has_l1_write_access_pattern_202 = false;
+std::vector<access_pattern> l1_write_pattern_202 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_202 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 60} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 60} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 60} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 60} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_202 = {8, 20, 120, 12};
+std::vector<uint32_t> ifm2_bound_202 = {8, 20, 120, 12};
+std::vector<uint32_t> ifm2sv_dim_202 = {8, 20, 2, 3};
+uint32_t ifm2sv_size_202 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_202 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 60} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 60} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 60} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 60} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_202 = 0;
+bool has_l1_wts_write_access_pattern_202 = false;
+std::vector<access_pattern> l1_wts_write_pattern_202 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_202 = {};
+
+
+std::vector<uint32_t> ofm_dim_202 = {8, 20, 120, 12};
+std::vector<uint32_t> ofm_bound_202 = {8, 20, 120, 12};
+std::vector<uint32_t> ofmsv_dim_202 = {8, 20, 2, 3};
+uint32_t ofmsv_size_202 = 960;
+uint32_t ofm_repetition_202 = 1;
+bool has_l1_read_access_pattern_202 = false;
+
+std::vector<access_pattern> l1_read_pattern_202 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_202 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 15} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 203
+// LayerName: Conv_329
+std::vector<uint32_t> ifm_dim_203 = {8, 20, 120, 12};
+std::vector<uint32_t> ifm_bound_203 = {8, 20, 120, 12};
+std::vector<uint32_t> ifmsv_dim_203 = {8, 32, 14, 1};
+uint32_t ifmsv_size_203 = 3584;
+uint32_t kernel_iter_203 = 54;
+bool has_l1_write_access_pattern_203 = false;
+std::vector<access_pattern> l1_write_pattern_203 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_203 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 32, 14, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 14, .wrap = 9}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 32, 14, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 14, .wrap = 9}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 32, 14, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 14, .wrap = 9}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 32, 14, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 14, .wrap = 9}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_203 = {8, 32, 24, 12};
+std::vector<uint32_t> ifm2_bound_203 = {8, 20, 20, 12};
+std::vector<uint32_t> ifm2sv_dim_203 = {8, 32, 3, 1};
+uint32_t ifm2sv_size_203 = 3072;
+std::vector<std::vector<access_pattern>> ifm2_pattern_203 = {
+{
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 20, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 20, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 20, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 20, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_203 = {200448};
+std::vector<uint32_t> wts_dim_203 = {200448};
+std::vector<uint32_t> wtssv_dim_203 = {2784};
+uint32_t wtssv_size_203 = 2784;
+uint32_t wts_repetition_203 = 1;
+bool has_l1_wts_write_access_pattern_203 = false;
+std::vector<access_pattern> l1_wts_write_pattern_203 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_203 = {
+{
+  tiling({.buffer_dimension = {25056, 8}, .tiling_dimension = {2784, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 2784, .wrap = 9} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {25056, 8}, .tiling_dimension = {2784, 1}, .offset = {0, 4}, .tile_traversal = { {.dimension = 0, .stride = 2784, .wrap = 9} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {25056, 8}, .tiling_dimension = {2784, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 2784, .wrap = 9} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {25056, 8}, .tiling_dimension = {2784, 1}, .offset = {0, 5}, .tile_traversal = { {.dimension = 0, .stride = 2784, .wrap = 9} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {25056, 8}, .tiling_dimension = {2784, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 2784, .wrap = 9} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {25056, 8}, .tiling_dimension = {2784, 1}, .offset = {0, 6}, .tile_traversal = { {.dimension = 0, .stride = 2784, .wrap = 9} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {25056, 8}, .tiling_dimension = {2784, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 2784, .wrap = 9} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {25056, 8}, .tiling_dimension = {2784, 1}, .offset = {0, 7}, .tile_traversal = { {.dimension = 0, .stride = 2784, .wrap = 9} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_203[] = {
+{
+  tiling({.buffer_dimension = {200448, 1}, .tiling_dimension = {100224, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {200448, 1}, .tiling_dimension = {100224, 1}, .offset = {100224, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_203[] = {
+{
+  tiling({.buffer_dimension = {200448}, .tiling_dimension = {100224}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {200448}, .tiling_dimension = {100224}, .offset = {100224}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_203 = {8, 32, 24, 12};
+std::vector<uint32_t> ofm_bound_203 = {8, 20, 20, 12};
+std::vector<uint32_t> ofmsv_dim_203 = {8, 32, 3, 1};
+uint32_t ofmsv_size_203 = 768;
+uint32_t ofm_repetition_203 = 9;
+bool has_l1_read_access_pattern_203 = false;
+
+std::vector<access_pattern> l1_read_pattern_203 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_203 = {
+{
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 9, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 3, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 6, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 9, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 3, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 6, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 9, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 3, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 32, 3, 1}, .offset = {0, 0, 9, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 12, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 204
+// LayerName: Conv_331
+std::vector<uint32_t> ifm_dim_204 = {8, 32, 24, 12};
+std::vector<uint32_t> ifm_bound_204 = {8, 20, 20, 12};
+std::vector<uint32_t> ifmsv_dim_204 = {8, 32, 10, 1};
+uint32_t ifmsv_size_204 = 2560;
+uint32_t kernel_iter_204 = 36;
+bool has_l1_write_access_pattern_204 = true;
+std::vector<access_pattern> l1_write_pattern_204 = {tiling({.buffer_dimension = {8, 32, 10, 1}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_204 = {
+{
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {8, 20, 20, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {8, 20, 20, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {8, 20, 20, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 24, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 2}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 6, .boundary_dimension = {8, 20, 20, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_204 = {161280};
+std::vector<uint32_t> wts_dim_204 = {161280};
+std::vector<uint32_t> wtssv_dim_204 = {3360};
+uint32_t wtssv_size_204 = 3360;
+uint32_t wts_repetition_204 = 1;
+bool has_l1_wts_write_access_pattern_204 = false;
+std::vector<access_pattern> l1_wts_write_pattern_204 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_204 = {
+{
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 4}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 8}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 12}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 16}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 20}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 5}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 9}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 13}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 17}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 21}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 6}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 10}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 14}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 18}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 22}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 7}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 11}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 15}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 19}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {6720, 24}, .tiling_dimension = {3360, 1}, .offset = {0, 23}, .tile_traversal = { {.dimension = 0, .stride = 3360, .wrap = 2} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_204[] = {
+{
+  tiling({.buffer_dimension = {161280, 1}, .tiling_dimension = {80640, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {161280, 1}, .tiling_dimension = {80640, 1}, .offset = {80640, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_204[] = {
+{
+  tiling({.buffer_dimension = {161280}, .tiling_dimension = {80640}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {161280}, .tiling_dimension = {80640}, .offset = {80640}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_204 = {8, 32, 120, 12};
+std::vector<uint32_t> ofm_bound_204 = {8, 20, 120, 12};
+std::vector<uint32_t> ofmsv_dim_204 = {8, 32, 5, 1};
+uint32_t ofmsv_size_204 = 1280;
+uint32_t ofm_repetition_204 = 2;
+bool has_l1_read_access_pattern_204 = false;
+
+std::vector<access_pattern> l1_read_pattern_204 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_204 = {
+{
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 5, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 10, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 15, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 5, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 10, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 15, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 5, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 10, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 15, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 5, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 10, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 32, 5, 1}, .offset = {0, 0, 15, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 205
+// LayerName: Add_333
+std::vector<uint32_t> ifm_dim_205 = {8, 32, 120, 12};
+std::vector<uint32_t> ifm_bound_205 = {8, 20, 120, 12};
+std::vector<uint32_t> ifmsv_dim_205 = {8, 20, 10, 1};
+uint32_t ifmsv_size_205 = 6400;
+uint32_t kernel_iter_205 = 9;
+bool has_l1_write_access_pattern_205 = false;
+std::vector<access_pattern> l1_write_pattern_205 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_205 = {
+{
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_205 = 0;
+bool has_l1_wts_write_access_pattern_205 = false;
+std::vector<access_pattern> l1_wts_write_pattern_205 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_205 = {};
+
+
+std::vector<uint32_t> ofm_dim_205 = {8, 20, 120, 12};
+std::vector<uint32_t> ofm_bound_205 = {8, 20, 120, 12};
+std::vector<uint32_t> ofmsv_dim_205 = {8, 20, 10, 1};
+uint32_t ofmsv_size_205 = 1600;
+uint32_t ofm_repetition_205 = 1;
+bool has_l1_read_access_pattern_205 = false;
+
+std::vector<access_pattern> l1_read_pattern_205 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_205 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 206
+// LayerName: Clip_336
+std::vector<uint32_t> ifm_dim_206 = {8, 20, 120, 12};
+std::vector<uint32_t> ifm_bound_206 = {8, 20, 120, 12};
+std::vector<uint32_t> ifmsv_dim_206 = {8, 20, 10, 1};
+uint32_t ifmsv_size_206 = 6400;
+uint32_t kernel_iter_206 = 9;
+bool has_l1_write_access_pattern_206 = false;
+std::vector<access_pattern> l1_write_pattern_206 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_206 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_206 = 0;
+bool has_l1_wts_write_access_pattern_206 = false;
+std::vector<access_pattern> l1_wts_write_pattern_206 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_206 = {};
+
+
+std::vector<uint32_t> ofm_dim_206 = {8, 20, 120, 12};
+std::vector<uint32_t> ofm_bound_206 = {8, 20, 120, 12};
+std::vector<uint32_t> ofmsv_dim_206 = {8, 20, 10, 1};
+uint32_t ofmsv_size_206 = 1600;
+uint32_t ofm_repetition_206 = 1;
+bool has_l1_read_access_pattern_206 = false;
+
+std::vector<access_pattern> l1_read_pattern_206 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_206 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 207
+// LayerName: Div_338
+std::vector<uint32_t> ifm_dim_207 = {8, 20, 120, 12};
+std::vector<uint32_t> ifm_bound_207 = {8, 20, 120, 12};
+std::vector<uint32_t> ifmsv_dim_207 = {8, 20, 10, 1};
+uint32_t ifmsv_size_207 = 6400;
+uint32_t kernel_iter_207 = 9;
+bool has_l1_write_access_pattern_207 = false;
+std::vector<access_pattern> l1_write_pattern_207 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_207 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 10, .wrap = 12}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_207 = 0;
+bool has_l1_wts_write_access_pattern_207 = false;
+std::vector<access_pattern> l1_wts_write_pattern_207 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_207 = {};
+
+
+std::vector<uint32_t> ofm_dim_207 = {8, 20, 120, 12};
+std::vector<uint32_t> ofm_bound_207 = {8, 20, 120, 12};
+std::vector<uint32_t> ofmsv_dim_207 = {8, 20, 10, 1};
+uint32_t ofmsv_size_207 = 1600;
+uint32_t ofm_repetition_207 = 1;
+bool has_l1_read_access_pattern_207 = false;
+
+std::vector<access_pattern> l1_read_pattern_207 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_207 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 0}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 1}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 2}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 10, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 20, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 20, 10, 1}, .offset = {0, 0, 30, 3}, .tile_traversal = { {.dimension = 2, .stride = 40, .wrap = 3}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 208
+// LayerName: Mul_339
+std::vector<uint32_t> ifm_dim_208 = {8, 20, 120, 6};
+std::vector<uint32_t> ifm_bound_208 = {8, 20, 120, 6};
+std::vector<uint32_t> ifmsv_dim_208 = {8, 20, 3, 2};
+uint32_t ifmsv_size_208 = 3840;
+uint32_t kernel_iter_208 = 20;
+bool has_l1_write_access_pattern_208 = false;
+std::vector<access_pattern> l1_write_pattern_208 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_208 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_208 = {8, 20, 120, 6};
+std::vector<uint32_t> ifm2_bound_208 = {8, 20, 120, 6};
+std::vector<uint32_t> ifm2sv_dim_208 = {8, 20, 3, 2};
+uint32_t ifm2sv_size_208 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_208 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 6}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 40} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_208 = 0;
+bool has_l1_wts_write_access_pattern_208 = false;
+std::vector<access_pattern> l1_wts_write_pattern_208 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_208 = {};
+
+
+std::vector<uint32_t> ofm_dim_208 = {8, 20, 120, 8};
+std::vector<uint32_t> ofm_bound_208 = {8, 20, 120, 6};
+std::vector<uint32_t> ofmsv_dim_208 = {8, 20, 3, 2};
+uint32_t ofmsv_size_208 = 960;
+uint32_t ofm_repetition_208 = 1;
+bool has_l1_read_access_pattern_208 = false;
+
+std::vector<access_pattern> l1_read_pattern_208 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_208 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 9, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 3, 2}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 6, 2}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 9, 2}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 3, 4}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 6, 4}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 9, 4}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 3, 6}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 120, 8}, .tiling_dimension = {8, 20, 3, 2}, .offset = {0, 0, 9, 6}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 210
+// LayerName: Generated-#56
+std::vector<uint32_t> ifm_dim_210 = {8, 240, 120, 1};
+std::vector<uint32_t> ifm_bound_210 = {8, 240, 120, 1};
+std::vector<uint32_t> ifmsv_dim_210 = {8, 48, 5, 1};
+uint32_t ifmsv_size_210 = 7680;
+uint32_t kernel_iter_210 = 30;
+bool has_l1_write_access_pattern_210 = false;
+std::vector<access_pattern> l1_write_pattern_210 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_210 = {
+{
+  tiling({.buffer_dimension = {8, 240, 120, 1}, .tiling_dimension = {8, 48, 5, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 5, .wrap = 4}, {.dimension = 1, .stride = 48, .wrap = 5}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 240, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 240, 120, 1}, .tiling_dimension = {8, 48, 5, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 5, .wrap = 4}, {.dimension = 1, .stride = 48, .wrap = 5}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 240, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 240, 120, 1}, .tiling_dimension = {8, 48, 5, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 5, .wrap = 4}, {.dimension = 1, .stride = 48, .wrap = 5}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 240, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 240, 120, 1}, .tiling_dimension = {8, 48, 5, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 5, .wrap = 4}, {.dimension = 1, .stride = 48, .wrap = 5}, {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 240, 120, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_210 = 0;
+bool has_l1_wts_write_access_pattern_210 = false;
+std::vector<access_pattern> l1_wts_write_pattern_210 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_210 = {};
+
+
+std::vector<uint32_t> ofm_dim_210 = {8, 1, 120, 4};
+std::vector<uint32_t> ofm_bound_210 = {8, 1, 120, 1};
+std::vector<uint32_t> ofmsv_dim_210 = {8, 1, 5, 1};
+uint32_t ofmsv_size_210 = 40;
+uint32_t ofm_repetition_210 = 5;
+bool has_l1_read_access_pattern_210 = false;
+std::vector<access_pattern> l1_read_pattern_210 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ofm_pattern_210 = {
+{
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 5, 0}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 10, 0}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 15, 0}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 5, 1}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 10, 1}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 15, 1}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 5, 2}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 10, 2}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 15, 2}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 5, 3}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 10, 3}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 1, 5, 1}, .offset = {0, 0, 15, 3}, .tile_traversal = { {.dimension = 2, .stride = 20, .wrap = 6} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 211
+// LayerName: Conv_343
+std::vector<uint32_t> ifm_dim_211 = {8, 1, 120, 4};
+std::vector<uint32_t> ifm_bound_211 = {8, 1, 120, 1};
+std::vector<uint32_t> ifmsv_dim_211 = {8, 16, 24, 1};
+uint32_t ifmsv_size_211 = 3072;
+uint32_t kernel_iter_211 = 10;
+bool has_l1_write_access_pattern_211 = false;
+std::vector<access_pattern> l1_write_pattern_211 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_211 = {
+{
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 16, 24, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 16, 24, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 16, 24, 1}, .offset = {0, 32, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 120, 4}, .tiling_dimension = {8, 16, 24, 1}, .offset = {0, 48, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 24, .wrap = 5} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 1, 120, 1}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_211 = {125440};
+std::vector<uint32_t> wts_dim_211 = {125440};
+std::vector<uint32_t> wtssv_dim_211 = {3136};
+uint32_t wtssv_size_211 = 3136;
+uint32_t wts_repetition_211 = 1;
+bool has_l1_wts_write_access_pattern_211 = false;
+std::vector<access_pattern> l1_wts_write_pattern_211 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_211 = {
+{
+  tiling({.buffer_dimension = {15680, 8}, .tiling_dimension = {3136, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 3136, .wrap = 5}, {.dimension = 1, .stride = 4, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {15680, 8}, .tiling_dimension = {3136, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 3136, .wrap = 5}, {.dimension = 1, .stride = 4, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {15680, 8}, .tiling_dimension = {3136, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 3136, .wrap = 5}, {.dimension = 1, .stride = 4, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {15680, 8}, .tiling_dimension = {3136, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 3136, .wrap = 5}, {.dimension = 1, .stride = 4, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_211[] = {
+{
+  tiling({.buffer_dimension = {125440, 1}, .tiling_dimension = {62720, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {125440, 1}, .tiling_dimension = {62720, 1}, .offset = {62720, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_211[] = {
+{
+  tiling({.buffer_dimension = {125440}, .tiling_dimension = {62720}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {125440}, .tiling_dimension = {62720}, .offset = {62720}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_211 = {8, 64, 16, 1};
+std::vector<uint32_t> ofm_bound_211 = {8, 1, 16, 1};
+std::vector<uint32_t> ofmsv_dim_211 = {8, 16, 2, 1};
+uint32_t ofmsv_size_211 = 256;
+uint32_t ofm_repetition_211 = 5;
+bool has_l1_read_access_pattern_211 = false;
+
+std::vector<access_pattern> l1_read_pattern_211 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_211 = {
+{
+  tiling({.buffer_dimension = {8, 64, 16, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 16, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 16, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 16, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 32, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 16, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 64, 16, 1}, .tiling_dimension = {8, 16, 2, 1}, .offset = {0, 48, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 212
+// LayerName: Sigmoid_344
+std::vector<uint32_t> ifm_dim_212 = {8, 64, 16, 1};
+std::vector<uint32_t> ifm_bound_212 = {8, 1, 16, 1};
+std::vector<uint32_t> ifmsv_dim_212 = {8, 1, 4, 16};
+uint32_t ifmsv_size_212 = 2048;
+uint32_t kernel_iter_212 = 1;
+bool has_l1_write_access_pattern_212 = false;
+std::vector<access_pattern> l1_write_pattern_212 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_212 = {
+{
+  tiling({.buffer_dimension = {8, 64, 16, 1}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 16, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 16, 1}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 16, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 16, 1}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 32}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 16, 1}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 64, 16, 1}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 48}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 1, 16, 1}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_212 = 0;
+bool has_l1_wts_write_access_pattern_212 = false;
+std::vector<access_pattern> l1_wts_write_pattern_212 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_212 = {};
+
+
+std::vector<uint32_t> ofm_dim_212 = {8, 1, 16, 64};
+std::vector<uint32_t> ofm_bound_212 = {8, 1, 16, 1};
+std::vector<uint32_t> ofmsv_dim_212 = {8, 1, 4, 16};
+uint32_t ofmsv_size_212 = 512;
+uint32_t ofm_repetition_212 = 1;
+bool has_l1_read_access_pattern_212 = false;
+
+std::vector<access_pattern> l1_read_pattern_212 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_212 = {
+{
