diff --git "a/original/compiled/TextEncoder.mlmodelc/model.mil" "b/original/compiled/TextEncoder.mlmodelc/model.mil" new file mode 100644--- /dev/null +++ "b/original/compiled/TextEncoder.mlmodelc/model.mil" @@ -0,0 +1,887 @@ +program(1.0) +[buildInfo = dict, tensor>({{"coremlc-component-MIL", "5.33.4"}, {"coremlc-version", "1436.100.10"}})] +{ + func main(tensor input_ids) { + tensor var_5 = const()[name = tensor("op_5"), val = tensor(-1)]; + tensor inputs_embeds_axis_0 = const()[name = tensor("inputs_embeds_axis_0"), val = tensor(0)]; + tensor inputs_embeds_batch_dims_0 = const()[name = tensor("inputs_embeds_batch_dims_0"), val = tensor(0)]; + tensor text_encoder_text_model_embeddings_token_embedding_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_embeddings_token_embedding_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64)))]; + tensor inputs_embeds_cast = gather(axis = inputs_embeds_axis_0, batch_dims = inputs_embeds_batch_dims_0, indices = input_ids, x = text_encoder_text_model_embeddings_token_embedding_weight_to_fp16)[name = tensor("inputs_embeds_cast")]; + tensor position_embeddings_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75890816))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75935232))), name = tensor("position_embeddings_to_fp16_palettized"), shape = tensor([1, 77, 768])]; + tensor input_3_cast = add(x = inputs_embeds_cast, y = position_embeddings_to_fp16_palettized)[name = tensor("input_3_cast")]; + tensor hidden_states_1_axes_0 = const()[name = tensor("hidden_states_1_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_0_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75935424)))]; + tensor text_encoder_text_model_encoder_layers_0_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75937024)))]; + tensor var_13_to_fp16 = const()[name = tensor("op_13_to_fp16"), val = tensor(0x1.5p-17)]; + tensor hidden_states_1_cast = layer_norm(axes = hidden_states_1_axes_0, beta = text_encoder_text_model_encoder_layers_0_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_0_layer_norm1_weight_to_fp16, x = input_3_cast)[name = tensor("hidden_states_1_cast")]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75938624))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(76381056))), name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(76381248)))]; + tensor var_87_cast = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_1_cast)[name = tensor("op_87_cast")]; + tensor var_88_to_fp16 = const()[name = tensor("op_88_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_5_cast = mul(x = var_87_cast, y = var_88_to_fp16)[name = tensor("tensor_5_cast")]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(76382848))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(76825280))), name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(76825472)))]; + tensor tensor_1_cast = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_1_cast)[name = tensor("tensor_1_cast")]; + tensor var_93 = const()[name = tensor("op_93"), val = tensor([1, -1, 12, 64])]; + tensor var_94_cast = reshape(shape = var_93, x = tensor_1_cast)[name = tensor("op_94_cast")]; + tensor var_95_perm_0 = const()[name = tensor("op_95_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(76827072))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77269504))), name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77269696)))]; + tensor tensor_3_cast = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_1_cast)[name = tensor("tensor_3_cast")]; + tensor var_100 = const()[name = tensor("op_100"), val = tensor([1, -1, 12, 64])]; + tensor var_101_cast = reshape(shape = var_100, x = tensor_3_cast)[name = tensor("op_101_cast")]; + tensor var_102_perm_0 = const()[name = tensor("op_102_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_109 = const()[name = tensor("op_109"), val = tensor([1, 77, 12, 64])]; + tensor var_110_cast = reshape(shape = var_109, x = tensor_5_cast)[name = tensor("op_110_cast")]; + tensor var_111_perm_0 = const()[name = tensor("op_111_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_113 = const()[name = tensor("op_113"), val = tensor([12, -1, 64])]; + tensor transpose_59 = transpose(perm = var_111_perm_0, x = var_110_cast)[name = tensor("transpose_59")]; + tensor query_states_1_cast = reshape(shape = var_113, x = transpose_59)[name = tensor("query_states_1_cast")]; + tensor var_115 = const()[name = tensor("op_115"), val = tensor([12, -1, 64])]; + tensor transpose_58 = transpose(perm = var_95_perm_0, x = var_94_cast)[name = tensor("transpose_58")]; + tensor key_states_3_cast = reshape(shape = var_115, x = transpose_58)[name = tensor("key_states_3_cast")]; + tensor var_117 = const()[name = tensor("op_117"), val = tensor([12, -1, 64])]; + tensor transpose_57 = transpose(perm = var_102_perm_0, x = var_101_cast)[name = tensor("transpose_57")]; + tensor value_states_3_cast = reshape(shape = var_117, x = transpose_57)[name = tensor("value_states_3_cast")]; + tensor var_120_perm_0 = const()[name = tensor("op_120_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_1_transpose_x_0 = const()[name = tensor("attn_weights_1_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_1_transpose_y_0 = const()[name = tensor("attn_weights_1_transpose_y_0"), val = tensor(false)]; + tensor transpose_56 = transpose(perm = var_120_perm_0, x = key_states_3_cast)[name = tensor("transpose_56")]; + tensor attn_weights_1_cast = matmul(transpose_x = attn_weights_1_transpose_x_0, transpose_y = attn_weights_1_transpose_y_0, x = query_states_1_cast, y = transpose_56)[name = tensor("attn_weights_1_cast")]; + tensor var_122 = const()[name = tensor("op_122"), val = tensor([1, 12, 77, 77])]; + tensor var_123_cast = reshape(shape = var_122, x = attn_weights_1_cast)[name = tensor("op_123_cast")]; + tensor causal_attention_mask_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77271296))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77275840))), name = tensor("causal_attention_mask_to_fp16_palettized"), shape = tensor([1, 1, 77, 77])]; + tensor attn_weights_3_cast = add(x = var_123_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_3_cast")]; + tensor var_128 = const()[name = tensor("op_128"), val = tensor([12, 77, 77])]; + tensor input_5_cast = reshape(shape = var_128, x = attn_weights_3_cast)[name = tensor("input_5_cast")]; + tensor input_7_cast = softmax(axis = var_5, x = input_5_cast)[name = tensor("input_7_cast")]; + tensor attn_output_1_transpose_x_0 = const()[name = tensor("attn_output_1_transpose_x_0"), val = tensor(false)]; + tensor attn_output_1_transpose_y_0 = const()[name = tensor("attn_output_1_transpose_y_0"), val = tensor(false)]; + tensor attn_output_1_cast = matmul(transpose_x = attn_output_1_transpose_x_0, transpose_y = attn_output_1_transpose_y_0, x = input_7_cast, y = value_states_3_cast)[name = tensor("attn_output_1_cast")]; + tensor var_133 = const()[name = tensor("op_133"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_3_cast = reshape(shape = var_133, x = attn_output_1_cast)[name = tensor("attn_output_3_cast")]; + tensor attn_output_5_perm_0 = const()[name = tensor("attn_output_5_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_136 = const()[name = tensor("op_136"), val = tensor([1, 77, 768])]; + tensor transpose_55 = transpose(perm = attn_output_5_perm_0, x = attn_output_3_cast)[name = tensor("transpose_55")]; + tensor input_9_cast = reshape(shape = var_136, x = transpose_55)[name = tensor("input_9_cast")]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77276032))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77718464))), name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77718656)))]; + tensor hidden_states_3_cast = linear(bias = text_encoder_text_model_encoder_layers_0_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_self_attn_out_proj_weight_to_fp16_palettized, x = input_9_cast)[name = tensor("hidden_states_3_cast")]; + tensor input_11_cast = add(x = input_3_cast, y = hidden_states_3_cast)[name = tensor("input_11_cast")]; + tensor input_13_axes_0 = const()[name = tensor("input_13_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_0_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77720256)))]; + tensor text_encoder_text_model_encoder_layers_0_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77721856)))]; + tensor input_13_cast = layer_norm(axes = input_13_axes_0, beta = text_encoder_text_model_encoder_layers_0_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_0_layer_norm2_weight_to_fp16, x = input_11_cast)[name = tensor("input_13_cast")]; + tensor text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77723456))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79492992))), name = tensor("text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([3072, 768])]; + tensor text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79493184))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79495552))), name = tensor("text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor input_15_cast = linear(bias = text_encoder_text_model_encoder_layers_0_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_0_mlp_fc1_weight_to_fp16_palettized, x = input_13_cast)[name = tensor("input_15_cast")]; + tensor var_151