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 16}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 4, 16}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 8, 16}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 12, 16}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 32}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 4, 32}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 8, 32}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 12, 32}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 0, 48}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 4, 48}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 8, 48}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 1, 16, 64}, .tiling_dimension = {8, 1, 4, 16}, .offset = {0, 0, 12, 48}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 214
+// LayerName: Conv_340
+std::vector<uint32_t> ifm_dim_214 = {8, 20, 120, 12};
+std::vector<uint32_t> ifm_bound_214 = {8, 20, 120, 12};
+std::vector<uint32_t> ifmsv_dim_214 = {8, 32, 12, 1};
+uint32_t ifmsv_size_214 = 3072;
+uint32_t kernel_iter_214 = 30;
+bool has_l1_write_access_pattern_214 = false;
+std::vector<access_pattern> l1_write_pattern_214 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_214 = {
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 32, 12, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 32, 12, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 32, 12, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 120, 12}, .tiling_dimension = {8, 32, 12, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 12, .wrap = 10}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 120, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_214 = {8, 32, 16, 12};
+std::vector<uint32_t> ifm2_bound_214 = {8, 20, 16, 12};
+std::vector<uint32_t> ifm2sv_dim_214 = {8, 32, 4, 1};
+uint32_t ifm2sv_size_214 = 4096;
+std::vector<std::vector<access_pattern>> ifm2_pattern_214 = {
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 16, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 16, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 16, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 16, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_214 = {128000};
+std::vector<uint32_t> wts_dim_214 = {128000};
+std::vector<uint32_t> wtssv_dim_214 = {3200};
+uint32_t wtssv_size_214 = 3200;
+uint32_t wts_repetition_214 = 1;
+bool has_l1_wts_write_access_pattern_214 = false;
+std::vector<access_pattern> l1_wts_write_pattern_214 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_214 = {
+{
+  tiling({.buffer_dimension = {32000, 4}, .tiling_dimension = {3200, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 3200, .wrap = 10} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {32000, 4}, .tiling_dimension = {3200, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 3200, .wrap = 10} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {32000, 4}, .tiling_dimension = {3200, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 3200, .wrap = 10} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {32000, 4}, .tiling_dimension = {3200, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 3200, .wrap = 10} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_214[] = {
+{
+  tiling({.buffer_dimension = {128000, 1}, .tiling_dimension = {64000, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {128000, 1}, .tiling_dimension = {64000, 1}, .offset = {64000, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_214[] = {
+{
+  tiling({.buffer_dimension = {128000}, .tiling_dimension = {64000}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {128000}, .tiling_dimension = {64000}, .offset = {64000}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_214 = {8, 32, 16, 12};
+std::vector<uint32_t> ofm_bound_214 = {8, 20, 16, 12};
+std::vector<uint32_t> ofmsv_dim_214 = {8, 32, 4, 1};
+uint32_t ofmsv_size_214 = 1024;
+uint32_t ofm_repetition_214 = 10;
+bool has_l1_read_access_pattern_214 = false;
+
+std::vector<access_pattern> l1_read_pattern_214 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_214 = {
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 8, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 12, 0}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 4, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 8, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 12, 1}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 4, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 8, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 12, 2}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 8, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 4, 1}, .offset = {0, 0, 12, 3}, .tile_traversal = { {.dimension = 3, .stride = 4, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 218
+// LayerName: Conv_351
+std::vector<uint32_t> ifm_dim_218 = {8, 20, 16, 12};
+std::vector<uint32_t> ifm_bound_218 = {8, 20, 16, 12};
+std::vector<uint32_t> ifmsv_dim_218 = {8, 34, 2, 5};
+uint32_t ifmsv_size_218 = 2720;
+uint32_t kernel_iter_218 = 16;
+bool has_l1_write_access_pattern_218 = true;
+std::vector<access_pattern> l1_write_pattern_218 = {tiling({.buffer_dimension = {8, 34, 2, 5}, .tiling_dimension = {8, 22, 2, 5}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_218 = {
+{
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 22, 2, 5}, .offset = {0, -1, 0, -1}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 8} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 20, 16, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 22, 2, 5}, .offset = {0, -1, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 8} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 20, 16, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 22, 2, 5}, .offset = {0, -1, 0, 5}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 8} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 20, 16, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 22, 2, 5}, .offset = {0, -1, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 8} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 20, 16, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_218 = {151552};
+std::vector<uint32_t> wts_dim_218 = {151552};
+std::vector<uint32_t> wtssv_dim_218 = {2368};
+uint32_t wtssv_size_218 = 2368;
+uint32_t wts_repetition_218 = 1;
+bool has_l1_wts_write_access_pattern_218 = false;
+std::vector<access_pattern> l1_wts_write_pattern_218 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_218 = {
+{
+  tiling({.buffer_dimension = {18944, 8}, .tiling_dimension = {2368, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 8}, {.dimension = 1, .stride = 4, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {18944, 8}, .tiling_dimension = {2368, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 8}, {.dimension = 1, .stride = 4, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {18944, 8}, .tiling_dimension = {2368, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 8}, {.dimension = 1, .stride = 4, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {18944, 8}, .tiling_dimension = {2368, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 8}, {.dimension = 1, .stride = 4, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_218[] = {
+{
+  tiling({.buffer_dimension = {151552, 1}, .tiling_dimension = {75776, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {151552, 1}, .tiling_dimension = {75776, 1}, .offset = {75776, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_218[] = {
+{
+  tiling({.buffer_dimension = {151552}, .tiling_dimension = {75776}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {151552}, .tiling_dimension = {75776}, .offset = {75776}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_218 = {8, 32, 16, 12};
+std::vector<uint32_t> ofm_bound_218 = {8, 20, 16, 12};
+std::vector<uint32_t> ofmsv_dim_218 = {8, 32, 2, 3};
+uint32_t ofmsv_size_218 = 1536;
+uint32_t ofm_repetition_218 = 8;
+bool has_l1_read_access_pattern_218 = false;
+
+std::vector<access_pattern> l1_read_pattern_218 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_218 = {
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 219
+// LayerName: Sigmoid_352
+std::vector<uint32_t> ifm_dim_219 = {8, 32, 16, 12};
+std::vector<uint32_t> ifm_bound_219 = {8, 20, 16, 12};
+std::vector<uint32_t> ifmsv_dim_219 = {8, 20, 4, 3};
+uint32_t ifmsv_size_219 = 7680;
+uint32_t kernel_iter_219 = 1;
+bool has_l1_write_access_pattern_219 = false;
+std::vector<access_pattern> l1_write_pattern_219 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_219 = {
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 16, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 16, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 16, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 16, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 4, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 16, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_219 = 0;
+bool has_l1_wts_write_access_pattern_219 = false;
+std::vector<access_pattern> l1_wts_write_pattern_219 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_219 = {};
+
+
+std::vector<uint32_t> ofm_dim_219 = {8, 20, 16, 12};
+std::vector<uint32_t> ofm_bound_219 = {8, 20, 16, 12};
+std::vector<uint32_t> ofmsv_dim_219 = {8, 20, 4, 3};
+uint32_t ofmsv_size_219 = 1920;
+uint32_t ofm_repetition_219 = 1;
+bool has_l1_read_access_pattern_219 = false;
+
+std::vector<access_pattern> l1_read_pattern_219 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_219 = {
+{
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 3}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 3}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 6}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 6}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 8, 9}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 20, 4, 3}, .offset = {0, 0, 12, 9}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 221
+// LayerName: Sub_359
+std::vector<uint32_t> ifm_dim_221 = {8, 20, 8, 12};
+std::vector<uint32_t> ifm_bound_221 = {8, 20, 8, 12};
+std::vector<uint32_t> ifmsv_dim_221 = {8, 20, 2, 3};
+uint32_t ifmsv_size_221 = 3840;
+uint32_t kernel_iter_221 = 1;
+bool has_l1_write_access_pattern_221 = false;
+std::vector<access_pattern> l1_write_pattern_221 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_221 = {
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_221 = {8, 20, 8, 12};
+std::vector<uint32_t> ifm2_bound_221 = {8, 20, 8, 12};
+std::vector<uint32_t> ifm2sv_dim_221 = {8, 20, 2, 3};
+uint32_t ifm2sv_size_221 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_221 = {
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_221 = 0;
+bool has_l1_wts_write_access_pattern_221 = false;
+std::vector<access_pattern> l1_wts_write_pattern_221 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_221 = {};
+
+
+std::vector<uint32_t> ofm_dim_221 = {8, 20, 8, 12};
+std::vector<uint32_t> ofm_bound_221 = {8, 20, 8, 12};
+std::vector<uint32_t> ofmsv_dim_221 = {8, 20, 2, 3};
+uint32_t ofmsv_size_221 = 960;
+uint32_t ofm_repetition_221 = 1;
+bool has_l1_read_access_pattern_221 = false;
+
+std::vector<access_pattern> l1_read_pattern_221 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_221 = {
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 222
+// LayerName: Mul_360
+std::vector<uint32_t> ifm_dim_222 = {8, 20, 8, 12};
+std::vector<uint32_t> ifm_bound_222 = {8, 20, 8, 12};
+std::vector<uint32_t> ifmsv_dim_222 = {8, 20, 2, 3};
+uint32_t ifmsv_size_222 = 3840;
+uint32_t kernel_iter_222 = 1;
+bool has_l1_write_access_pattern_222 = false;
+std::vector<access_pattern> l1_write_pattern_222 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_222 = {
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_222 = {8, 20, 8, 12};
+std::vector<uint32_t> ifm2_bound_222 = {8, 20, 8, 12};
+std::vector<uint32_t> ifm2sv_dim_222 = {8, 20, 2, 3};
+uint32_t ifm2sv_size_222 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_222 = {
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_222 = 0;
+bool has_l1_wts_write_access_pattern_222 = false;
+std::vector<access_pattern> l1_wts_write_pattern_222 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_222 = {};
+
+
+std::vector<uint32_t> ofm_dim_222 = {8, 20, 8, 12};
+std::vector<uint32_t> ofm_bound_222 = {8, 20, 8, 12};
+std::vector<uint32_t> ofmsv_dim_222 = {8, 20, 2, 3};
+uint32_t ofmsv_size_222 = 960;
+uint32_t ofm_repetition_222 = 1;
+bool has_l1_read_access_pattern_222 = false;
+
+std::vector<access_pattern> l1_read_pattern_222 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_222 = {
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 224
+// LayerName: Mul_354
+std::vector<uint32_t> ifm_dim_224 = {8, 20, 8, 12};
+std::vector<uint32_t> ifm_bound_224 = {8, 20, 8, 12};
+std::vector<uint32_t> ifmsv_dim_224 = {8, 20, 2, 3};
+uint32_t ifmsv_size_224 = 3840;
+uint32_t kernel_iter_224 = 1;
+bool has_l1_write_access_pattern_224 = false;
+std::vector<access_pattern> l1_write_pattern_224 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_224 = {
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_224 = {8, 20, 8, 12};
+std::vector<uint32_t> ifm2_bound_224 = {8, 20, 8, 12};
+std::vector<uint32_t> ifm2sv_dim_224 = {8, 20, 2, 3};
+uint32_t ifm2sv_size_224 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_224 = {
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_224 = 0;
+bool has_l1_wts_write_access_pattern_224 = false;
+std::vector<access_pattern> l1_wts_write_pattern_224 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_224 = {};
+
+
+std::vector<uint32_t> ofm_dim_224 = {8, 20, 8, 12};
+std::vector<uint32_t> ofm_bound_224 = {8, 20, 8, 12};
+std::vector<uint32_t> ofmsv_dim_224 = {8, 20, 2, 3};
+uint32_t ofmsv_size_224 = 960;
+uint32_t ofm_repetition_224 = 1;
+bool has_l1_read_access_pattern_224 = false;
+
+std::vector<access_pattern> l1_read_pattern_224 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_224 = {
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 226
+// LayerName: Conv_356
+std::vector<uint32_t> ifm_dim_226 = {8, 20, 16, 12};
+std::vector<uint32_t> ifm_bound_226 = {8, 20, 16, 12};
+std::vector<uint32_t> ifmsv_dim_226 = {8, 34, 2, 5};
+uint32_t ifmsv_size_226 = 2720;
+uint32_t kernel_iter_226 = 8;
+bool has_l1_write_access_pattern_226 = true;
+std::vector<access_pattern> l1_write_pattern_226 = {tiling({.buffer_dimension = {8, 34, 2, 5}, .tiling_dimension = {8, 22, 2, 5}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_226 = {
+{
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 22, 2, 5}, .offset = {0, -1, 0, -1}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 16, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 22, 2, 5}, .offset = {0, -1, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 16, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 22, 2, 5}, .offset = {0, -1, 0, 5}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 16, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 16, 12}, .tiling_dimension = {8, 22, 2, 5}, .offset = {0, -1, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 16, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_226 = {75776};
+std::vector<uint32_t> wts_dim_226 = {75776};
+std::vector<uint32_t> wtssv_dim_226 = {2368};
+uint32_t wtssv_size_226 = 2368;
+uint32_t wts_repetition_226 = 1;
+bool has_l1_wts_write_access_pattern_226 = false;
+std::vector<access_pattern> l1_wts_write_pattern_226 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_226 = {
+{
+  tiling({.buffer_dimension = {18944, 4}, .tiling_dimension = {2368, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {18944, 4}, .tiling_dimension = {2368, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {18944, 4}, .tiling_dimension = {2368, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {18944, 4}, .tiling_dimension = {2368, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_226[] = {
+{
+  tiling({.buffer_dimension = {75776, 1}, .tiling_dimension = {37888, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {75776, 1}, .tiling_dimension = {37888, 1}, .offset = {37888, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_226[] = {
+{
+  tiling({.buffer_dimension = {75776}, .tiling_dimension = {37888}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {75776}, .tiling_dimension = {37888}, .offset = {37888}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_226 = {8, 32, 8, 12};
+std::vector<uint32_t> ofm_bound_226 = {8, 20, 8, 12};
+std::vector<uint32_t> ofmsv_dim_226 = {8, 32, 2, 3};
+uint32_t ofmsv_size_226 = 1536;
+uint32_t ofm_repetition_226 = 8;
+bool has_l1_read_access_pattern_226 = false;
+
+std::vector<access_pattern> l1_read_pattern_226 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_226 = {
+{
+  tiling({.buffer_dimension = {8, 32, 8, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 8, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 8, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 8, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 8, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 8, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 8, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 8, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 8, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 8, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 8, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 8, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 8, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 8, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 8, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 32, 8, 12}, .tiling_dimension = {8, 32, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 227
+// LayerName: Tanh_357
+std::vector<uint32_t> ifm_dim_227 = {8, 32, 8, 12};
+std::vector<uint32_t> ifm_bound_227 = {8, 20, 8, 12};
+std::vector<uint32_t> ifmsv_dim_227 = {8, 20, 2, 3};
+uint32_t ifmsv_size_227 = 3840;
+uint32_t kernel_iter_227 = 1;
+bool has_l1_write_access_pattern_227 = false;
+std::vector<access_pattern> l1_write_pattern_227 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_227 = {
+{
+  tiling({.buffer_dimension = {8, 32, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 32, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_227 = 0;
+bool has_l1_wts_write_access_pattern_227 = false;
+std::vector<access_pattern> l1_wts_write_pattern_227 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_227 = {};
+
+
+std::vector<uint32_t> ofm_dim_227 = {8, 20, 8, 12};
+std::vector<uint32_t> ofm_bound_227 = {8, 20, 8, 12};
+std::vector<uint32_t> ofmsv_dim_227 = {8, 20, 2, 3};
+uint32_t ofmsv_size_227 = 960;
+uint32_t ofm_repetition_227 = 1;
+bool has_l1_read_access_pattern_227 = false;
+
+std::vector<access_pattern> l1_read_pattern_227 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_227 = {
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 228
+// LayerName: Mul_361
+std::vector<uint32_t> ifm_dim_228 = {8, 20, 8, 12};
+std::vector<uint32_t> ifm_bound_228 = {8, 20, 8, 12};
+std::vector<uint32_t> ifmsv_dim_228 = {8, 20, 2, 3};
+uint32_t ifmsv_size_228 = 3840;
+uint32_t kernel_iter_228 = 1;
+bool has_l1_write_access_pattern_228 = false;
+std::vector<access_pattern> l1_write_pattern_228 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_228 = {
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_228 = {8, 20, 8, 12};
+std::vector<uint32_t> ifm2_bound_228 = {8, 20, 8, 12};
+std::vector<uint32_t> ifm2sv_dim_228 = {8, 20, 2, 3};
+uint32_t ifm2sv_size_228 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_228 = {
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_228 = 0;
+bool has_l1_wts_write_access_pattern_228 = false;
+std::vector<access_pattern> l1_wts_write_pattern_228 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_228 = {};
+
+
+std::vector<uint32_t> ofm_dim_228 = {8, 20, 8, 12};
+std::vector<uint32_t> ofm_bound_228 = {8, 20, 8, 12};
+std::vector<uint32_t> ofmsv_dim_228 = {8, 20, 2, 3};
+uint32_t ofmsv_size_228 = 960;
+uint32_t ofm_repetition_228 = 1;
+bool has_l1_read_access_pattern_228 = false;
+
+std::vector<access_pattern> l1_read_pattern_228 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_228 = {
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 229
+// LayerName: Add_362
+std::vector<uint32_t> ifm_dim_229 = {8, 20, 8, 12};
+std::vector<uint32_t> ifm_bound_229 = {8, 20, 8, 12};
+std::vector<uint32_t> ifmsv_dim_229 = {8, 20, 2, 3};
+uint32_t ifmsv_size_229 = 3840;
+uint32_t kernel_iter_229 = 1;
+bool has_l1_write_access_pattern_229 = false;
+std::vector<access_pattern> l1_write_pattern_229 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_229 = {
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_229 = {8, 20, 8, 12};
+std::vector<uint32_t> ifm2_bound_229 = {8, 20, 8, 12};
+std::vector<uint32_t> ifm2sv_dim_229 = {8, 20, 2, 3};
+uint32_t ifm2sv_size_229 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_229 = {
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 20, 8, 12}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_229 = 0;
+bool has_l1_wts_write_access_pattern_229 = false;
+std::vector<access_pattern> l1_wts_write_pattern_229 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_229 = {};
+
+
+std::vector<uint32_t> ofm_dim_229 = {8, 20, 8, 12};
+std::vector<uint32_t> ofm_bound_229 = {8, 20, 8, 12};
+std::vector<uint32_t> ofmsv_dim_229 = {8, 20, 2, 3};
+uint32_t ofmsv_size_229 = 960;
+uint32_t ofm_repetition_229 = 1;
+bool has_l1_read_access_pattern_229 = false;
+
+std::vector<access_pattern> l1_read_pattern_229 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_229 = {
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 20, 8, 12}, .tiling_dimension = {8, 20, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 233
+// LayerName: AveragePool_346
+std::vector<uint32_t> ifm_dim_233 = {8, 320, 1, 60};
+std::vector<uint32_t> ifm_bound_233 = {8, 320, 1, 60};
+std::vector<uint32_t> ifmsv_dim_233 = {8, 80, 1, 2};
+uint32_t ifmsv_size_233 = 5120;
+uint32_t kernel_iter_233 = 96;
+bool has_l1_write_access_pattern_233 = false;
+std::vector<access_pattern> l1_write_pattern_233 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_233 = {
+{
+  tiling({.buffer_dimension = {8, 320, 1, 60}, .tiling_dimension = {8, 80, 1, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 80, .wrap = 4}, {.dimension = 3, .stride = 8, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 60}, .tiling_dimension = {8, 80, 1, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 80, .wrap = 4}, {.dimension = 3, .stride = 8, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 60}, .tiling_dimension = {8, 80, 1, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 80, .wrap = 4}, {.dimension = 3, .stride = 8, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 60}, .tiling_dimension = {8, 80, 1, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 80, .wrap = 4}, {.dimension = 3, .stride = 8, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_233 = 0;
+bool has_l1_wts_write_access_pattern_233 = false;
+std::vector<access_pattern> l1_wts_write_pattern_233 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_233 = {
+{
+  tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 96, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 96, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 96, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 96, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_233 = {8, 160, 4, 32};
+std::vector<uint32_t> ofm_bound_233 = {8, 160, 1, 30};
+std::vector<uint32_t> ofmsv_dim_233 = {8, 40, 1, 1};
+uint32_t ofmsv_size_233 = 320;
+uint32_t ofm_repetition_233 = 1;
+bool has_l1_read_access_pattern_233 = false;
+
+std::vector<access_pattern> l1_read_pattern_233 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_233 = {
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 40, 1, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 40, 1, 1}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 40, 1, 1}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 40, 1, 1}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 40, 1, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 40, 1, 1}, .offset = {0, 0, 1, 1}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 40, 1, 1}, .offset = {0, 0, 2, 1}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 40, 1, 1}, .offset = {0, 0, 3, 1}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 40, 1, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 40, 1, 1}, .offset = {0, 0, 1, 2}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 40, 1, 1}, .offset = {0, 0, 2, 2}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 40, 1, 1}, .offset = {0, 0, 3, 2}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 40, 1, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 40, 1, 1}, .offset = {0, 0, 1, 3}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 40, 1, 1}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 40, 1, 1}, .offset = {0, 0, 3, 3}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 4}, {.dimension = 3, .stride = 4, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 234
+// LayerName: AveragePool_347
+std::vector<uint32_t> ifm_dim_234 = {8, 160, 1, 90};
+std::vector<uint32_t> ifm_bound_234 = {8, 160, 1, 90};
+std::vector<uint32_t> ifmsv_dim_234 = {8, 16, 1, 12};
+uint32_t ifmsv_size_234 = 6144;
+uint32_t kernel_iter_234 = 20;
+bool has_l1_write_access_pattern_234 = false;
+std::vector<access_pattern> l1_write_pattern_234 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_234 = {
+{
+  tiling({.buffer_dimension = {8, 160, 1, 90}, .tiling_dimension = {8, 16, 1, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10}, {.dimension = 3, .stride = 48, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 160, 1, 90}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 1, 90}, .tiling_dimension = {8, 16, 1, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10}, {.dimension = 3, .stride = 48, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 160, 1, 90}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 1, 90}, .tiling_dimension = {8, 16, 1, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10}, {.dimension = 3, .stride = 48, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 160, 1, 90}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 1, 90}, .tiling_dimension = {8, 16, 1, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10}, {.dimension = 3, .stride = 48, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 160, 1, 90}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_234 = 0;
+bool has_l1_wts_write_access_pattern_234 = false;
+std::vector<access_pattern> l1_wts_write_pattern_234 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_234 = {
+{
+  tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 20, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 20, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 20, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 20, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_234 = {8, 80, 4, 48};
+std::vector<uint32_t> ofm_bound_234 = {8, 80, 1, 45};
+std::vector<uint32_t> ofmsv_dim_234 = {8, 8, 1, 6};
+uint32_t ofmsv_size_234 = 384;
+uint32_t ofm_repetition_234 = 1;
+bool has_l1_read_access_pattern_234 = false;
+
+std::vector<access_pattern> l1_read_pattern_234 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_234 = {
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 1, 6}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 3, 6}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 1, 12}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 3, 12}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 1, 18}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 2, 18}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 3, 18}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 10}, {.dimension = 3, .stride = 24, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 235
+// LayerName: AveragePool_348
+std::vector<uint32_t> ifm_dim_235 = {8, 80, 4, 48};
+std::vector<uint32_t> ifm_bound_235 = {8, 80, 1, 45};
+std::vector<uint32_t> ifmsv_dim_235 = {8, 16, 1, 12};
+uint32_t ifmsv_size_235 = 6144;
+uint32_t kernel_iter_235 = 5;
+bool has_l1_write_access_pattern_235 = false;
+std::vector<access_pattern> l1_write_pattern_235 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_235 = {
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 16, 1, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 1, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 16, 1, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 1, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 16, 1, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 1, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 16, 1, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 1, 45}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_235 = 0;
+bool has_l1_wts_write_access_pattern_235 = false;
+std::vector<access_pattern> l1_wts_write_pattern_235 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_235 = {
+{
+  tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_235 = {8, 40, 4, 24};
+std::vector<uint32_t> ofm_bound_235 = {8, 40, 1, 23};
+std::vector<uint32_t> ofmsv_dim_235 = {8, 8, 1, 6};
+uint32_t ofmsv_size_235 = 384;
+uint32_t ofm_repetition_235 = 1;
+bool has_l1_read_access_pattern_235 = false;
+
+std::vector<access_pattern> l1_read_pattern_235 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_235 = {
+{
+  tiling({.buffer_dimension = {8, 40, 4, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 4, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 4, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 4, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 4, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 4, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 1, 6}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 4, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 4, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 3, 6}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 4, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 4, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 1, 12}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 4, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 4, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 3, 12}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 4, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 4, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 1, 18}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 4, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 2, 18}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 4, 24}, .tiling_dimension = {8, 8, 1, 6}, .offset = {0, 0, 3, 18}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 237
+// LayerName: Conv_373
+std::vector<uint32_t> ifm_dim_237 = {8, 40, 22, 23};
+std::vector<uint32_t> ifm_bound_237 = {8, 40, 22, 23};
+std::vector<uint32_t> ifmsv_dim_237 = {8, 50, 2, 5};
+uint32_t ifmsv_size_237 = 4000;
+uint32_t kernel_iter_237 = 44;
+bool has_l1_write_access_pattern_237 = true;
+std::vector<access_pattern> l1_write_pattern_237 = {tiling({.buffer_dimension = {8, 50, 2, 5}, .tiling_dimension = {8, 42, 2, 5}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_237 = {
+{
+  tiling({.buffer_dimension = {8, 40, 22, 23}, .tiling_dimension = {8, 42, 2, 5}, .offset = {0, -1, 0, -1}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 11}, {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 40, 22, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 22, 23}, .tiling_dimension = {8, 42, 2, 5}, .offset = {0, -1, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 11}, {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 40, 22, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 22, 23}, .tiling_dimension = {8, 42, 2, 5}, .offset = {0, -1, 0, 5}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 11}, {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 40, 22, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 22, 23}, .tiling_dimension = {8, 42, 2, 5}, .offset = {0, -1, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 11}, {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 40, 22, 23}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_237 = {208384};
+std::vector<uint32_t> wts_dim_237 = {208384};
+std::vector<uint32_t> wtssv_dim_237 = {2368};
+uint32_t wtssv_size_237 = 2368;
+uint32_t wts_repetition_237 = 1;
+bool has_l1_wts_write_access_pattern_237 = false;
+std::vector<access_pattern> l1_wts_write_pattern_237 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_237 = {
+{
+  tiling({.buffer_dimension = {26048, 8}, .tiling_dimension = {2368, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 11} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {26048, 8}, .tiling_dimension = {2368, 1}, .offset = {0, 4}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 11} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {26048, 8}, .tiling_dimension = {2368, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 11} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {26048, 8}, .tiling_dimension = {2368, 1}, .offset = {0, 5}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 11} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {26048, 8}, .tiling_dimension = {2368, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 11} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {26048, 8}, .tiling_dimension = {2368, 1}, .offset = {0, 6}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 11} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {26048, 8}, .tiling_dimension = {2368, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 11} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {26048, 8}, .tiling_dimension = {2368, 1}, .offset = {0, 7}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 11} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_237[] = {
+{
+  tiling({.buffer_dimension = {208384, 1}, .tiling_dimension = {104192, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {208384, 1}, .tiling_dimension = {104192, 1}, .offset = {104192, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_237[] = {
+{
+  tiling({.buffer_dimension = {208384}, .tiling_dimension = {104192}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {208384}, .tiling_dimension = {104192}, .offset = {104192}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_237 = {8, 48, 16, 24};
+std::vector<uint32_t> ofm_bound_237 = {8, 40, 10, 23};
+std::vector<uint32_t> ofmsv_dim_237 = {8, 48, 2, 3};
+uint32_t ofmsv_size_237 = 2304;
+uint32_t ofm_repetition_237 = 11;
+bool has_l1_read_access_pattern_237 = false;
+
+std::vector<access_pattern> l1_read_pattern_237 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_237 = {
+{
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 241
+// LayerName: Conv_377
+std::vector<uint32_t> ifm_dim_241 = {8, 40, 10, 23};
+std::vector<uint32_t> ifm_bound_241 = {8, 40, 10, 23};
+std::vector<uint32_t> ifmsv_dim_241 = {8, 50, 2, 5};
+uint32_t ifmsv_size_241 = 4000;
+uint32_t kernel_iter_241 = 20;
+bool has_l1_write_access_pattern_241 = true;
+std::vector<access_pattern> l1_write_pattern_241 = {tiling({.buffer_dimension = {8, 50, 2, 5}, .tiling_dimension = {8, 42, 2, 5}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_241 = {
+{
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 42, 2, 5}, .offset = {0, -1, 0, -1}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 5}, {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 40, 10, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 42, 2, 5}, .offset = {0, -1, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 5}, {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 40, 10, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 42, 2, 5}, .offset = {0, -1, 0, 5}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 5}, {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 40, 10, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 42, 2, 5}, .offset = {0, -1, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 5}, {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {8, 40, 10, 23}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_241 = {94720};
+std::vector<uint32_t> wts_dim_241 = {94720};
+std::vector<uint32_t> wtssv_dim_241 = {2368};
+uint32_t wtssv_size_241 = 2368;
+uint32_t wts_repetition_241 = 1;
+bool has_l1_wts_write_access_pattern_241 = false;
+std::vector<access_pattern> l1_wts_write_pattern_241 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_241 = {
+{
+  tiling({.buffer_dimension = {11840, 8}, .tiling_dimension = {2368, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 5} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {11840, 8}, .tiling_dimension = {2368, 1}, .offset = {0, 4}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 5} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {11840, 8}, .tiling_dimension = {2368, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 5} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {11840, 8}, .tiling_dimension = {2368, 1}, .offset = {0, 5}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 5} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {11840, 8}, .tiling_dimension = {2368, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 5} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {11840, 8}, .tiling_dimension = {2368, 1}, .offset = {0, 6}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 5} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {11840, 8}, .tiling_dimension = {2368, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 5} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {11840, 8}, .tiling_dimension = {2368, 1}, .offset = {0, 7}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 5} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_241[] = {
+{
+  tiling({.buffer_dimension = {94720, 1}, .tiling_dimension = {47360, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {94720, 1}, .tiling_dimension = {47360, 1}, .offset = {47360, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_241[] = {
+{
+  tiling({.buffer_dimension = {94720}, .tiling_dimension = {47360}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {94720}, .tiling_dimension = {47360}, .offset = {47360}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_241 = {8, 48, 16, 24};
+std::vector<uint32_t> ofm_bound_241 = {8, 40, 10, 23};
+std::vector<uint32_t> ofmsv_dim_241 = {8, 48, 2, 3};
+uint32_t ofmsv_size_241 = 2304;
+uint32_t ofm_repetition_241 = 5;
+bool has_l1_read_access_pattern_241 = false;
+
+std::vector<access_pattern> l1_read_pattern_241 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_241 = {
+{
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2}, {.dimension = 2, .stride = 8, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 242
+// LayerName: Sigmoid_378
+std::vector<uint32_t> ifm_dim_242 = {8, 48, 16, 24};
+std::vector<uint32_t> ifm_bound_242 = {8, 40, 10, 23};
+std::vector<uint32_t> ifmsv_dim_242 = {8, 40, 3, 2};
+uint32_t ifmsv_size_242 = 7680;
+uint32_t kernel_iter_242 = 3;
+bool has_l1_write_access_pattern_242 = false;
+std::vector<access_pattern> l1_write_pattern_242 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_242 = {
+{
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 40, 3, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 10, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 40, 3, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 10, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 40, 3, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 10, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 48, 16, 24}, .tiling_dimension = {8, 40, 3, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 3, .wrap = 4}, {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 10, 23}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_242 = 0;
+bool has_l1_wts_write_access_pattern_242 = false;
+std::vector<access_pattern> l1_wts_write_pattern_242 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_242 = {};
+
+
+std::vector<uint32_t> ofm_dim_242 = {8, 40, 12, 24};
+std::vector<uint32_t> ofm_bound_242 = {8, 40, 10, 23};
+std::vector<uint32_t> ofmsv_dim_242 = {8, 40, 3, 2};
+uint32_t ofmsv_size_242 = 1920;
+uint32_t ofm_repetition_242 = 1;
+bool has_l1_read_access_pattern_242 = false;
+
+std::vector<access_pattern> l1_read_pattern_242 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_242 = {
+{
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 40, 3, 2}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 40, 3, 2}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 40, 3, 2}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 40, 3, 2}, .offset = {0, 0, 9, 0}, .tile_traversal = { {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 40, 3, 2}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 40, 3, 2}, .offset = {0, 0, 3, 2}, .tile_traversal = { {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 40, 3, 2}, .offset = {0, 0, 6, 2}, .tile_traversal = { {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 40, 3, 2}, .offset = {0, 0, 9, 2}, .tile_traversal = { {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 40, 3, 2}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 40, 3, 2}, .offset = {0, 0, 3, 4}, .tile_traversal = { {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 40, 3, 2}, .offset = {0, 0, 6, 4}, .tile_traversal = { {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 40, 3, 2}, .offset = {0, 0, 9, 4}, .tile_traversal = { {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 40, 3, 2}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 40, 3, 2}, .offset = {0, 0, 3, 6}, .tile_traversal = { {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 40, 3, 2}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 12, 24}, .tiling_dimension = {8, 40, 3, 2}, .offset = {0, 0, 9, 6}, .tile_traversal = { {.dimension = 3, .stride = 8, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 244
+// LayerName: Sub_385
+std::vector<uint32_t> ifm_dim_244 = {8, 40, 5, 23};
+std::vector<uint32_t> ifm_bound_244 = {8, 40, 5, 23};
+std::vector<uint32_t> ifmsv_dim_244 = {8, 10, 2, 6};
+uint32_t ifmsv_size_244 = 3840;
+uint32_t kernel_iter_244 = 4;
+bool has_l1_write_access_pattern_244 = false;
+std::vector<access_pattern> l1_write_pattern_244 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_244 = {
+{
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_244 = {8, 40, 5, 23};
+std::vector<uint32_t> ifm2_bound_244 = {8, 40, 5, 23};
+std::vector<uint32_t> ifm2sv_dim_244 = {8, 10, 2, 6};
+uint32_t ifm2sv_size_244 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_244 = {
+{
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_244 = 0;
+bool has_l1_wts_write_access_pattern_244 = false;
+std::vector<access_pattern> l1_wts_write_pattern_244 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_244 = {};
+
+
+std::vector<uint32_t> ofm_dim_244 = {8, 40, 8, 24};
+std::vector<uint32_t> ofm_bound_244 = {8, 40, 5, 23};
+std::vector<uint32_t> ofmsv_dim_244 = {8, 10, 2, 6};
+uint32_t ofmsv_size_244 = 960;
+uint32_t ofm_repetition_244 = 1;
+bool has_l1_read_access_pattern_244 = false;
+
+std::vector<access_pattern> l1_read_pattern_244 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_244 = {
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 18}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 18}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 18}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 245
+// LayerName: Mul_386
+std::vector<uint32_t> ifm_dim_245 = {8, 40, 8, 24};
+std::vector<uint32_t> ifm_bound_245 = {8, 40, 5, 23};
+std::vector<uint32_t> ifmsv_dim_245 = {8, 10, 2, 6};
+uint32_t ifmsv_size_245 = 3840;
+uint32_t kernel_iter_245 = 4;
+bool has_l1_write_access_pattern_245 = false;
+std::vector<access_pattern> l1_write_pattern_245 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_245 = {
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_245 = {8, 40, 5, 23};
+std::vector<uint32_t> ifm2_bound_245 = {8, 40, 5, 23};
+std::vector<uint32_t> ifm2sv_dim_245 = {8, 10, 2, 6};
+uint32_t ifm2sv_size_245 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_245 = {
+{
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_245 = 0;
+bool has_l1_wts_write_access_pattern_245 = false;
+std::vector<access_pattern> l1_wts_write_pattern_245 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_245 = {};
+
+
+std::vector<uint32_t> ofm_dim_245 = {8, 40, 8, 24};
+std::vector<uint32_t> ofm_bound_245 = {8, 40, 5, 23};
+std::vector<uint32_t> ofmsv_dim_245 = {8, 10, 2, 6};
+uint32_t ofmsv_size_245 = 960;
+uint32_t ofm_repetition_245 = 1;
+bool has_l1_read_access_pattern_245 = false;
+
+std::vector<access_pattern> l1_read_pattern_245 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_245 = {
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 18}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 18}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 18}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 247
+// LayerName: Mul_380
+std::vector<uint32_t> ifm_dim_247 = {8, 40, 5, 23};
+std::vector<uint32_t> ifm_bound_247 = {8, 40, 5, 23};
+std::vector<uint32_t> ifmsv_dim_247 = {8, 10, 2, 6};
+uint32_t ifmsv_size_247 = 3840;
+uint32_t kernel_iter_247 = 4;
+bool has_l1_write_access_pattern_247 = false;
+std::vector<access_pattern> l1_write_pattern_247 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_247 = {
+{
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_247 = {8, 40, 5, 23};
+std::vector<uint32_t> ifm2_bound_247 = {8, 40, 5, 23};
+std::vector<uint32_t> ifm2sv_dim_247 = {8, 10, 2, 6};
+uint32_t ifm2sv_size_247 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_247 = {
+{
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_247 = 0;
+bool has_l1_wts_write_access_pattern_247 = false;
+std::vector<access_pattern> l1_wts_write_pattern_247 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_247 = {};
+
+
+std::vector<uint32_t> ofm_dim_247 = {8, 40, 8, 24};
+std::vector<uint32_t> ofm_bound_247 = {8, 40, 5, 23};
+std::vector<uint32_t> ofmsv_dim_247 = {8, 10, 2, 6};
+uint32_t ofmsv_size_247 = 960;
+uint32_t ofm_repetition_247 = 1;
+bool has_l1_read_access_pattern_247 = false;
+
+std::vector<access_pattern> l1_read_pattern_247 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_247 = {
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 18}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 18}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 18}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 249
+// LayerName: Conv_382
+std::vector<uint32_t> ifm_dim_249 = {8, 40, 10, 23};
+std::vector<uint32_t> ifm_bound_249 = {8, 40, 10, 23};
+std::vector<uint32_t> ifmsv_dim_249 = {8, 50, 2, 5};
+uint32_t ifmsv_size_249 = 4000;
+uint32_t kernel_iter_249 = 10;
+bool has_l1_write_access_pattern_249 = true;
+std::vector<access_pattern> l1_write_pattern_249 = {tiling({.buffer_dimension = {8, 50, 2, 5}, .tiling_dimension = {8, 42, 2, 5}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_249 = {
+{
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 42, 2, 5}, .offset = {0, -1, 0, -1}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 5}, {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 10, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 42, 2, 5}, .offset = {0, -1, 0, 2}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 5}, {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 10, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 42, 2, 5}, .offset = {0, -1, 0, 5}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 5}, {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 10, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 10, 23}, .tiling_dimension = {8, 42, 2, 5}, .offset = {0, -1, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 5}, {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 10, 23}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_249 = {47360};
+std::vector<uint32_t> wts_dim_249 = {47360};
+std::vector<uint32_t> wtssv_dim_249 = {2368};
+uint32_t wtssv_size_249 = 2368;
+uint32_t wts_repetition_249 = 1;
+bool has_l1_wts_write_access_pattern_249 = false;
+std::vector<access_pattern> l1_wts_write_pattern_249 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_249 = {
+{
+  tiling({.buffer_dimension = {11840, 4}, .tiling_dimension = {2368, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 5} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {11840, 4}, .tiling_dimension = {2368, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 5} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {11840, 4}, .tiling_dimension = {2368, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 5} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {11840, 4}, .tiling_dimension = {2368, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 5} }, .packet_port_id = -1, .repetition = 2, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_249[] = {
+{
+  tiling({.buffer_dimension = {47360, 1}, .tiling_dimension = {23680, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {47360, 1}, .tiling_dimension = {23680, 1}, .offset = {23680, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_249[] = {
+{
+  tiling({.buffer_dimension = {47360}, .tiling_dimension = {23680}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {47360}, .tiling_dimension = {23680}, .offset = {23680}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_249 = {8, 48, 8, 24};
+std::vector<uint32_t> ofm_bound_249 = {8, 40, 5, 23};
+std::vector<uint32_t> ofmsv_dim_249 = {8, 48, 2, 3};
+uint32_t ofmsv_size_249 = 2304;
+uint32_t ofm_repetition_249 = 5;
+bool has_l1_read_access_pattern_249 = false;
+
+std::vector<access_pattern> l1_read_pattern_249 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_249 = {
+{
+  tiling({.buffer_dimension = {8, 48, 8, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 8, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 8, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 8, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 48, 8, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 8, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 8, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 4, 3}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 8, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 6, 3}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 48, 8, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 8, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 8, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 8, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 48, 8, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 0, 9}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 8, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 2, 9}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 8, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 4, 9}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 48, 8, 24}, .tiling_dimension = {8, 48, 2, 3}, .offset = {0, 0, 6, 9}, .tile_traversal = { {.dimension = 3, .stride = 12, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 250
+// LayerName: Tanh_383
+std::vector<uint32_t> ifm_dim_250 = {8, 48, 8, 24};
+std::vector<uint32_t> ifm_bound_250 = {8, 40, 5, 23};
+std::vector<uint32_t> ifmsv_dim_250 = {8, 20, 2, 6};
+uint32_t ifmsv_size_250 = 7680;
+uint32_t kernel_iter_250 = 2;
+bool has_l1_write_access_pattern_250 = false;
+std::vector<access_pattern> l1_write_pattern_250 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_250 = {
+{
+  tiling({.buffer_dimension = {8, 48, 8, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 48, 8, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 48, 8, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 48, 8, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_250 = 0;
+bool has_l1_wts_write_access_pattern_250 = false;
+std::vector<access_pattern> l1_wts_write_pattern_250 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_250 = {};
+
+
+std::vector<uint32_t> ofm_dim_250 = {8, 40, 8, 24};
+std::vector<uint32_t> ofm_bound_250 = {8, 40, 5, 23};
+std::vector<uint32_t> ofmsv_dim_250 = {8, 20, 2, 6};
+uint32_t ofmsv_size_250 = 1920;
+uint32_t ofm_repetition_250 = 1;
+bool has_l1_read_access_pattern_250 = false;
+
+std::vector<access_pattern> l1_read_pattern_250 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_250 = {
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 4, 12}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 6, 12}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 2, 18}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 4, 18}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 20, 2, 6}, .offset = {0, 0, 6, 18}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 251
+// LayerName: Mul_387
+std::vector<uint32_t> ifm_dim_251 = {8, 40, 5, 23};
+std::vector<uint32_t> ifm_bound_251 = {8, 40, 5, 23};
+std::vector<uint32_t> ifmsv_dim_251 = {8, 10, 2, 6};
+uint32_t ifmsv_size_251 = 3840;
+uint32_t kernel_iter_251 = 4;
+bool has_l1_write_access_pattern_251 = false;
+std::vector<access_pattern> l1_write_pattern_251 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_251 = {
+{
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 5, 23}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_251 = {8, 40, 8, 24};
+std::vector<uint32_t> ifm2_bound_251 = {8, 40, 5, 23};
+std::vector<uint32_t> ifm2sv_dim_251 = {8, 10, 2, 6};
+uint32_t ifm2sv_size_251 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_251 = {
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_251 = 0;
+bool has_l1_wts_write_access_pattern_251 = false;
+std::vector<access_pattern> l1_wts_write_pattern_251 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_251 = {};
+
+
+std::vector<uint32_t> ofm_dim_251 = {8, 40, 8, 24};
+std::vector<uint32_t> ofm_bound_251 = {8, 40, 5, 23};
+std::vector<uint32_t> ofmsv_dim_251 = {8, 10, 2, 6};
+uint32_t ofmsv_size_251 = 960;
+uint32_t ofm_repetition_251 = 1;
+bool has_l1_read_access_pattern_251 = false;
+
+std::vector<access_pattern> l1_read_pattern_251 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_251 = {
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 18}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 18}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 18}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 252
+// LayerName: Add_388
+std::vector<uint32_t> ifm_dim_252 = {8, 40, 8, 24};
+std::vector<uint32_t> ifm_bound_252 = {8, 40, 5, 23};
+std::vector<uint32_t> ifmsv_dim_252 = {8, 10, 2, 6};
+uint32_t ifmsv_size_252 = 3840;
+uint32_t kernel_iter_252 = 4;
+bool has_l1_write_access_pattern_252 = false;
+std::vector<access_pattern> l1_write_pattern_252 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_252 = {
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_252 = {8, 40, 8, 24};
+std::vector<uint32_t> ifm2_bound_252 = {8, 40, 5, 23};
+std::vector<uint32_t> ifm2sv_dim_252 = {8, 10, 2, 6};
+uint32_t ifm2sv_size_252 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_252 = {
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 40, 5, 23}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_252 = 0;
+bool has_l1_wts_write_access_pattern_252 = false;
+std::vector<access_pattern> l1_wts_write_pattern_252 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_252 = {};
+
+
+std::vector<uint32_t> ofm_dim_252 = {8, 40, 8, 24};
+std::vector<uint32_t> ofm_bound_252 = {8, 40, 5, 23};
+std::vector<uint32_t> ofmsv_dim_252 = {8, 10, 2, 6};
+uint32_t ofmsv_size_252 = 960;
+uint32_t ofm_repetition_252 = 1;
+bool has_l1_read_access_pattern_252 = false;
+
+std::vector<access_pattern> l1_read_pattern_252 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_252 = {
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 6}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 6}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 6}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 6}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 0, 18}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 2, 18}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 4, 18}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 40, 8, 24}, .tiling_dimension = {8, 10, 2, 6}, .offset = {0, 0, 6, 18}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 257
+// LayerName: Conv_399
+std::vector<uint32_t> ifm_dim_257 = {8, 80, 14, 45};
+std::vector<uint32_t> ifm_bound_257 = {8, 80, 14, 45};
+std::vector<uint32_t> ifmsv_dim_257 = {8, 18, 2, 14};
+uint32_t ifmsv_size_257 = 4032;
+uint32_t kernel_iter_257 = 35;
+bool has_l1_write_access_pattern_257 = false;
+std::vector<access_pattern> l1_write_pattern_257 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_257 = {
+{
+  tiling({.buffer_dimension = {8, 80, 14, 45}, .tiling_dimension = {8, 18, 2, 14}, .offset = {0, -1, 0, -1}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 7}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 14, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 14, 45}, .tiling_dimension = {8, 18, 2, 14}, .offset = {0, -1, 0, 11}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 7}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 14, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 14, 45}, .tiling_dimension = {8, 18, 2, 14}, .offset = {0, -1, 0, 23}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 7}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 14, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 14, 45}, .tiling_dimension = {8, 18, 2, 14}, .offset = {0, -1, 0, 35}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 7}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 14, 45}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_257 = {66304};
+std::vector<uint32_t> wts_dim_257 = {66304};
+std::vector<uint32_t> wtssv_dim_257 = {2368};
+uint32_t wtssv_size_257 = 2368;
+uint32_t wts_repetition_257 = 1;
+bool has_l1_wts_write_access_pattern_257 = false;
+std::vector<access_pattern> l1_wts_write_pattern_257 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_257 = {
+{
+  tiling({.buffer_dimension = {16576, 4}, .tiling_dimension = {2368, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 7} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {16576, 4}, .tiling_dimension = {2368, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 7} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {16576, 4}, .tiling_dimension = {2368, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 7} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {16576, 4}, .tiling_dimension = {2368, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 7} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_257[] = {
+{
+  tiling({.buffer_dimension = {66304, 1}, .tiling_dimension = {33152, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {66304, 1}, .tiling_dimension = {33152, 1}, .offset = {33152, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_257[] = {
+{
+  tiling({.buffer_dimension = {66304}, .tiling_dimension = {33152}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {66304}, .tiling_dimension = {33152}, .offset = {33152}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_257 = {8, 80, 8, 48};
+std::vector<uint32_t> ofm_bound_257 = {8, 80, 5, 45};
+std::vector<uint32_t> ofmsv_dim_257 = {8, 16, 2, 12};
+uint32_t ofmsv_size_257 = 3072;
+uint32_t ofm_repetition_257 = 7;
+bool has_l1_read_access_pattern_257 = false;
+
+std::vector<access_pattern> l1_read_pattern_257 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_257 = {
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 4, 12}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 6, 12}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 2, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 4, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 6, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 2, 36}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 4, 36}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 6, 36}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 261
+// LayerName: Conv_403
+std::vector<uint32_t> ifm_dim_261 = {8, 80, 5, 45};
+std::vector<uint32_t> ifm_bound_261 = {8, 80, 5, 45};
+std::vector<uint32_t> ifmsv_dim_261 = {8, 18, 2, 14};
+uint32_t ifmsv_size_261 = 4032;
+uint32_t kernel_iter_261 = 15;
+bool has_l1_write_access_pattern_261 = false;
+std::vector<access_pattern> l1_write_pattern_261 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_261 = {
+{
+  tiling({.buffer_dimension = {8, 80, 5, 45}, .tiling_dimension = {8, 18, 2, 14}, .offset = {0, -1, 0, -1}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 3}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 5, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 5, 45}, .tiling_dimension = {8, 18, 2, 14}, .offset = {0, -1, 0, 11}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 3}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 5, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 5, 45}, .tiling_dimension = {8, 18, 2, 14}, .offset = {0, -1, 0, 23}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 3}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 5, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 5, 45}, .tiling_dimension = {8, 18, 2, 14}, .offset = {0, -1, 0, 35}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 3}, {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 5, 45}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_261 = {28416};
+std::vector<uint32_t> wts_dim_261 = {28416};
+std::vector<uint32_t> wtssv_dim_261 = {2368};
+uint32_t wtssv_size_261 = 2368;
+uint32_t wts_repetition_261 = 1;
+bool has_l1_wts_write_access_pattern_261 = false;
+std::vector<access_pattern> l1_wts_write_pattern_261 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_261 = {
+{
+  tiling({.buffer_dimension = {7104, 4}, .tiling_dimension = {2368, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 3} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {7104, 4}, .tiling_dimension = {2368, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 3} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {7104, 4}, .tiling_dimension = {2368, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 3} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {7104, 4}, .tiling_dimension = {2368, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 2368, .wrap = 3} }, .packet_port_id = -1, .repetition = 5, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_261[] = {
+{
+  tiling({.buffer_dimension = {28416, 1}, .tiling_dimension = {14208, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {28416, 1}, .tiling_dimension = {14208, 1}, .offset = {14208, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_261[] = {
+{
+  tiling({.buffer_dimension = {28416}, .tiling_dimension = {14208}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {28416}, .tiling_dimension = {14208}, .offset = {14208}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_261 = {8, 80, 8, 48};
+std::vector<uint32_t> ofm_bound_261 = {8, 80, 5, 45};
+std::vector<uint32_t> ofmsv_dim_261 = {8, 16, 2, 12};
+uint32_t ofmsv_size_261 = 3072;
+uint32_t ofm_repetition_261 = 3;
+bool has_l1_read_access_pattern_261 = false;
+
+std::vector<access_pattern> l1_read_pattern_261 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_261 = {
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 4, 12}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 6, 12}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 2, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 4, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 6, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 2, 36}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 4, 36}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 16, 2, 12}, .offset = {0, 0, 6, 36}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 262
+// LayerName: Sigmoid_404
+std::vector<uint32_t> ifm_dim_262 = {8, 80, 8, 48};
+std::vector<uint32_t> ifm_bound_262 = {8, 80, 5, 45};
+std::vector<uint32_t> ifmsv_dim_262 = {8, 10, 2, 12};
+uint32_t ifmsv_size_262 = 7680;
+uint32_t kernel_iter_262 = 8;
+bool has_l1_write_access_pattern_262 = false;
+std::vector<access_pattern> l1_write_pattern_262 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_262 = {
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 10, 2, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 5, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 10, 2, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 5, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 10, 2, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 5, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 10, 2, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 5, 45}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_262 = 0;
+bool has_l1_wts_write_access_pattern_262 = false;
+std::vector<access_pattern> l1_wts_write_pattern_262 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_262 = {};
+
+
+std::vector<uint32_t> ofm_dim_262 = {8, 80, 8, 48};
+std::vector<uint32_t> ofm_bound_262 = {8, 80, 5, 45};
+std::vector<uint32_t> ofmsv_dim_262 = {8, 10, 2, 12};
+uint32_t ofmsv_size_262 = 1920;
+uint32_t ofm_repetition_262 = 1;
+bool has_l1_read_access_pattern_262 = false;
+
+std::vector<access_pattern> l1_read_pattern_262 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_262 = {
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 10, 2, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 10, 2, 12}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 10, 2, 12}, .offset = {0, 0, 4, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 10, 2, 12}, .offset = {0, 0, 6, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 10, 2, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 10, 2, 12}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 10, 2, 12}, .offset = {0, 0, 4, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 10, 2, 12}, .offset = {0, 0, 6, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 10, 2, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 10, 2, 12}, .offset = {0, 0, 2, 24}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 10, 2, 12}, .offset = {0, 0, 4, 24}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 10, 2, 12}, .offset = {0, 0, 6, 24}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 10, 2, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 10, 2, 12}, .offset = {0, 0, 2, 36}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 10, 2, 12}, .offset = {0, 0, 4, 36}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 8, 48}, .tiling_dimension = {8, 10, 2, 12}, .offset = {0, 0, 6, 36}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 264
+// LayerName: Sub_411
+std::vector<uint32_t> ifm_dim_264 = {8, 80, 3, 45};
+std::vector<uint32_t> ifm_bound_264 = {8, 80, 3, 45};
+std::vector<uint32_t> ifmsv_dim_264 = {8, 10, 1, 12};
+uint32_t ifmsv_size_264 = 3840;
+uint32_t kernel_iter_264 = 8;
+bool has_l1_write_access_pattern_264 = false;
+std::vector<access_pattern> l1_write_pattern_264 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_264 = {
+{
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_264 = {8, 80, 3, 45};
+std::vector<uint32_t> ifm2_bound_264 = {8, 80, 3, 45};
+std::vector<uint32_t> ifm2sv_dim_264 = {8, 10, 1, 12};
+uint32_t ifm2sv_size_264 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_264 = {
+{
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_264 = 0;
+bool has_l1_wts_write_access_pattern_264 = false;
+std::vector<access_pattern> l1_wts_write_pattern_264 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_264 = {};
+
+
+std::vector<uint32_t> ofm_dim_264 = {8, 80, 4, 48};
+std::vector<uint32_t> ofm_bound_264 = {8, 80, 3, 45};
+std::vector<uint32_t> ofmsv_dim_264 = {8, 10, 1, 12};
+uint32_t ofmsv_size_264 = 960;
+uint32_t ofm_repetition_264 = 1;
+bool has_l1_read_access_pattern_264 = false;
+
+std::vector<access_pattern> l1_read_pattern_264 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_264 = {
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 1, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 3, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 1, 24}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 2, 24}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 3, 24}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 1, 36}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 2, 36}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 3, 36}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 265
+// LayerName: Mul_412
+std::vector<uint32_t> ifm_dim_265 = {8, 80, 4, 48};
+std::vector<uint32_t> ifm_bound_265 = {8, 80, 3, 45};
+std::vector<uint32_t> ifmsv_dim_265 = {8, 10, 1, 12};
+uint32_t ifmsv_size_265 = 3840;
+uint32_t kernel_iter_265 = 8;
+bool has_l1_write_access_pattern_265 = false;
+std::vector<access_pattern> l1_write_pattern_265 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_265 = {
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_265 = {8, 80, 3, 45};
+std::vector<uint32_t> ifm2_bound_265 = {8, 80, 3, 45};
+std::vector<uint32_t> ifm2sv_dim_265 = {8, 10, 1, 12};
+uint32_t ifm2sv_size_265 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_265 = {
+{
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_265 = 0;
+bool has_l1_wts_write_access_pattern_265 = false;
+std::vector<access_pattern> l1_wts_write_pattern_265 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_265 = {};
+
+
+std::vector<uint32_t> ofm_dim_265 = {8, 80, 4, 48};
+std::vector<uint32_t> ofm_bound_265 = {8, 80, 3, 45};
+std::vector<uint32_t> ofmsv_dim_265 = {8, 10, 1, 12};
+uint32_t ofmsv_size_265 = 960;
+uint32_t ofm_repetition_265 = 1;
+bool has_l1_read_access_pattern_265 = false;
+
+std::vector<access_pattern> l1_read_pattern_265 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_265 = {
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 1, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 3, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 1, 24}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 2, 24}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 3, 24}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 1, 36}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 2, 36}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 3, 36}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 267
+// LayerName: Mul_406
+std::vector<uint32_t> ifm_dim_267 = {8, 80, 3, 45};
+std::vector<uint32_t> ifm_bound_267 = {8, 80, 3, 45};
+std::vector<uint32_t> ifmsv_dim_267 = {8, 10, 1, 12};
+uint32_t ifmsv_size_267 = 3840;
+uint32_t kernel_iter_267 = 8;
+bool has_l1_write_access_pattern_267 = false;
+std::vector<access_pattern> l1_write_pattern_267 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_267 = {
+{
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_267 = {8, 80, 3, 45};
+std::vector<uint32_t> ifm2_bound_267 = {8, 80, 3, 45};
+std::vector<uint32_t> ifm2sv_dim_267 = {8, 10, 1, 12};
+uint32_t ifm2sv_size_267 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_267 = {
+{
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_267 = 0;
+bool has_l1_wts_write_access_pattern_267 = false;
+std::vector<access_pattern> l1_wts_write_pattern_267 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_267 = {};
+
+
+std::vector<uint32_t> ofm_dim_267 = {8, 80, 4, 48};
+std::vector<uint32_t> ofm_bound_267 = {8, 80, 3, 45};
+std::vector<uint32_t> ofmsv_dim_267 = {8, 10, 1, 12};
+uint32_t ofmsv_size_267 = 960;
+uint32_t ofm_repetition_267 = 1;
+bool has_l1_read_access_pattern_267 = false;
+
+std::vector<access_pattern> l1_read_pattern_267 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_267 = {
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 1, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 3, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 1, 24}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 2, 24}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 3, 24}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 1, 36}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 2, 36}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 3, 36}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 269
+// LayerName: Conv_408
+std::vector<uint32_t> ifm_dim_269 = {8, 80, 5, 45};
+std::vector<uint32_t> ifm_bound_269 = {8, 80, 5, 45};
+std::vector<uint32_t> ifmsv_dim_269 = {8, 34, 1, 14};
+uint32_t ifmsv_size_269 = 3808;
+uint32_t kernel_iter_269 = 15;
+bool has_l1_write_access_pattern_269 = false;
+std::vector<access_pattern> l1_write_pattern_269 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_269 = {
+{
+  tiling({.buffer_dimension = {8, 80, 5, 45}, .tiling_dimension = {8, 34, 1, 14}, .offset = {0, -1, 0, -1}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 32, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 5, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 5, 45}, .tiling_dimension = {8, 34, 1, 14}, .offset = {0, -1, 0, 11}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 32, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 5, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 5, 45}, .tiling_dimension = {8, 34, 1, 14}, .offset = {0, -1, 0, 23}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 32, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 5, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 5, 45}, .tiling_dimension = {8, 34, 1, 14}, .offset = {0, -1, 0, 35}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 32, .wrap = 3} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 5, 45}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_269 = {12160};
+std::vector<uint32_t> wts_dim_269 = {12160};
+std::vector<uint32_t> wtssv_dim_269 = {608};
+uint32_t wtssv_size_269 = 608;
+uint32_t wts_repetition_269 = 1;
+bool has_l1_wts_write_access_pattern_269 = false;
+std::vector<access_pattern> l1_wts_write_pattern_269 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_269 = {
+{
+  tiling({.buffer_dimension = {3040, 4}, .tiling_dimension = {608, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 608, .wrap = 5} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {3040, 4}, .tiling_dimension = {608, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 608, .wrap = 5} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {3040, 4}, .tiling_dimension = {608, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 608, .wrap = 5} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {3040, 4}, .tiling_dimension = {608, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 608, .wrap = 5} }, .packet_port_id = -1, .repetition = 3, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_269[] = {
+{
+  tiling({.buffer_dimension = {12160, 1}, .tiling_dimension = {6080, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {12160, 1}, .tiling_dimension = {6080, 1}, .offset = {6080, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_269[] = {
+{
+  tiling({.buffer_dimension = {12160}, .tiling_dimension = {6080}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {12160}, .tiling_dimension = {6080}, .offset = {6080}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_269 = {8, 96, 4, 48};
+std::vector<uint32_t> ofm_bound_269 = {8, 80, 3, 45};
+std::vector<uint32_t> ofmsv_dim_269 = {8, 32, 1, 12};
+uint32_t ofmsv_size_269 = 3072;
+uint32_t ofm_repetition_269 = 5;
+bool has_l1_read_access_pattern_269 = false;
+
+std::vector<access_pattern> l1_read_pattern_269 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_269 = {
+{
+  tiling({.buffer_dimension = {8, 96, 4, 48}, .tiling_dimension = {8, 32, 1, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 4, 48}, .tiling_dimension = {8, 32, 1, 12}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 4, 48}, .tiling_dimension = {8, 32, 1, 12}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 4, 48}, .tiling_dimension = {8, 32, 1, 12}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 96, 4, 48}, .tiling_dimension = {8, 32, 1, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 4, 48}, .tiling_dimension = {8, 32, 1, 12}, .offset = {0, 0, 1, 12}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 4, 48}, .tiling_dimension = {8, 32, 1, 12}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 4, 48}, .tiling_dimension = {8, 32, 1, 12}, .offset = {0, 0, 3, 12}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 96, 4, 48}, .tiling_dimension = {8, 32, 1, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 4, 48}, .tiling_dimension = {8, 32, 1, 12}, .offset = {0, 0, 1, 24}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 4, 48}, .tiling_dimension = {8, 32, 1, 12}, .offset = {0, 0, 2, 24}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 4, 48}, .tiling_dimension = {8, 32, 1, 12}, .offset = {0, 0, 3, 24}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 96, 4, 48}, .tiling_dimension = {8, 32, 1, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 4, 48}, .tiling_dimension = {8, 32, 1, 12}, .offset = {0, 0, 1, 36}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 4, 48}, .tiling_dimension = {8, 32, 1, 12}, .offset = {0, 0, 2, 36}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 96, 4, 48}, .tiling_dimension = {8, 32, 1, 12}, .offset = {0, 0, 3, 36}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 3} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 270
+// LayerName: Tanh_409
+std::vector<uint32_t> ifm_dim_270 = {8, 96, 4, 48};
+std::vector<uint32_t> ifm_bound_270 = {8, 80, 3, 45};
+std::vector<uint32_t> ifmsv_dim_270 = {8, 20, 1, 12};
+uint32_t ifmsv_size_270 = 7680;
+uint32_t kernel_iter_270 = 4;
+bool has_l1_write_access_pattern_270 = false;
+std::vector<access_pattern> l1_write_pattern_270 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_270 = {
+{
+  tiling({.buffer_dimension = {8, 96, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 96, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 96, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 96, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 20, .wrap = 4} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_270 = 0;
+bool has_l1_wts_write_access_pattern_270 = false;
+std::vector<access_pattern> l1_wts_write_pattern_270 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_270 = {};
+
+
+std::vector<uint32_t> ofm_dim_270 = {8, 80, 4, 48};
+std::vector<uint32_t> ofm_bound_270 = {8, 80, 3, 45};
+std::vector<uint32_t> ofmsv_dim_270 = {8, 20, 1, 12};
+uint32_t ofmsv_size_270 = 1920;
+uint32_t ofm_repetition_270 = 1;
+bool has_l1_read_access_pattern_270 = false;
+
+std::vector<access_pattern> l1_read_pattern_270 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_270 = {
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 1, 12}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 3, 12}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 1, 24}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 2, 24}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 3, 24}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 4} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 1, 36}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 4} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 2, 36}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 4} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 20, 1, 12}, .offset = {0, 0, 3, 36}, .tile_traversal = { {.dimension = 1, .stride = 20, .wrap = 4} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 271
+// LayerName: Mul_413
+std::vector<uint32_t> ifm_dim_271 = {8, 80, 3, 45};
+std::vector<uint32_t> ifm_bound_271 = {8, 80, 3, 45};
+std::vector<uint32_t> ifmsv_dim_271 = {8, 10, 1, 12};
+uint32_t ifmsv_size_271 = 3840;
+uint32_t kernel_iter_271 = 8;
+bool has_l1_write_access_pattern_271 = false;
+std::vector<access_pattern> l1_write_pattern_271 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_271 = {
+{
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 3, 45}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_271 = {8, 80, 4, 48};
+std::vector<uint32_t> ifm2_bound_271 = {8, 80, 3, 45};
+std::vector<uint32_t> ifm2sv_dim_271 = {8, 10, 1, 12};
+uint32_t ifm2sv_size_271 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_271 = {
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_271 = 0;
+bool has_l1_wts_write_access_pattern_271 = false;
+std::vector<access_pattern> l1_wts_write_pattern_271 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_271 = {};
+
+
+std::vector<uint32_t> ofm_dim_271 = {8, 80, 4, 48};
+std::vector<uint32_t> ofm_bound_271 = {8, 80, 3, 45};
+std::vector<uint32_t> ofmsv_dim_271 = {8, 10, 1, 12};
+uint32_t ofmsv_size_271 = 960;
+uint32_t ofm_repetition_271 = 1;
+bool has_l1_read_access_pattern_271 = false;
+
+std::vector<access_pattern> l1_read_pattern_271 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_271 = {
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 1, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 3, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 1, 24}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 2, 24}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 3, 24}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 1, 36}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 2, 36}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 3, 36}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 272
+// LayerName: Add_414
+std::vector<uint32_t> ifm_dim_272 = {8, 80, 4, 48};
+std::vector<uint32_t> ifm_bound_272 = {8, 80, 3, 45};
+std::vector<uint32_t> ifmsv_dim_272 = {8, 10, 1, 12};
+uint32_t ifmsv_size_272 = 3840;
+uint32_t kernel_iter_272 = 8;
+bool has_l1_write_access_pattern_272 = false;
+std::vector<access_pattern> l1_write_pattern_272 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_272 = {
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_272 = {8, 80, 4, 48};
+std::vector<uint32_t> ifm2_bound_272 = {8, 80, 3, 45};
+std::vector<uint32_t> ifm2sv_dim_272 = {8, 10, 1, 12};
+uint32_t ifm2sv_size_272 = 3840;
+std::vector<std::vector<access_pattern>> ifm2_pattern_272 = {
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 80, 3, 45}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_272 = 0;
+bool has_l1_wts_write_access_pattern_272 = false;
+std::vector<access_pattern> l1_wts_write_pattern_272 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_272 = {};
+
+
+std::vector<uint32_t> ofm_dim_272 = {8, 80, 4, 48};
+std::vector<uint32_t> ofm_bound_272 = {8, 80, 3, 45};
+std::vector<uint32_t> ofmsv_dim_272 = {8, 10, 1, 12};
+uint32_t ofmsv_size_272 = 960;
+uint32_t ofm_repetition_272 = 1;
+bool has_l1_read_access_pattern_272 = false;
+
+std::vector<access_pattern> l1_read_pattern_272 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_272 = {
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 1, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 3, 12}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 1, 24}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 2, 24}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 3, 24}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 0, 36}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 1, 36}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 2, 36}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 80, 4, 48}, .tiling_dimension = {8, 10, 1, 12}, .offset = {0, 0, 3, 36}, .tile_traversal = { {.dimension = 1, .stride = 10, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 276
+// LayerName: Conv_419
+std::vector<uint32_t> ifm_dim_276 = {8, 160, 8, 20};
+std::vector<uint32_t> ifm_bound_276 = {8, 160, 8, 20};
+std::vector<uint32_t> ifmsv_dim_276 = {8, 34, 2, 7};
+uint32_t ifmsv_size_276 = 3808;
+uint32_t kernel_iter_276 = 100;
+bool has_l1_write_access_pattern_276 = false;
+std::vector<access_pattern> l1_write_pattern_276 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_276 = {
+{
+  tiling({.buffer_dimension = {8, 160, 8, 19}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, -1}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 20}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 160, 8, 20}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2}),
+  tiling({.buffer_dimension = {8, 160, 8, 20}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 3}),
+  tiling({.buffer_dimension = {8, 160, 8, 19}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 4})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 8, 19}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 20}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 5}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 160, 8, 20}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 5}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2}),
+  tiling({.buffer_dimension = {8, 160, 8, 20}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 5}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 3}),
+  tiling({.buffer_dimension = {8, 160, 8, 19}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 5}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 4})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 8, 19}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 9}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 20}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 10}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 160, 8, 20}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 10}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2}),
+  tiling({.buffer_dimension = {8, 160, 8, 20}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 10}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 3}),
+  tiling({.buffer_dimension = {8, 160, 8, 19}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 10}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 4})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 8, 19}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 14}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 8, 20}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 15}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 160, 8, 20}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 15}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2}),
+  tiling({.buffer_dimension = {8, 160, 8, 20}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 15}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 3}),
+  tiling({.buffer_dimension = {8, 160, 8, 19}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 15}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 4})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_276 = {18944};
+std::vector<uint32_t> wts_dim_276 = {18944};
+std::vector<uint32_t> wtssv_dim_276 = {1184};
+uint32_t wtssv_size_276 = 1184;
+uint32_t wts_repetition_276 = 1;
+bool has_l1_wts_write_access_pattern_276 = false;
+std::vector<access_pattern> l1_wts_write_pattern_276 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_276 = {
+{
+  tiling({.buffer_dimension = {4736, 4}, .tiling_dimension = {1184, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 1184, .wrap = 4} }, .packet_port_id = -1, .repetition = 25, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4736, 4}, .tiling_dimension = {1184, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 1184, .wrap = 4} }, .packet_port_id = -1, .repetition = 25, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4736, 4}, .tiling_dimension = {1184, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 1184, .wrap = 4} }, .packet_port_id = -1, .repetition = 25, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4736, 4}, .tiling_dimension = {1184, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 1184, .wrap = 4} }, .packet_port_id = -1, .repetition = 25, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_276[] = {
+{
+  tiling({.buffer_dimension = {18944, 1}, .tiling_dimension = {9472, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {18944, 1}, .tiling_dimension = {9472, 1}, .offset = {9472, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_276[] = {
+{
+  tiling({.buffer_dimension = {18944}, .tiling_dimension = {9472}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {18944}, .tiling_dimension = {9472}, .offset = {9472}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_276 = {8, 160, 4, 20};
+std::vector<uint32_t> ofm_bound_276 = {8, 160, 4, 18};
+std::vector<uint32_t> ofmsv_dim_276 = {8, 32, 1, 5};
+uint32_t ofmsv_size_276 = 1280;
+uint32_t ofm_repetition_276 = 4;
+bool has_l1_read_access_pattern_276 = false;
+
+std::vector<access_pattern> l1_read_pattern_276 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_276 = {
+{
+  tiling({.buffer_dimension = {8, 160, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 0, 5}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 1, 5}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 2, 5}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 3, 5}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 1, 10}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 2, 10}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 3, 10}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 1, 15}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 2, 15}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 3, 15}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 280
+// LayerName: Conv_423
+std::vector<uint32_t> ifm_dim_280 = {8, 160, 4, 32};
+std::vector<uint32_t> ifm_bound_280 = {8, 160, 4, 32};
+std::vector<uint32_t> ifmsv_dim_280 = {8, 34, 2, 6};
+uint32_t ifmsv_size_280 = 3264;
+uint32_t kernel_iter_280 = 60;
+bool has_l1_write_access_pattern_280 = false;
+std::vector<access_pattern> l1_write_pattern_280 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_280 = {
+{
+  tiling({.buffer_dimension = {8, 160, 4, 31}, .tiling_dimension = {8, 34, 2, 6}, .offset = {0, -1, 0, -1}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 2}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 34, 2, 6}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 2}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 160, 4, 31}, .tiling_dimension = {8, 34, 2, 6}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 2}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 31}, .tiling_dimension = {8, 34, 2, 6}, .offset = {0, -1, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 2}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 34, 2, 6}, .offset = {0, -1, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 2}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 160, 4, 31}, .tiling_dimension = {8, 34, 2, 6}, .offset = {0, -1, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 2}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 31}, .tiling_dimension = {8, 34, 2, 6}, .offset = {0, -1, 0, 7}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 2}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 34, 2, 6}, .offset = {0, -1, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 2}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 160, 4, 31}, .tiling_dimension = {8, 34, 2, 6}, .offset = {0, -1, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 2}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 31}, .tiling_dimension = {8, 34, 2, 6}, .offset = {0, -1, 0, 11}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 2}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 34, 2, 6}, .offset = {0, -1, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 2}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 160, 4, 31}, .tiling_dimension = {8, 34, 2, 6}, .offset = {0, -1, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 2}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_280 = {9472};
+std::vector<uint32_t> wts_dim_280 = {9472};
+std::vector<uint32_t> wtssv_dim_280 = {1184};
+uint32_t wtssv_size_280 = 1184;
+uint32_t wts_repetition_280 = 1;
+bool has_l1_wts_write_access_pattern_280 = false;
+std::vector<access_pattern> l1_wts_write_pattern_280 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_280 = {
+{
+  tiling({.buffer_dimension = {2368, 4}, .tiling_dimension = {1184, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 1184, .wrap = 2} }, .packet_port_id = -1, .repetition = 30, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2368, 4}, .tiling_dimension = {1184, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 1184, .wrap = 2} }, .packet_port_id = -1, .repetition = 30, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2368, 4}, .tiling_dimension = {1184, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 1184, .wrap = 2} }, .packet_port_id = -1, .repetition = 30, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2368, 4}, .tiling_dimension = {1184, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 1184, .wrap = 2} }, .packet_port_id = -1, .repetition = 30, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_280[] = {
+{
+  tiling({.buffer_dimension = {9472, 1}, .tiling_dimension = {4736, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {9472, 1}, .tiling_dimension = {4736, 1}, .offset = {4736, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_280[] = {
+{
+  tiling({.buffer_dimension = {9472}, .tiling_dimension = {4736}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {9472}, .tiling_dimension = {4736}, .offset = {4736}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_280 = {8, 160, 4, 32};
+std::vector<uint32_t> ofm_bound_280 = {8, 160, 4, 30};
+std::vector<uint32_t> ofmsv_dim_280 = {8, 32, 1, 4};
+uint32_t ofmsv_size_280 = 1024;
+uint32_t ofm_repetition_280 = 2;
+bool has_l1_read_access_pattern_280 = false;
+
+std::vector<access_pattern> l1_read_pattern_280 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_280 = {
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 1, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 2, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 3, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 1, 8}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 2, 8}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 3, 8}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 1, 12}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 3, 12}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 281
+// LayerName: Sigmoid_424
+std::vector<uint32_t> ifm_dim_281 = {8, 160, 4, 30};
+std::vector<uint32_t> ifm_bound_281 = {8, 160, 4, 30};
+std::vector<uint32_t> ifmsv_dim_281 = {8, 32, 1, 8};
+uint32_t ifmsv_size_281 = 8192;
+uint32_t kernel_iter_281 = 15;
+bool has_l1_write_access_pattern_281 = false;
+std::vector<access_pattern> l1_write_pattern_281 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_281 = {
+{
+  tiling({.buffer_dimension = {8, 160, 4, 30}, .tiling_dimension = {8, 32, 1, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 30}, .tiling_dimension = {8, 32, 1, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 30}, .tiling_dimension = {8, 32, 1, 8}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 30}, .tiling_dimension = {8, 32, 1, 8}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_281 = 0;
+bool has_l1_wts_write_access_pattern_281 = false;
+std::vector<access_pattern> l1_wts_write_pattern_281 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_281 = {};
+
+
+std::vector<uint32_t> ofm_dim_281 = {8, 160, 4, 32};
+std::vector<uint32_t> ofm_bound_281 = {8, 160, 4, 30};
+std::vector<uint32_t> ofmsv_dim_281 = {8, 32, 1, 8};
+uint32_t ofmsv_size_281 = 2048;
+uint32_t ofm_repetition_281 = 1;
+bool has_l1_read_access_pattern_281 = false;
+
+std::vector<access_pattern> l1_read_pattern_281 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_281 = {
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 8}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 8}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 8}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 8}, .offset = {0, 0, 1, 8}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 8}, .offset = {0, 0, 2, 8}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 8}, .offset = {0, 0, 3, 8}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 8}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 8}, .offset = {0, 0, 1, 16}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 8}, .offset = {0, 0, 2, 16}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 8}, .offset = {0, 0, 3, 16}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 8}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 8}, .offset = {0, 0, 1, 24}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 8}, .offset = {0, 0, 2, 24}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 8}, .offset = {0, 0, 3, 24}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 283
+// LayerName: Sub_431
+std::vector<uint32_t> ifm_dim_283 = {8, 160, 2, 30};
+std::vector<uint32_t> ifm_bound_283 = {8, 160, 2, 30};
+std::vector<uint32_t> ifmsv_dim_283 = {8, 16, 1, 8};
+uint32_t ifmsv_size_283 = 4096;
+uint32_t kernel_iter_283 = 30;
+bool has_l1_write_access_pattern_283 = false;
+std::vector<access_pattern> l1_write_pattern_283 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_283 = {
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_283 = {8, 160, 2, 30};
+std::vector<uint32_t> ifm2_bound_283 = {8, 160, 2, 30};
+std::vector<uint32_t> ifm2sv_dim_283 = {8, 16, 1, 8};
+uint32_t ifm2sv_size_283 = 4096;
+std::vector<std::vector<access_pattern>> ifm2_pattern_283 = {
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_283 = 0;
+bool has_l1_wts_write_access_pattern_283 = false;
+std::vector<access_pattern> l1_wts_write_pattern_283 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_283 = {};
+
+
+std::vector<uint32_t> ofm_dim_283 = {8, 160, 4, 32};
+std::vector<uint32_t> ofm_bound_283 = {8, 160, 2, 30};
+std::vector<uint32_t> ofmsv_dim_283 = {8, 16, 1, 8};
+uint32_t ofmsv_size_283 = 1024;
+uint32_t ofm_repetition_283 = 1;
+bool has_l1_read_access_pattern_283 = false;
+
+std::vector<access_pattern> l1_read_pattern_283 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_283 = {
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 1, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 2, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 3, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 1, 16}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 2, 16}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 3, 16}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 1, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 2, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 3, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 284
+// LayerName: Mul_432
+std::vector<uint32_t> ifm_dim_284 = {8, 160, 2, 30};
+std::vector<uint32_t> ifm_bound_284 = {8, 160, 2, 30};
+std::vector<uint32_t> ifmsv_dim_284 = {8, 16, 1, 8};
+uint32_t ifmsv_size_284 = 4096;
+uint32_t kernel_iter_284 = 30;
+bool has_l1_write_access_pattern_284 = false;
+std::vector<access_pattern> l1_write_pattern_284 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_284 = {
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_284 = {8, 160, 2, 30};
+std::vector<uint32_t> ifm2_bound_284 = {8, 160, 2, 30};
+std::vector<uint32_t> ifm2sv_dim_284 = {8, 16, 1, 8};
+uint32_t ifm2sv_size_284 = 4096;
+std::vector<std::vector<access_pattern>> ifm2_pattern_284 = {
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_284 = 0;
+bool has_l1_wts_write_access_pattern_284 = false;
+std::vector<access_pattern> l1_wts_write_pattern_284 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_284 = {};
+
+
+std::vector<uint32_t> ofm_dim_284 = {8, 160, 4, 32};
+std::vector<uint32_t> ofm_bound_284 = {8, 160, 2, 30};
+std::vector<uint32_t> ofmsv_dim_284 = {8, 16, 1, 8};
+uint32_t ofmsv_size_284 = 1024;
+uint32_t ofm_repetition_284 = 1;
+bool has_l1_read_access_pattern_284 = false;
+
+std::vector<access_pattern> l1_read_pattern_284 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_284 = {
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 1, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 2, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 3, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 1, 16}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 2, 16}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 3, 16}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 1, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 2, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 3, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 286
+// LayerName: Mul_426
+std::vector<uint32_t> ifm_dim_286 = {8, 160, 2, 30};
+std::vector<uint32_t> ifm_bound_286 = {8, 160, 2, 30};
+std::vector<uint32_t> ifmsv_dim_286 = {8, 16, 1, 8};
+uint32_t ifmsv_size_286 = 4096;
+uint32_t kernel_iter_286 = 30;
+bool has_l1_write_access_pattern_286 = false;
+std::vector<access_pattern> l1_write_pattern_286 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_286 = {
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_286 = {8, 160, 2, 30};
+std::vector<uint32_t> ifm2_bound_286 = {8, 160, 2, 30};
+std::vector<uint32_t> ifm2sv_dim_286 = {8, 16, 1, 8};
+uint32_t ifm2sv_size_286 = 4096;
+std::vector<std::vector<access_pattern>> ifm2_pattern_286 = {
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_286 = 0;
+bool has_l1_wts_write_access_pattern_286 = false;
+std::vector<access_pattern> l1_wts_write_pattern_286 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_286 = {};
+
+
+std::vector<uint32_t> ofm_dim_286 = {8, 160, 4, 32};
+std::vector<uint32_t> ofm_bound_286 = {8, 160, 2, 30};
+std::vector<uint32_t> ofmsv_dim_286 = {8, 16, 1, 8};
+uint32_t ofmsv_size_286 = 1024;
+uint32_t ofm_repetition_286 = 1;
+bool has_l1_read_access_pattern_286 = false;
+
+std::vector<access_pattern> l1_read_pattern_286 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_286 = {
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 1, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 2, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 3, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 1, 16}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 2, 16}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 3, 16}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 1, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 2, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 3, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 288
+// LayerName: Conv_428
+std::vector<uint32_t> ifm_dim_288 = {8, 160, 4, 32};
+std::vector<uint32_t> ifm_bound_288 = {8, 160, 4, 32};
+std::vector<uint32_t> ifmsv_dim_288 = {8, 34, 2, 6};
+uint32_t ifmsv_size_288 = 3264;
+uint32_t kernel_iter_288 = 60;
+bool has_l1_write_access_pattern_288 = false;
+std::vector<access_pattern> l1_write_pattern_288 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_288 = {
+{
+  tiling({.buffer_dimension = {8, 160, 4, 31}, .tiling_dimension = {8, 34, 2, 6}, .offset = {0, -1, 0, -1}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 2}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 34, 2, 6}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 2}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 160, 4, 31}, .tiling_dimension = {8, 34, 2, 6}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 2}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 31}, .tiling_dimension = {8, 34, 2, 6}, .offset = {0, -1, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 2}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 34, 2, 6}, .offset = {0, -1, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 2}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 160, 4, 31}, .tiling_dimension = {8, 34, 2, 6}, .offset = {0, -1, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 2}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 31}, .tiling_dimension = {8, 34, 2, 6}, .offset = {0, -1, 0, 7}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 2}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 34, 2, 6}, .offset = {0, -1, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 2}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 160, 4, 31}, .tiling_dimension = {8, 34, 2, 6}, .offset = {0, -1, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 2}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 31}, .tiling_dimension = {8, 34, 2, 6}, .offset = {0, -1, 0, 11}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 2}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 34, 2, 6}, .offset = {0, -1, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 2}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 160, 4, 31}, .tiling_dimension = {8, 34, 2, 6}, .offset = {0, -1, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 2, .wrap = 2}, {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_288 = {9472};
+std::vector<uint32_t> wts_dim_288 = {9472};
+std::vector<uint32_t> wtssv_dim_288 = {1184};
+uint32_t wtssv_size_288 = 1184;
+uint32_t wts_repetition_288 = 1;
+bool has_l1_wts_write_access_pattern_288 = false;
+std::vector<access_pattern> l1_wts_write_pattern_288 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_288 = {
+{
+  tiling({.buffer_dimension = {2368, 4}, .tiling_dimension = {1184, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 1184, .wrap = 2} }, .packet_port_id = -1, .repetition = 30, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2368, 4}, .tiling_dimension = {1184, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 1184, .wrap = 2} }, .packet_port_id = -1, .repetition = 30, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2368, 4}, .tiling_dimension = {1184, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 1184, .wrap = 2} }, .packet_port_id = -1, .repetition = 30, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2368, 4}, .tiling_dimension = {1184, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 1184, .wrap = 2} }, .packet_port_id = -1, .repetition = 30, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_288[] = {
+{
+  tiling({.buffer_dimension = {9472, 1}, .tiling_dimension = {4736, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {9472, 1}, .tiling_dimension = {4736, 1}, .offset = {4736, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_288[] = {
+{
+  tiling({.buffer_dimension = {9472}, .tiling_dimension = {4736}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {9472}, .tiling_dimension = {4736}, .offset = {4736}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_288 = {8, 160, 4, 32};
+std::vector<uint32_t> ofm_bound_288 = {8, 160, 2, 30};
+std::vector<uint32_t> ofmsv_dim_288 = {8, 32, 1, 4};
+uint32_t ofmsv_size_288 = 1024;
+uint32_t ofm_repetition_288 = 2;
+bool has_l1_read_access_pattern_288 = false;
+
+std::vector<access_pattern> l1_read_pattern_288 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_288 = {
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 1, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 2, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 3, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 1, 8}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 2, 8}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 3, 8}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 1, 12}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 32, 1, 4}, .offset = {0, 0, 3, 12}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 5}, {.dimension = 3, .stride = 16, .wrap = 2} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 289
+// LayerName: Tanh_429
+std::vector<uint32_t> ifm_dim_289 = {8, 160, 2, 90};
+std::vector<uint32_t> ifm_bound_289 = {8, 160, 2, 90};
+std::vector<uint32_t> ifmsv_dim_289 = {8, 8, 1, 23};
+uint32_t ifmsv_size_289 = 5888;
+uint32_t kernel_iter_289 = 20;
+bool has_l1_write_access_pattern_289 = false;
+std::vector<access_pattern> l1_write_pattern_289 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_289 = {
+{
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 160, 2, 90}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 0, 23}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 160, 2, 90}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 0, 46}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 160, 2, 90}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 90}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 0, 69}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {8, 160, 2, 90}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_289 = 0;
+bool has_l1_wts_write_access_pattern_289 = false;
+std::vector<access_pattern> l1_wts_write_pattern_289 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_289 = {};
+
+
+std::vector<uint32_t> ofm_dim_289 = {8, 160, 4, 92};
+std::vector<uint32_t> ofm_bound_289 = {8, 160, 2, 90};
+std::vector<uint32_t> ofmsv_dim_289 = {8, 8, 1, 23};
+uint32_t ofmsv_size_289 = 1472;
+uint32_t ofm_repetition_289 = 1;
+bool has_l1_read_access_pattern_289 = false;
+
+std::vector<access_pattern> l1_read_pattern_289 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_289 = {
+{
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 0, 23}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 1, 23}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 2, 23}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 3, 23}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 0, 46}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 1, 46}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 2, 46}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 3, 46}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 0, 69}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 1, 69}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 2, 69}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 92}, .tiling_dimension = {8, 8, 1, 23}, .offset = {0, 0, 3, 69}, .tile_traversal = { {.dimension = 1, .stride = 8, .wrap = 20} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 290
+// LayerName: Mul_433
+std::vector<uint32_t> ifm_dim_290 = {8, 160, 2, 30};
+std::vector<uint32_t> ifm_bound_290 = {8, 160, 2, 30};
+std::vector<uint32_t> ifmsv_dim_290 = {8, 16, 1, 8};
+uint32_t ifmsv_size_290 = 4096;
+uint32_t kernel_iter_290 = 30;
+bool has_l1_write_access_pattern_290 = false;
+std::vector<access_pattern> l1_write_pattern_290 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_290 = {
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_290 = {8, 160, 2, 30};
+std::vector<uint32_t> ifm2_bound_290 = {8, 160, 2, 30};
+std::vector<uint32_t> ifm2sv_dim_290 = {8, 16, 1, 8};
+uint32_t ifm2sv_size_290 = 4096;
+std::vector<std::vector<access_pattern>> ifm2_pattern_290 = {
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_290 = 0;
+bool has_l1_wts_write_access_pattern_290 = false;
+std::vector<access_pattern> l1_wts_write_pattern_290 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_290 = {};
+
+
+std::vector<uint32_t> ofm_dim_290 = {8, 160, 4, 32};
+std::vector<uint32_t> ofm_bound_290 = {8, 160, 2, 30};
+std::vector<uint32_t> ofmsv_dim_290 = {8, 16, 1, 8};
+uint32_t ofmsv_size_290 = 1024;
+uint32_t ofm_repetition_290 = 1;
+bool has_l1_read_access_pattern_290 = false;
+
+std::vector<access_pattern> l1_read_pattern_290 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_290 = {
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 1, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 2, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 3, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 1, 16}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 2, 16}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 3, 16}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 1, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 2, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 3, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 291
+// LayerName: Add_434
+std::vector<uint32_t> ifm_dim_291 = {8, 160, 2, 30};
+std::vector<uint32_t> ifm_bound_291 = {8, 160, 2, 30};
+std::vector<uint32_t> ifmsv_dim_291 = {8, 16, 1, 8};
+uint32_t ifmsv_size_291 = 4096;
+uint32_t kernel_iter_291 = 30;
+bool has_l1_write_access_pattern_291 = false;
+std::vector<access_pattern> l1_write_pattern_291 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_291 = {
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_291 = {8, 160, 2, 30};
+std::vector<uint32_t> ifm2_bound_291 = {8, 160, 2, 30};
+std::vector<uint32_t> ifm2sv_dim_291 = {8, 16, 1, 8};
+uint32_t ifm2sv_size_291 = 4096;
+std::vector<std::vector<access_pattern>> ifm2_pattern_291 = {
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 2, 30}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_291 = 0;
+bool has_l1_wts_write_access_pattern_291 = false;
+std::vector<access_pattern> l1_wts_write_pattern_291 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_291 = {};
+
+
+std::vector<uint32_t> ofm_dim_291 = {8, 160, 4, 32};
+std::vector<uint32_t> ofm_bound_291 = {8, 160, 2, 30};
+std::vector<uint32_t> ofmsv_dim_291 = {8, 16, 1, 8};
+uint32_t ofmsv_size_291 = 1024;
+uint32_t ofm_repetition_291 = 1;
+bool has_l1_read_access_pattern_291 = false;
+
+std::vector<access_pattern> l1_read_pattern_291 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_291 = {
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 1, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 2, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 3, 8}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 16}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 1, 16}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 2, 16}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 3, 16}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 0, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 1, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 2, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 160, 4, 32}, .tiling_dimension = {8, 16, 1, 8}, .offset = {0, 0, 3, 24}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 295
+// LayerName: Conv_439
+std::vector<uint32_t> ifm_dim_295 = {8, 320, 5, 17};
+std::vector<uint32_t> ifm_bound_295 = {8, 320, 5, 17};
+std::vector<uint32_t> ifmsv_dim_295 = {8, 66, 1, 6};
+uint32_t ifmsv_size_295 = 3168;
+uint32_t kernel_iter_295 = 300;
+bool has_l1_write_access_pattern_295 = false;
+std::vector<access_pattern> l1_write_pattern_295 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_295 = {
+{
+  tiling({.buffer_dimension = {8, 320, 5, 16}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, -1}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 3}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 4}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 5}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 6}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 7}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 8}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 9}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 10}),
+  tiling({.buffer_dimension = {8, 320, 5, 16}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 11})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 5, 16}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 3}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 3}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 4}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 5}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 6}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 7}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 8}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 9}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 10}),
+  tiling({.buffer_dimension = {8, 320, 5, 16}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 4}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 11})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 5, 16}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 7}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 3}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 4}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 5}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 6}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 7}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 8}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 9}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 10}),
+  tiling({.buffer_dimension = {8, 320, 5, 16}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 8}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 11})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 5, 16}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 11}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 3}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 4}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 5}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 6}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 7}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 8}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 9}),
+  tiling({.buffer_dimension = {8, 320, 5, 17}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 10}),
+  tiling({.buffer_dimension = {8, 320, 5, 16}, .tiling_dimension = {8, 66, 1, 6}, .offset = {0, -1, 0, 12}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 5}, {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 11})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_295 = {12160};
+std::vector<uint32_t> wts_dim_295 = {12160};
+std::vector<uint32_t> wtssv_dim_295 = {608};
+uint32_t wtssv_size_295 = 608;
+uint32_t wts_repetition_295 = 1;
+bool has_l1_wts_write_access_pattern_295 = false;
+std::vector<access_pattern> l1_wts_write_pattern_295 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_295 = {
+{
+  tiling({.buffer_dimension = {3040, 4}, .tiling_dimension = {608, 1}, .offset = {0, 0}, .tile_traversal = { {.dimension = 0, .stride = 608, .wrap = 5} }, .packet_port_id = -1, .repetition = 60, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {3040, 4}, .tiling_dimension = {608, 1}, .offset = {0, 1}, .tile_traversal = { {.dimension = 0, .stride = 608, .wrap = 5} }, .packet_port_id = -1, .repetition = 60, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {3040, 4}, .tiling_dimension = {608, 1}, .offset = {0, 2}, .tile_traversal = { {.dimension = 0, .stride = 608, .wrap = 5} }, .packet_port_id = -1, .repetition = 60, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {3040, 4}, .tiling_dimension = {608, 1}, .offset = {0, 3}, .tile_traversal = { {.dimension = 0, .stride = 608, .wrap = 5} }, .packet_port_id = -1, .repetition = 60, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_295[] = {
+{
+  tiling({.buffer_dimension = {12160, 1}, .tiling_dimension = {6080, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {12160, 1}, .tiling_dimension = {6080, 1}, .offset = {6080, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_295[] = {
+{
+  tiling({.buffer_dimension = {12160}, .tiling_dimension = {6080}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {12160}, .tiling_dimension = {6080}, .offset = {6080}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_295 = {8, 320, 4, 16};
+std::vector<uint32_t> ofm_bound_295 = {8, 320, 2, 15};
+std::vector<uint32_t> ofmsv_dim_295 = {8, 64, 1, 4};
+uint32_t ofmsv_size_295 = 2048;
+uint32_t ofm_repetition_295 = 5;
+bool has_l1_read_access_pattern_295 = false;
+
+std::vector<access_pattern> l1_read_pattern_295 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_295 = {
+{
+  tiling({.buffer_dimension = {8, 320, 4, 16}, .tiling_dimension = {8, 64, 1, 4}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 16}, .tiling_dimension = {8, 64, 1, 4}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 16}, .tiling_dimension = {8, 64, 1, 4}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 16}, .tiling_dimension = {8, 64, 1, 4}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 4, 16}, .tiling_dimension = {8, 64, 1, 4}, .offset = {0, 0, 0, 4}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 16}, .tiling_dimension = {8, 64, 1, 4}, .offset = {0, 0, 1, 4}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 16}, .tiling_dimension = {8, 64, 1, 4}, .offset = {0, 0, 2, 4}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 16}, .tiling_dimension = {8, 64, 1, 4}, .offset = {0, 0, 3, 4}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 4, 16}, .tiling_dimension = {8, 64, 1, 4}, .offset = {0, 0, 0, 8}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 16}, .tiling_dimension = {8, 64, 1, 4}, .offset = {0, 0, 1, 8}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 16}, .tiling_dimension = {8, 64, 1, 4}, .offset = {0, 0, 2, 8}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 16}, .tiling_dimension = {8, 64, 1, 4}, .offset = {0, 0, 3, 8}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 4, 16}, .tiling_dimension = {8, 64, 1, 4}, .offset = {0, 0, 0, 12}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 16}, .tiling_dimension = {8, 64, 1, 4}, .offset = {0, 0, 1, 12}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 16}, .tiling_dimension = {8, 64, 1, 4}, .offset = {0, 0, 2, 12}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 16}, .tiling_dimension = {8, 64, 1, 4}, .offset = {0, 0, 3, 12}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 296
+// LayerName: Conv_441
+std::vector<uint32_t> ifm_dim_296 = {8, 320, 2, 22};
+std::vector<uint32_t> ifm_bound_296 = {8, 320, 2, 22};
+std::vector<uint32_t> ifmsv_dim_296 = {8, 34, 2, 7};
+uint32_t ifmsv_size_296 = 3808;
+uint32_t kernel_iter_296 = 90;
+bool has_l1_write_access_pattern_296 = false;
+std::vector<access_pattern> l1_write_pattern_296 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_296 = {
+{
+  tiling({.buffer_dimension = {8, 320, 2, 21}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, -1}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 3}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 4}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 5}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 6}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 7}),
+  tiling({.buffer_dimension = {8, 320, 2, 21}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 8})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 2, 21}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 4}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 5}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 5}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 5}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 3}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 5}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 4}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 5}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 5}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 5}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 6}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 5}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 7}),
+  tiling({.buffer_dimension = {8, 320, 2, 21}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 5}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 8})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 2, 21}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 9}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 10}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 10}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 10}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 3}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 10}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 4}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 10}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 5}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 10}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 6}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 10}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 7}),
+  tiling({.buffer_dimension = {8, 320, 2, 21}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 10}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 8})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 2, 21}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 14}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 15}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 1}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 15}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 2}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 15}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 3}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 15}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 4}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 15}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 5}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 15}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 6}),
+  tiling({.buffer_dimension = {8, 320, 2, 22}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 15}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 7}),
+  tiling({.buffer_dimension = {8, 320, 2, 21}, .tiling_dimension = {8, 34, 2, 7}, .offset = {0, -1, 0, 15}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 8})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_296 = {4736};
+std::vector<uint32_t> wts_dim_296 = {4736};
+std::vector<uint32_t> wtssv_dim_296 = {1184};
+uint32_t wtssv_size_296 = 1184;
+uint32_t wts_repetition_296 = 1;
+bool has_l1_wts_write_access_pattern_296 = false;
+std::vector<access_pattern> l1_wts_write_pattern_296 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_296 = {
+{
+  tiling({.buffer_dimension = {1184, 4}, .tiling_dimension = {1184, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 90, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1184, 4}, .tiling_dimension = {1184, 1}, .offset = {0, 1}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 90, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1184, 4}, .tiling_dimension = {1184, 1}, .offset = {0, 2}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 90, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {1184, 4}, .tiling_dimension = {1184, 1}, .offset = {0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 90, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_296[] = {
+{
+  tiling({.buffer_dimension = {4736, 1}, .tiling_dimension = {2368, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4736, 1}, .tiling_dimension = {2368, 1}, .offset = {2368, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_296[] = {
+{
+  tiling({.buffer_dimension = {4736}, .tiling_dimension = {2368}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {4736}, .tiling_dimension = {2368}, .offset = {2368}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_296 = {8, 320, 4, 20};
+std::vector<uint32_t> ofm_bound_296 = {8, 320, 2, 20};
+std::vector<uint32_t> ofmsv_dim_296 = {8, 32, 1, 5};
+uint32_t ofmsv_size_296 = 1280;
+uint32_t ofm_repetition_296 = 1;
+bool has_l1_read_access_pattern_296 = false;
+
+std::vector<access_pattern> l1_read_pattern_296 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_296 = {
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 0, 5}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 1, 5}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 2, 5}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 3, 5}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 1, 10}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 2, 10}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 3, 10}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 1, 15}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 2, 15}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 32, 1, 5}, .offset = {0, 0, 3, 15}, .tile_traversal = { {.dimension = 1, .stride = 32, .wrap = 10} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 297
+// LayerName: Conv_443
+std::vector<uint32_t> ifm_dim_297 = {8, 320, 2, 20};
+std::vector<uint32_t> ifm_bound_297 = {8, 320, 2, 20};
+std::vector<uint32_t> ifmsv_dim_297 = {8, 64, 8, 1};
+uint32_t ifmsv_size_297 = 4096;
+uint32_t kernel_iter_297 = 225;
+bool has_l1_write_access_pattern_297 = false;
+std::vector<access_pattern> l1_write_pattern_297 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_297 = {
+{
+  tiling({.buffer_dimension = {8, 320, 2, 20}, .tiling_dimension = {8, 64, 8, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 4, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 2, 20}, .tiling_dimension = {8, 64, 8, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 4, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 2, 20}, .tiling_dimension = {8, 64, 8, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 4, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 2, 20}, .tiling_dimension = {8, 64, 8, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 4, .wrap = 5} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> wts_ddr_dim_297 = {2176};
+std::vector<uint32_t> wts_dim_297 = {2176};
+std::vector<uint32_t> wtssv_dim_297 = {544};
+uint32_t wtssv_size_297 = 544;
+uint32_t wts_repetition_297 = 1;
+bool has_l1_wts_write_access_pattern_297 = false;
+std::vector<access_pattern> l1_wts_write_pattern_297 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_297 = {
+{
+  tiling({.buffer_dimension = {544, 4}, .tiling_dimension = {544, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 225, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {544, 4}, .tiling_dimension = {544, 1}, .offset = {0, 1}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 225, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {544, 4}, .tiling_dimension = {544, 1}, .offset = {0, 2}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 225, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {544, 4}, .tiling_dimension = {544, 1}, .offset = {0, 3}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 225, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<access_pattern> wts_ddr_read_pattern_297[] = {
+{
+  tiling({.buffer_dimension = {2176, 1}, .tiling_dimension = {1088, 1}, .offset = {0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176, 1}, .tiling_dimension = {1088, 1}, .offset = {1088, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+std::vector<access_pattern> wts_ddr_write_pattern_297[] = {
+{
+  tiling({.buffer_dimension = {2176}, .tiling_dimension = {1088}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {2176}, .tiling_dimension = {1088}, .offset = {1088}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ofm_dim_297 = {8, 320, 4, 20};
+std::vector<uint32_t> ofm_bound_297 = {8, 320, 1, 20};
+std::vector<uint32_t> ofmsv_dim_297 = {8, 64, 1, 1};
+uint32_t ofmsv_size_297 = 512;
+uint32_t ofm_repetition_297 = 1;
+bool has_l1_read_access_pattern_297 = false;
+
+std::vector<access_pattern> l1_read_pattern_297 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_297 = {
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 64, 1, 1}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 4, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 64, 1, 1}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 4, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 64, 1, 1}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 4, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 64, 1, 1}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 4, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 64, 1, 1}, .offset = {0, 0, 0, 1}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 4, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 64, 1, 1}, .offset = {0, 0, 1, 1}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 4, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 64, 1, 1}, .offset = {0, 0, 2, 1}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 4, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 64, 1, 1}, .offset = {0, 0, 3, 1}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 4, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 64, 1, 1}, .offset = {0, 0, 0, 2}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 4, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 64, 1, 1}, .offset = {0, 0, 1, 2}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 4, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 64, 1, 1}, .offset = {0, 0, 2, 2}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 4, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 64, 1, 1}, .offset = {0, 0, 3, 2}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 4, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 64, 1, 1}, .offset = {0, 0, 0, 3}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 4, .wrap = 5} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 64, 1, 1}, .offset = {0, 0, 1, 3}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 4, .wrap = 5} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 64, 1, 1}, .offset = {0, 0, 2, 3}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 4, .wrap = 5} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 64, 1, 1}, .offset = {0, 0, 3, 3}, .tile_traversal = { {.dimension = 1, .stride = 64, .wrap = 5}, {.dimension = 3, .stride = 4, .wrap = 5} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 299
+// LayerName: Clip_447
+std::vector<uint32_t> ifm_dim_299 = {8, 320, 1, 20};
+std::vector<uint32_t> ifm_bound_299 = {8, 320, 1, 20};
+std::vector<uint32_t> ifmsv_dim_299 = {8, 40, 1, 5};
+uint32_t ifmsv_size_299 = 6400;
+uint32_t kernel_iter_299 = 72;
+bool has_l1_write_access_pattern_299 = false;
+std::vector<access_pattern> l1_write_pattern_299 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_299 = {
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 0, 5}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_299 = 0;
+bool has_l1_wts_write_access_pattern_299 = false;
+std::vector<access_pattern> l1_wts_write_pattern_299 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_299 = {};
+
+
+std::vector<uint32_t> ofm_dim_299 = {8, 320, 4, 20};
+std::vector<uint32_t> ofm_bound_299 = {8, 320, 1, 20};
+std::vector<uint32_t> ofmsv_dim_299 = {8, 40, 1, 5};
+uint32_t ofmsv_size_299 = 1600;
+uint32_t ofm_repetition_299 = 1;
+bool has_l1_read_access_pattern_299 = false;
+
+std::vector<access_pattern> l1_read_pattern_299 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_299 = {
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 0, 5}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 1, 5}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 2, 5}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 3, 5}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 1, 10}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 2, 10}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 3, 10}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 1, 15}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 2, 15}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 3, 15}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 301
+// LayerName: Add_445
+std::vector<uint32_t> ifm_dim_301 = {8, 320, 1, 20};
+std::vector<uint32_t> ifm_bound_301 = {8, 320, 1, 20};
+std::vector<uint32_t> ifmsv_dim_301 = {8, 16, 1, 5};
+uint32_t ifmsv_size_301 = 2560;
+uint32_t kernel_iter_301 = 180;
+bool has_l1_write_access_pattern_301 = false;
+std::vector<access_pattern> l1_write_pattern_301 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_301 = {
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 5}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+std::vector<uint32_t> ifm2_dim_301 = {8, 320, 1, 20};
+std::vector<uint32_t> ifm2_bound_301 = {8, 320, 1, 20};
+std::vector<uint32_t> ifm2sv_dim_301 = {8, 16, 1, 5};
+uint32_t ifm2sv_size_301 = 2560;
+std::vector<std::vector<access_pattern>> ifm2_pattern_301 = {
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 5}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_301 = 0;
+bool has_l1_wts_write_access_pattern_301 = false;
+std::vector<access_pattern> l1_wts_write_pattern_301 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_301 = {};
+
+
+std::vector<uint32_t> ofm_dim_301 = {8, 320, 4, 20};
+std::vector<uint32_t> ofm_bound_301 = {8, 320, 1, 20};
+std::vector<uint32_t> ofmsv_dim_301 = {8, 16, 1, 5};
+uint32_t ofmsv_size_301 = 640;
+uint32_t ofm_repetition_301 = 1;
+bool has_l1_read_access_pattern_301 = false;
+
+std::vector<access_pattern> l1_read_pattern_301 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_301 = {
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 5}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 1, 5}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 2, 5}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 3, 5}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 1, 10}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 2, 10}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 3, 10}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 1, 15}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 2, 15}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 16, 1, 5}, .offset = {0, 0, 3, 15}, .tile_traversal = { {.dimension = 1, .stride = 16, .wrap = 20} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+// Layer: 302
+// LayerName: Clip_446
+std::vector<uint32_t> ifm_dim_302 = {8, 320, 1, 20};
+std::vector<uint32_t> ifm_bound_302 = {8, 320, 1, 20};
+std::vector<uint32_t> ifmsv_dim_302 = {8, 40, 1, 5};
+uint32_t ifmsv_size_302 = 6400;
+uint32_t kernel_iter_302 = 72;
+bool has_l1_write_access_pattern_302 = false;
+std::vector<access_pattern> l1_write_pattern_302 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> ifm_pattern_302 = {
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 0, 5}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 1, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 2, .stride = 1, .wrap = 4}, {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
+
+uint32_t wtssv_size_302 = 0;
+bool has_l1_wts_write_access_pattern_302 = false;
+std::vector<access_pattern> l1_wts_write_pattern_302 = {tiling({.buffer_dimension = {0}, .tiling_dimension = {0}, .offset = {0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+std::vector<std::vector<access_pattern>> wts_pattern_302 = {};
+
+
+std::vector<uint32_t> ofm_dim_302 = {8, 320, 4, 20};
+std::vector<uint32_t> ofm_bound_302 = {8, 320, 1, 20};
+std::vector<uint32_t> ofmsv_dim_302 = {8, 40, 1, 5};
+uint32_t ofmsv_size_302 = 1600;
+uint32_t ofm_repetition_302 = 1;
+bool has_l1_read_access_pattern_302 = false;
+
+std::vector<access_pattern> l1_read_pattern_302 = {tiling({.buffer_dimension = {0, 0, 0, 0}, .tiling_dimension = {0, 0, 0, 0}, .offset = {0, 0, 0, 0}, .tile_traversal = { }, .packet_port_id = -1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})};
+
+std::vector<std::vector<access_pattern>> ofm_pattern_302 = {
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 0, 0}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 1, 0}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 2, 0}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 3, 0}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 0, 5}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 1, 5}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 2, 5}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 3, 5}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 0, 10}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 1, 10}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 2, 10}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 3, 10}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+},
+{
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 0, 15}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 0, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 1, 15}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 1, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 2, 15}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 2, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0}),
+  tiling({.buffer_dimension = {8, 320, 4, 20}, .tiling_dimension = {8, 40, 1, 5}, .offset = {0, 0, 3, 15}, .tile_traversal = { {.dimension = 1, .stride = 40, .wrap = 8} }, .packet_port_id = 3, .repetition = 1, .boundary_dimension = {}, .buffer_iteration = 0})
+}};
+
diff --git a/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/top.cpp b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/top.cpp
new file mode 100644
index 0000000000000000000000000000000000000000..7ac016ebe913c252ea4afa6de422fc07ca9091ca
--- /dev/null
+++ b/segmentation_1_4_0_fp32_combined/vaiml_par_0/0/backend/top.cpp
@@ -0,0 +1,711 @@
+
+  #include "multi_layer_overlay.h"
+  #include <fstream>
+  #include <iomanip>
+
+  #ifdef __AIESIM__
+  #include "../aie_runtime_control.cpp"
+  #endif
+  
+FlexMLGraph compute_graph;
+
+// WTS DDR Offsets
+std::vector<uint32_t> wts_ddr_offset = {
+0/4,
+4864/4,
+5888/4,
+10240/4,
+18944/4,
+20992/4,
+29696/4,
+42752/4,
+45824/4,
+55552/4,
+68608/4,
+77056/4,
+86784/4,
+104192/4,
+113920/4,
+131328/4,
+142592/4,
+158464/4,
+175872/4,
+193280/4,
+210688/4,
+221952/4,
+237824/4,
+255232/4,
+272640/4,
+307456/4,
+315648/4,
+364032/4,
+407040/4,
+414208/4,
+455680/4,
+487936/4,
+494080/4,
+532480/4,
+564736/4,
+570880/4,
+609280/4,
+689920/4,
+705280/4,
+832256/4,
+959232/4,
+1087232/4,
+1270016/4,
+1291520/4,
+1560320/4,
+1802496/4,
+1981696/4,
+2164480/4,
+2315008/4,
+2583808/4,
+2825984/4,
+3067904/4,
+3390464/4,
+3605504/4,
+4107264/4,
+4591104/4,
+4992000/4,
+5314560/4,
+5529600/4,
+6031360/4,
+6515200/4,
+6916096/4,
+7238656/4,
+7489536/4,
+7745536/4,
+8048640/4,
+8200192/4,
+8616960/4,
+8806400/4,
+8901120/4,
+9033728/4,
+9090560/4,
+9114880/4,
+9152768/4,
+9171712/4,
+9190656/4,
+9214976/4,
+9224448/4,
+};
+std::vector<uint32_t> const_ifm_ddr_offset = {
+9228800/4,
+10150400/4,
+11072000/4,
+11102720/4,
+11176320/4,
+11349120/4
+};
+std::vector<uint32_t> spill_ddr_offset = {
+0/4,
+471040/4,
+824320/4,
+1766400/4,
+2708480/4,
+3650560/4,
+4572160/4,
+5493760/4,
+6415360/4,
+7336960/4,
+7797760/4,
+8258560/4,
+8719360/4,
+9180160/4,
+9640960/4,
+10101760/4,
+10562560/4,
+12405760/4,
+12897280/4,
+13358080/4,
+13818880/4,
+13991680/4,
+14510080/4,
+15040000/4,
+15558400/4,
+16076800/4,
+16209280/4,
+16341760/4,
+16474240/4,
+16474384/4,
+16606864/4,
+16739344/4,
+16871824/4,
+16945424/4,
+17166224/4,
+17387024/4,
+17607824/4,
+17608064/4,
+17828864/4,
+18049664/4,
+18270464/4,
+18344064/4,
+18564864/4,
+18785664/4,
+19006464/4,
+19006704/4,
+19227504/4,
+19448304/4,
+19669104/4,
+20110704/4,
+20552304/4,
+21013104/4,
+21454704/4,
+21896304/4,
+22126704/4,
+22357104/4,
+22587504/4,
+22588464/4,
+22818864/4,
+23049264/4,
+23279664/4,
+23333424/4,
+23655984/4,
+23978544/4,
+24301104/4,
+24302448/4,
+24625008/4,
+24947568/4,
+25270128/4,
+25592688/4,
+25915248/4,
+26237808/4,
+26239152/4,
+26561712/4,
+26884272/4,
+27206832/4,
+27283632/4,
+27744432/4,
+28205232/4,
+28666032/4,
+29126832/4,
+29587632/4,
+30048432/4,
+30509232/4,
+30511152/4,
+30971952/4,
+31432752/4,
+31893552/4,
+31970352/4,
+32431152/4,
+32891952/4,
+33352752/4,
+33813552/4,
+34274352/4,
+34735152/4,
+35195952/4,
+35197872/4,
+35658672/4,
+36119472/4,
+36580272/4,
+37041072/4,
+37501872/4,
+37962672/4,
+38423472/4,
+38423728/4,
+38485168/4,
+38546608/4,
+38608048/4,
+38669488/4,
+38700208/4,
+38730928/4,
+38792368/4,
+38853808/4,
+38884528/4,
+38915248/4,
+38945968/4,
+39007408/4,
+39068848/4,
+39314608/4,
+39550128/4,
+39780528/4,
+40104368/4,
+40251568/4,
+40325168/4,
+40398768/4,
+40545968/4,
+40693168/4,
+40766768/4,
+40840368/4,
+40913968/4,
+41061168/4,
+41208368/4,
+41797168/4,
+42373168/4,
+43179568/4,
+43467568/4,
+43640368/4,
+43813168/4,
+44101168/4,
+44389168/4,
+44561968/4,
+44734768/4,
+44907568/4,
+45080368/4,
+45368368/4,
+45656368/4,
+47499568/4,
+48421168/4,
+48881968/4,
+49342768/4,
+50264368/4,
+51185968/4,
+52107568/4,
+52568368/4,
+53029168/4,
+53489968/4,
+53950768/4,
+54872368/4,
+55333168/4,
+55793968/4,
+56254768/4,
+57176368/4,
+61784368/4,
+63627568/4,
+65470768/4,
+66392368/4,
+67313968/4,
+68235568/4
+};
+int main() {
+
+uint32_t *ifm_ddr_buf = (uint32_t *)GMIO::malloc(471040);
+uint32_t *ifm_ddr_1_buf = (uint32_t *)GMIO::malloc(460800);
+uint32_t *ifm_ddr_2_buf = (uint32_t *)GMIO::malloc(172800);
+uint32_t *ifm_ddr_3_buf = (uint32_t *)GMIO::malloc(73600);
+uint32_t *ifm_ddr_4_buf = (uint32_t *)GMIO::malloc(30720);
+
+uint32_t *wts_ddr_buf = (uint32_t *)GMIO::malloc(11809920);
+
+uint32_t * spill_ddr_buf = (uint32_t *)GMIO::malloc(69157168);
+
+uint32_t *ofm_ddr_3_l2l3_291_spill_buf = (uint32_t *)GMIO::malloc(460800);
+uint32_t *ofm_ddr_2_l2l3_272_spill_buf = (uint32_t *)GMIO::malloc(172800);
+uint32_t *ofm_ddr_1_l2l3_252_spill_buf = (uint32_t *)GMIO::malloc(73600);
+uint32_t *ofm_ddr_0_l2l3_229_spill_buf = (uint32_t *)GMIO::malloc(30720);
+uint32_t *ofm_ddr_5_buf = (uint32_t *)GMIO::malloc(921600);
+uint32_t *ofm_ddr_4_buf = (uint32_t *)GMIO::malloc(921600);
+
+compute_graph.init();
+
+std::ifstream ifs_ifm_ddr;
+ifs_ifm_ddr.open("data/ifm32_0.txt");
+if (!ifs_ifm_ddr.good()) {
+  std::cout << "Failed to open data/ifm32_0.txt\n";
+  exit(1);
+}
+for (int i = 0; i < 471040/4; i++)
+  ifs_ifm_ddr >> std::hex >> ifm_ddr_buf[i];
+ifs_ifm_ddr.close();
+
+std::ifstream ifs_ifm_ddr_1;
+ifs_ifm_ddr_1.open("data/ifm32_1.txt");
+if (!ifs_ifm_ddr_1.good()) {
+  std::cout << "Failed to open data/ifm32_1.txt\n";
+  exit(1);
+}
+for (int i = 0; i < 460800/4; i++)
+  ifs_ifm_ddr_1 >> std::hex >> ifm_ddr_1_buf[i];
+ifs_ifm_ddr_1.close();
+
+std::ifstream ifs_ifm_ddr_2;
+ifs_ifm_ddr_2.open("data/ifm32_2.txt");
+if (!ifs_ifm_ddr_2.good()) {
+  std::cout << "Failed to open data/ifm32_2.txt\n";
+  exit(1);
+}
+for (int i = 0; i < 172800/4; i++)
+  ifs_ifm_ddr_2 >> std::hex >> ifm_ddr_2_buf[i];
+ifs_ifm_ddr_2.close();
+
+std::ifstream ifs_ifm_ddr_3;
+ifs_ifm_ddr_3.open("data/ifm32_3.txt");
+if (!ifs_ifm_ddr_3.good()) {
+  std::cout << "Failed to open data/ifm32_3.txt\n";
+  exit(1);
+}
+for (int i = 0; i < 73600/4; i++)
+  ifs_ifm_ddr_3 >> std::hex >> ifm_ddr_3_buf[i];
+ifs_ifm_ddr_3.close();
+
+std::ifstream ifs_ifm_ddr_4;
+ifs_ifm_ddr_4.open("data/ifm32_4.txt");
+if (!ifs_ifm_ddr_4.good()) {
+  std::cout << "Failed to open data/ifm32_4.txt\n";
+  exit(1);
+}
+for (int i = 0; i < 30720/4; i++)
+  ifs_ifm_ddr_4 >> std::hex >> ifm_ddr_4_buf[i];
+ifs_ifm_ddr_4.close();
+
+std::ifstream ifs_wts_ddr;
+ifs_wts_ddr.open("data/wts32.txt");
+if (!ifs_wts_ddr.good()) {
+  std::cout << "Failed to open data/wts32.txt\n";
+  exit(1);
+}
+for (int i = 0; i < 11809920/4; i++)
+  ifs_wts_ddr >> std::hex >> wts_ddr_buf[i];
+ifs_wts_ddr.close();
+
+compute_graph.ifm_ddr.setAddress(ifm_ddr_buf);
+compute_graph.ifm_ddr_1.setAddress(ifm_ddr_1_buf);
+compute_graph.ifm_ddr_2.setAddress(ifm_ddr_2_buf);
+compute_graph.ifm_ddr_3.setAddress(ifm_ddr_3_buf);
+compute_graph.ifm_ddr_4.setAddress(ifm_ddr_4_buf);
+compute_graph.l2l3_1_spill.setAddress(spill_ddr_buf + spill_ddr_offset[0]);
+compute_graph.l2l3_2_spill.setAddress(spill_ddr_buf + spill_ddr_offset[1]);
+compute_graph.l2l3_scratch_0_3_spill.setAddress(spill_ddr_buf + spill_ddr_offset[2]);
+compute_graph.l2l3_3_spill.setAddress(spill_ddr_buf + spill_ddr_offset[3]);
+compute_graph.l2l3_4_spill.setAddress(spill_ddr_buf + spill_ddr_offset[4]);
+compute_graph.l2l3_scratch_0_5_spill.setAddress(spill_ddr_buf + spill_ddr_offset[5]);
+compute_graph.l2l3_5_spill.setAddress(spill_ddr_buf + spill_ddr_offset[6]);
+compute_graph.l2l3_6_spill.setAddress(spill_ddr_buf + spill_ddr_offset[7]);
+compute_graph.l2l3_7_spill.setAddress(spill_ddr_buf + spill_ddr_offset[8]);
+compute_graph.l2l3_8_spill.setAddress(spill_ddr_buf + spill_ddr_offset[9]);
+compute_graph.l2l3_9_spill.setAddress(spill_ddr_buf + spill_ddr_offset[10]);
+compute_graph.l2l3_10_spill.setAddress(spill_ddr_buf + spill_ddr_offset[11]);
+compute_graph.l2l3_11_spill.setAddress(spill_ddr_buf + spill_ddr_offset[12]);
+compute_graph.l2l3_12_spill.setAddress(spill_ddr_buf + spill_ddr_offset[13]);
+compute_graph.l2l3_13_spill.setAddress(spill_ddr_buf + spill_ddr_offset[14]);
+compute_graph.l2l3_14_spill.setAddress(spill_ddr_buf + spill_ddr_offset[15]);
+compute_graph.l2l3_15_spill.setAddress(spill_ddr_buf + spill_ddr_offset[16]);
+compute_graph.l2l3_16_spill.setAddress(spill_ddr_buf + spill_ddr_offset[17]);
+compute_graph.l2l3_scratch_0_17_spill.setAddress(spill_ddr_buf + spill_ddr_offset[18]);
+compute_graph.l2l3_17_spill.setAddress(spill_ddr_buf + spill_ddr_offset[19]);
+compute_graph.L3_OFM_Buffer_layer_TGSpilling_1818.setAddress(spill_ddr_buf + spill_ddr_offset[20]);
+compute_graph.l2l3_19_spill.setAddress(spill_ddr_buf + spill_ddr_offset[21]);
+compute_graph.l2l3_20_spill.setAddress(spill_ddr_buf + spill_ddr_offset[22]);
+compute_graph.l2l3_scratch_0_21_spill.setAddress(spill_ddr_buf + spill_ddr_offset[23]);
+compute_graph.l2l3_21_spill.setAddress(spill_ddr_buf + spill_ddr_offset[24]);
+compute_graph.L3_OFM_Buffer_layer_TGSpilling_2424.setAddress(spill_ddr_buf + spill_ddr_offset[25]);
+compute_graph.l2l3_24_spill.setAddress(spill_ddr_buf + spill_ddr_offset[26]);
+compute_graph.l2l3_25_spill.setAddress(spill_ddr_buf + spill_ddr_offset[27]);
+compute_graph.l2l3_31_spill.setAddress(spill_ddr_buf + spill_ddr_offset[28]);
+compute_graph.l2l3_scratch_0_32_spill.setAddress(spill_ddr_buf + spill_ddr_offset[29]);
+compute_graph.l2l3_scratch_1_32_spill.setAddress(spill_ddr_buf + spill_ddr_offset[30]);
+compute_graph.l2l3_32_spill.setAddress(spill_ddr_buf + spill_ddr_offset[31]);
+compute_graph.L3_OFM_Buffer_layer_TGSpilling_3434.setAddress(spill_ddr_buf + spill_ddr_offset[32]);
+compute_graph.L3_OFM_Buffer_layer_TGSpilling_3636.setAddress(spill_ddr_buf + spill_ddr_offset[33]);
+compute_graph.l2l3_36_spill.setAddress(spill_ddr_buf + spill_ddr_offset[34]);
+compute_graph.l2l3_37_spill.setAddress(spill_ddr_buf + spill_ddr_offset[35]);
+compute_graph.l2l3_43_spill.setAddress(spill_ddr_buf + spill_ddr_offset[36]);
+compute_graph.l2l3_scratch_0_44_spill.setAddress(spill_ddr_buf + spill_ddr_offset[37]);
+compute_graph.l2l3_scratch_1_44_spill.setAddress(spill_ddr_buf + spill_ddr_offset[38]);
+compute_graph.l2l3_44_spill.setAddress(spill_ddr_buf + spill_ddr_offset[39]);
+compute_graph.L3_OFM_Buffer_layer_TGSpilling_4646.setAddress(spill_ddr_buf + spill_ddr_offset[40]);
+compute_graph.L3_OFM_Buffer_layer_TGSpilling_4848.setAddress(spill_ddr_buf + spill_ddr_offset[41]);
+compute_graph.l2l3_48_spill.setAddress(spill_ddr_buf + spill_ddr_offset[42]);
+compute_graph.l2l3_49_spill.setAddress(spill_ddr_buf + spill_ddr_offset[43]);
+compute_graph.l2l3_55_spill.setAddress(spill_ddr_buf + spill_ddr_offset[44]);
+compute_graph.l2l3_scratch_0_56_spill.setAddress(spill_ddr_buf + spill_ddr_offset[45]);
+compute_graph.l2l3_scratch_1_56_spill.setAddress(spill_ddr_buf + spill_ddr_offset[46]);
+compute_graph.l2l3_56_spill.setAddress(spill_ddr_buf + spill_ddr_offset[47]);
+compute_graph.l2l3_59_spill.setAddress(spill_ddr_buf + spill_ddr_offset[48]);
+compute_graph.l2l3_62_spill.setAddress(spill_ddr_buf + spill_ddr_offset[49]);
+compute_graph.l2l3_63_spill.setAddress(spill_ddr_buf + spill_ddr_offset[50]);
+compute_graph.l2l3_scratch_0_64_spill.setAddress(spill_ddr_buf + spill_ddr_offset[51]);
+compute_graph.l2l3_64_spill.setAddress(spill_ddr_buf + spill_ddr_offset[52]);
+compute_graph.L3_OFM_Buffer_layer_TGSpilling_113113.setAddress(spill_ddr_buf + spill_ddr_offset[53]);
+compute_graph.l2l3_113_spill.setAddress(spill_ddr_buf + spill_ddr_offset[54]);
+compute_graph.l2l3_114_spill.setAddress(spill_ddr_buf + spill_ddr_offset[55]);
+compute_graph.l2l3_120_spill.setAddress(spill_ddr_buf + spill_ddr_offset[56]);
+compute_graph.l2l3_scratch_0_121_spill.setAddress(spill_ddr_buf + spill_ddr_offset[57]);
+compute_graph.l2l3_scratch_1_121_spill.setAddress(spill_ddr_buf + spill_ddr_offset[58]);
+compute_graph.l2l3_121_spill.setAddress(spill_ddr_buf + spill_ddr_offset[59]);
+compute_graph.L3_OFM_Buffer_layer_TGSpilling_123123.setAddress(spill_ddr_buf + spill_ddr_offset[60]);
+compute_graph.L3_OFM_Buffer_layer_TGSpilling_133133.setAddress(spill_ddr_buf + spill_ddr_offset[61]);
+compute_graph.l2l3_133_spill.setAddress(spill_ddr_buf + spill_ddr_offset[62]);
+compute_graph.l2l3_134_spill.setAddress(spill_ddr_buf + spill_ddr_offset[63]);
+compute_graph.l2l3_140_spill.setAddress(spill_ddr_buf + spill_ddr_offset[64]);
+compute_graph.l2l3_scratch_0_141_spill.setAddress(spill_ddr_buf + spill_ddr_offset[65]);
+compute_graph.l2l3_scratch_1_141_spill.setAddress(spill_ddr_buf + spill_ddr_offset[66]);
+compute_graph.l2l3_141_spill.setAddress(spill_ddr_buf + spill_ddr_offset[67]);
+compute_graph.L3_OFM_Buffer_layer_TGSpilling_153153.setAddress(spill_ddr_buf + spill_ddr_offset[68]);
+compute_graph.l2l3_153_spill.setAddress(spill_ddr_buf + spill_ddr_offset[69]);
+compute_graph.l2l3_154_spill.setAddress(spill_ddr_buf + spill_ddr_offset[70]);
+compute_graph.l2l3_160_spill.setAddress(spill_ddr_buf + spill_ddr_offset[71]);
+compute_graph.l2l3_scratch_1_161_spill.setAddress(spill_ddr_buf + spill_ddr_offset[72]);
+compute_graph.l2l3_scratch_0_161_spill.setAddress(spill_ddr_buf + spill_ddr_offset[73]);
+compute_graph.l2l3_161_spill.setAddress(spill_ddr_buf + spill_ddr_offset[74]);
+compute_graph.L3_OFM_Buffer_layer_TGSpilling_163163.setAddress(spill_ddr_buf + spill_ddr_offset[75]);
+compute_graph.l2l3_164_spill.setAddress(spill_ddr_buf + spill_ddr_offset[76]);
+compute_graph.l2l3_167_spill.setAddress(spill_ddr_buf + spill_ddr_offset[77]);
+compute_graph.l2l3_168_spill.setAddress(spill_ddr_buf + spill_ddr_offset[78]);
+compute_graph.l2l3_169_spill.setAddress(spill_ddr_buf + spill_ddr_offset[79]);
+compute_graph.l2l3_172_spill.setAddress(spill_ddr_buf + spill_ddr_offset[80]);
+compute_graph.l2l3_173_spill.setAddress(spill_ddr_buf + spill_ddr_offset[81]);
+compute_graph.l2l3_174_spill.setAddress(spill_ddr_buf + spill_ddr_offset[82]);
+compute_graph.l2l3_180_spill.setAddress(spill_ddr_buf + spill_ddr_offset[83]);
+compute_graph.l2l3_scratch_0_181_spill.setAddress(spill_ddr_buf + spill_ddr_offset[84]);
+compute_graph.l2l3_scratch_1_181_spill.setAddress(spill_ddr_buf + spill_ddr_offset[85]);
+compute_graph.l2l3_181_spill.setAddress(spill_ddr_buf + spill_ddr_offset[86]);
+compute_graph.L3_OFM_Buffer_layer_TGSpilling_183183.setAddress(spill_ddr_buf + spill_ddr_offset[87]);
+compute_graph.l2l3_184_spill.setAddress(spill_ddr_buf + spill_ddr_offset[88]);
+compute_graph.l2l3_187_spill.setAddress(spill_ddr_buf + spill_ddr_offset[89]);
+compute_graph.l2l3_188_spill.setAddress(spill_ddr_buf + spill_ddr_offset[90]);
+compute_graph.l2l3_189_spill.setAddress(spill_ddr_buf + spill_ddr_offset[91]);
+compute_graph.l2l3_192_spill.setAddress(spill_ddr_buf + spill_ddr_offset[92]);
+compute_graph.l2l3_193_spill.setAddress(spill_ddr_buf + spill_ddr_offset[93]);
+compute_graph.l2l3_194_spill.setAddress(spill_ddr_buf + spill_ddr_offset[94]);
+compute_graph.l2l3_200_spill.setAddress(spill_ddr_buf + spill_ddr_offset[95]);
+compute_graph.l2l3_scratch_0_201_spill.setAddress(spill_ddr_buf + spill_ddr_offset[96]);
+compute_graph.l2l3_scratch_1_201_spill.setAddress(spill_ddr_buf + spill_ddr_offset[97]);
+compute_graph.l2l3_201_spill.setAddress(spill_ddr_buf + spill_ddr_offset[98]);
+compute_graph.l2l3_204_spill.setAddress(spill_ddr_buf + spill_ddr_offset[99]);
+compute_graph.l2l3_207_spill.setAddress(spill_ddr_buf + spill_ddr_offset[100]);
+compute_graph.l2l3_208_spill.setAddress(spill_ddr_buf + spill_ddr_offset[101]);
+compute_graph.l2l3_209_spill.setAddress(spill_ddr_buf + spill_ddr_offset[102]);
+compute_graph.l2l3_212_spill.setAddress(spill_ddr_buf + spill_ddr_offset[103]);
+compute_graph.l2l3_scratch_0_213_spill.setAddress(spill_ddr_buf + spill_ddr_offset[104]);
+compute_graph.l2l3_scratch_1_213_spill.setAddress(spill_ddr_buf + spill_ddr_offset[105]);
+compute_graph.l2l3_213_spill.setAddress(spill_ddr_buf + spill_ddr_offset[106]);
+compute_graph.l2l3_214_spill.setAddress(spill_ddr_buf + spill_ddr_offset[107]);
+compute_graph.l2l3_215_spill.setAddress(spill_ddr_buf + spill_ddr_offset[108]);
+compute_graph.l2l3_216_spill.setAddress(spill_ddr_buf + spill_ddr_offset[109]);
+compute_graph.spill_L3_Concat_Buffer_layer_217.setAddress(spill_ddr_buf + spill_ddr_offset[110]);
+compute_graph.l2l3_219_spill.setAddress(spill_ddr_buf + spill_ddr_offset[111]);
+compute_graph.l2l3_220_spill.setAddress(spill_ddr_buf + spill_ddr_offset[112]);
+compute_graph.L3_OFM_Buffer_layer_TGSpilling_222222.setAddress(spill_ddr_buf + spill_ddr_offset[113]);
+compute_graph.l2l3_223_spill.setAddress(spill_ddr_buf + spill_ddr_offset[114]);
+compute_graph.spill_L3_Concat_Buffer_layer_225.setAddress(spill_ddr_buf + spill_ddr_offset[115]);
+compute_graph.spill_L3_Concat_Buffer_layer_230.setAddress(spill_ddr_buf + spill_ddr_offset[116]);
+compute_graph.l2l3_231_spill.setAddress(spill_ddr_buf + spill_ddr_offset[117]);
+compute_graph.l2l3_232_spill.setAddress(spill_ddr_buf + spill_ddr_offset[118]);
+compute_graph.l2l3_233_spill.setAddress(spill_ddr_buf + spill_ddr_offset[119]);
+compute_graph.spill_L3_Concat_Buffer_layer_236.setAddress(spill_ddr_buf + spill_ddr_offset[120]);
+compute_graph.l2l3_237_spill.setAddress(spill_ddr_buf + spill_ddr_offset[121]);
+compute_graph.l2l3_238_spill.setAddress(spill_ddr_buf + spill_ddr_offset[122]);
+compute_graph.l2l3_239_spill.setAddress(spill_ddr_buf + spill_ddr_offset[123]);
+compute_graph.spill_L3_Concat_Buffer_layer_240.setAddress(spill_ddr_buf + spill_ddr_offset[124]);
+compute_graph.l2l3_242_spill.setAddress(spill_ddr_buf + spill_ddr_offset[125]);
+compute_graph.l2l3_243_spill.setAddress(spill_ddr_buf + spill_ddr_offset[126]);
+compute_graph.L3_OFM_Buffer_layer_TGSpilling_245245.setAddress(spill_ddr_buf + spill_ddr_offset[127]);
+compute_graph.l2l3_246_spill.setAddress(spill_ddr_buf + spill_ddr_offset[128]);
+compute_graph.spill_L3_Concat_Buffer_layer_248.setAddress(spill_ddr_buf + spill_ddr_offset[129]);
+compute_graph.spill_L3_Concat_Buffer_layer_253.setAddress(spill_ddr_buf + spill_ddr_offset[130]);
+compute_graph.l2l3_254_spill.setAddress(spill_ddr_buf + spill_ddr_offset[131]);
+compute_graph.l2l3_255_spill.setAddress(spill_ddr_buf + spill_ddr_offset[132]);
+compute_graph.spill_L3_Concat_Buffer_layer_256.setAddress(spill_ddr_buf + spill_ddr_offset[133]);
+compute_graph.l2l3_257_spill.setAddress(spill_ddr_buf + spill_ddr_offset[134]);
+compute_graph.l2l3_258_spill.setAddress(spill_ddr_buf + spill_ddr_offset[135]);
+compute_graph.l2l3_259_spill.setAddress(spill_ddr_buf + spill_ddr_offset[136]);
+compute_graph.l2l3_260_spill.setAddress(spill_ddr_buf + spill_ddr_offset[137]);
+compute_graph.l2l3_262_spill.setAddress(spill_ddr_buf + spill_ddr_offset[138]);
+compute_graph.l2l3_263_spill.setAddress(spill_ddr_buf + spill_ddr_offset[139]);
+compute_graph.L3_OFM_Buffer_layer_TGSpilling_265265.setAddress(spill_ddr_buf + spill_ddr_offset[140]);
+compute_graph.l2l3_266_spill.setAddress(spill_ddr_buf + spill_ddr_offset[141]);
+compute_graph.l2l3_267_spill.setAddress(spill_ddr_buf + spill_ddr_offset[142]);
+compute_graph.l2l3_268_spill.setAddress(spill_ddr_buf + spill_ddr_offset[143]);
+compute_graph.l2l3_273_spill.setAddress(spill_ddr_buf + spill_ddr_offset[144]);
+compute_graph.spill_L3_Concat_Buffer_layer_275.setAddress(spill_ddr_buf + spill_ddr_offset[145]);
+compute_graph.l2l3_276_spill.setAddress(spill_ddr_buf + spill_ddr_offset[146]);
+compute_graph.l2l3_277_spill.setAddress(spill_ddr_buf + spill_ddr_offset[147]);
+compute_graph.l2l3_278_spill.setAddress(spill_ddr_buf + spill_ddr_offset[148]);
+compute_graph.spill_L3_Concat_Buffer_layer_279.setAddress(spill_ddr_buf + spill_ddr_offset[149]);
+compute_graph.l2l3_280_spill.setAddress(spill_ddr_buf + spill_ddr_offset[150]);
+compute_graph.l2l3_281_spill.setAddress(spill_ddr_buf + spill_ddr_offset[151]);
+compute_graph.l2l3_282_spill.setAddress(spill_ddr_buf + spill_ddr_offset[152]);
+compute_graph.l2l3_283_spill.setAddress(spill_ddr_buf + spill_ddr_offset[153]);
+compute_graph.l2l3_284_spill.setAddress(spill_ddr_buf + spill_ddr_offset[154]);
+compute_graph.l2l3_285_spill.setAddress(spill_ddr_buf + spill_ddr_offset[155]);
+compute_graph.spill_L3_Concat_Buffer_layer_287.setAddress(spill_ddr_buf + spill_ddr_offset[156]);
+compute_graph.l2l3_288_spill.setAddress(spill_ddr_buf + spill_ddr_offset[157]);
+compute_graph.l2l3_289_spill.setAddress(spill_ddr_buf + spill_ddr_offset[158]);
+compute_graph.l2l3_290_spill.setAddress(spill_ddr_buf + spill_ddr_offset[159]);
+compute_graph.spill_L3_Concat_Buffer_layer_292.setAddress(spill_ddr_buf + spill_ddr_offset[160]);
+compute_graph.spill_L3_Concat_Buffer_layer_294.setAddress(spill_ddr_buf + spill_ddr_offset[161]);
+compute_graph.l2l3_295_spill.setAddress(spill_ddr_buf + spill_ddr_offset[162]);
+compute_graph.l2l3_296_spill.setAddress(spill_ddr_buf + spill_ddr_offset[163]);
+compute_graph.l2l3_297_spill.setAddress(spill_ddr_buf + spill_ddr_offset[164]);
+compute_graph.l2l3_298_spill.setAddress(spill_ddr_buf + spill_ddr_offset[165]);
+compute_graph.l2l3_300_spill.setAddress(spill_ddr_buf + spill_ddr_offset[166]);
+compute_graph.l2l3_301_spill.setAddress(spill_ddr_buf + spill_ddr_offset[167]);
+compute_graph.Layer_8_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[0]);
+compute_graph.Layer_13_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[1]);
+compute_graph.Layer_14_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[2]);
+compute_graph.Layer_15_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[3]);
+compute_graph.Layer_16_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[4]);
+compute_graph.Layer_18_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[5]);
+compute_graph.Layer_19_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[6]);
+compute_graph.Layer_20_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[7]);
+compute_graph.Layer_22_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[8]);
+compute_graph.Layer_23_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[9]);
+compute_graph.Layer_24_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[10]);
+compute_graph.Layer_27_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[11]);
+compute_graph.Layer_28_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[12]);
+compute_graph.Layer_34_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[13]);
+compute_graph.Layer_35_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[14]);
+compute_graph.Layer_36_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[15]);
+compute_graph.Layer_39_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[16]);
+compute_graph.Layer_40_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[17]);
+compute_graph.Layer_46_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[18]);
+compute_graph.Layer_47_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[19]);
+compute_graph.Layer_48_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[20]);
+compute_graph.Layer_51_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[21]);
+compute_graph.Layer_52_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[22]);
+compute_graph.Layer_58_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[23]);
+compute_graph.Layer_59_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[24]);
+compute_graph.Layer_65_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[25]);
+compute_graph.Layer_70_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[26]);
+compute_graph.Layer_71_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[27]);
+compute_graph.Layer_76_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[28]);
+compute_graph.Layer_81_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[29]);
+compute_graph.Layer_82_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[30]);
+compute_graph.Layer_87_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[31]);
+compute_graph.Layer_92_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[32]);
+compute_graph.Layer_93_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[33]);
+compute_graph.Layer_98_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[34]);
+compute_graph.Layer_103_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[35]);
+compute_graph.Layer_104_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[36]);
+compute_graph.Layer_109_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[37]);
+compute_graph.Layer_116_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[38]);
+compute_graph.Layer_117_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[39]);
+compute_graph.Layer_123_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[40]);
+compute_graph.Layer_124_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[41]);
+compute_graph.Layer_129_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[42]);
+compute_graph.Layer_136_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[43]);
+compute_graph.Layer_137_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[44]);
+compute_graph.Layer_143_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[45]);
+compute_graph.Layer_144_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[46]);
+compute_graph.Layer_149_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[47]);
+compute_graph.Layer_156_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[48]);
+compute_graph.Layer_157_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[49]);
+compute_graph.Layer_163_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[50]);
+compute_graph.Layer_164_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[51]);
+compute_graph.Layer_169_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[52]);
+compute_graph.Layer_176_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[53]);
+compute_graph.Layer_177_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[54]);
+compute_graph.Layer_183_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[55]);
+compute_graph.Layer_184_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[56]);
+compute_graph.Layer_189_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[57]);
+compute_graph.Layer_196_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[58]);
+compute_graph.Layer_197_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[59]);
+compute_graph.Layer_203_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[60]);
+compute_graph.Layer_204_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[61]);
+compute_graph.Layer_211_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[62]);
+compute_graph.Layer_214_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[63]);
+compute_graph.Layer_218_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[64]);
+compute_graph.Layer_226_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[65]);
+compute_graph.Layer_237_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[66]);
+compute_graph.Layer_241_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[67]);
+compute_graph.Layer_249_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[68]);
+compute_graph.Layer_257_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[69]);
+compute_graph.Layer_261_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[70]);
+compute_graph.Layer_269_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[71]);
+compute_graph.Layer_276_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[72]);
+compute_graph.Layer_280_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[73]);
+compute_graph.Layer_288_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[74]);
+compute_graph.Layer_295_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[75]);
+compute_graph.Layer_296_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[76]);
+compute_graph.Layer_297_wts_ddr.setAddress(wts_ddr_buf + wts_ddr_offset[77]);
+compute_graph.const_ifm_ddr_5.setAddress(wts_ddr_buf + const_ifm_ddr_offset[0]);
+compute_graph.const_ifm_ddr_4.setAddress(wts_ddr_buf + const_ifm_ddr_offset[1]);
+compute_graph.const_ifm_ddr_3.setAddress(wts_ddr_buf + const_ifm_ddr_offset[2]);
+compute_graph.const_ifm_ddr_2.setAddress(wts_ddr_buf + const_ifm_ddr_offset[3]);
+compute_graph.const_ifm_ddr_1.setAddress(wts_ddr_buf + const_ifm_ddr_offset[4]);
+compute_graph.const_ifm_ddr.setAddress(wts_ddr_buf + const_ifm_ddr_offset[5]);
+compute_graph.ofm_ddr_3_l2l3_291_spill.setAddress(ofm_ddr_3_l2l3_291_spill_buf);
+compute_graph.ofm_ddr_2_l2l3_272_spill.setAddress(ofm_ddr_2_l2l3_272_spill_buf);
+compute_graph.ofm_ddr_1_l2l3_252_spill.setAddress(ofm_ddr_1_l2l3_252_spill_buf);
+compute_graph.ofm_ddr_0_l2l3_229_spill.setAddress(ofm_ddr_0_l2l3_229_spill_buf);
+compute_graph.ofm_ddr_5.setAddress(ofm_ddr_5_buf);
+compute_graph.ofm_ddr_4.setAddress(ofm_ddr_4_buf);
+
+compute_graph.run(1);
+
+  #ifdef __AIESIM__
+    executeRuntimeControl();
+  #endif
+
+  compute_graph.end();
+
+  std::ofstream ofs_ofm_ddr_3_l2l3_291_spill;
+ofs_ofm_ddr_3_l2l3_291_spill.open("data/ofm32_0.txt", std::ofstream::out | std::ofstream::trunc);
+if (!ofs_ofm_ddr_3_l2l3_291_spill.good()) {
+  std::cout << "Failed to open data/ofm32_0.txt\n";
+  exit(1);
+}
+for (int i = 0; i < 460800/4; i++)
+  ofs_ofm_ddr_3_l2l3_291_spill << std::hex << std::setw(8) << std::setfill('0') << (uint32_t)ofm_ddr_3_l2l3_291_spill_buf[i] << std::endl;
+ofs_ofm_ddr_3_l2l3_291_spill.close();
+
+std::ofstream ofs_ofm_ddr_2_l2l3_272_spill;
+ofs_ofm_ddr_2_l2l3_272_spill.open("data/ofm32_1.txt", std::ofstream::out | std::ofstream::trunc);
+if (!ofs_ofm_ddr_2_l2l3_272_spill.good()) {
+  std::cout << "Failed to open data/ofm32_1.txt\n";
+  exit(1);
+}
+for (int i = 0; i < 172800/4; i++)
+  ofs_ofm_ddr_2_l2l3_272_spill << std::hex << std::setw(8) << std::setfill('0') << (uint32_t)ofm_ddr_2_l2l3_272_spill_buf[i] << std::endl;
+ofs_ofm_ddr_2_l2l3_272_spill.close();
+
+std::ofstream ofs_ofm_ddr_1_l2l3_252_spill;
+ofs_ofm_ddr_1_l2l3_252_spill.open("data/ofm32_2.txt", std::ofstream::out | std::ofstream::trunc);
+if (!ofs_ofm_ddr_1_l2l3_252_spill.good()) {
+  std::cout << "Failed to open data/ofm32_2.txt\n";
+  exit(1);
+}
+for (int i = 0; i < 73600/4; i++)
+  ofs_ofm_ddr_1_l2l3_252_spill << std::hex << std::setw(8) << std::setfill('0') << (uint32_t)ofm_ddr_1_l2l3_252_spill_buf[i] << std::endl;
+ofs_ofm_ddr_1_l2l3_252_spill.close();
+
+std::ofstream ofs_ofm_ddr_0_l2l3_229_spill;
+ofs_ofm_ddr_0_l2l3_229_spill.open("data/ofm32_3.txt", std::ofstream::out | std::ofstream::trunc);
+if (!ofs_ofm_ddr_0_l2l3_229_spill.good()) {
+  std::cout << "Failed to open data/ofm32_3.txt\n";
+  exit(1);
+}
+for (int i = 0; i < 30720/4; i++)
+  ofs_ofm_ddr_0_l2l3_229_spill << std::hex << std::setw(8) << std::setfill('0') << (uint32_t)ofm_ddr_0_l2l3_229_spill_buf[i] << std::endl;
+ofs_ofm_ddr_0_l2l3_229_spill.close();
+
+std::ofstream ofs_ofm_ddr_5;
+ofs_ofm_ddr_5.open("data/ofm32_4.txt", std::ofstream::out | std::ofstream::trunc);
+if (!ofs_ofm_ddr_5.good()) {
+  std::cout << "Failed to open data/ofm32_4.txt\n";
+  exit(1);
+}
+for (int i = 0; i < 921600/4; i++)
+  ofs_ofm_ddr_5 << std::hex << std::setw(8) << std::setfill('0') << (uint32_t)ofm_ddr_5_buf[i] << std::endl;
+ofs_ofm_ddr_5.close();
+
+std::ofstream ofs_ofm_ddr_4;
+ofs_ofm_ddr_4.open("data/ofm32_5.txt", std::ofstream::out | std::ofstream::trunc);
+if (!ofs_ofm_ddr_4.good()) {
+  std::cout << "Failed to open data/ofm32_5.txt\n";
+  exit(1);
+}
+for (int i = 0; i < 921600/4; i++)
+  ofs_ofm_ddr_4 << std::hex << std::setw(8) << std::setfill('0') << (uint32_t)ofm_ddr_4_buf[i] << std::endl;
+ofs_ofm_ddr_4.close();
+
+GMIO::free(ifm_ddr_buf);
+
+GMIO::free(ifm_ddr_1_buf);
+
+GMIO::free(ifm_ddr_2_buf);
+
+GMIO::free(ifm_ddr_3_buf);
+
+GMIO::free(ifm_ddr_4_buf);
+
+GMIO::free(wts_ddr_buf);
+
+GMIO::free(spill_ddr_buf);
+
+GMIO::free(ofm_ddr_3_l2l3_291_spill_buf);
+
+GMIO::free(ofm_ddr_2_l2l3_272_spill_buf);
+
+GMIO::free(ofm_ddr_1_l2l3_252_spill_buf);
+
+GMIO::free(ofm_ddr_0_l2l3_229_spill_buf);
+
+GMIO::free(ofm_ddr_5_buf);
+
+GMIO::free(ofm_ddr_4_buf);
+
+return 0;
+}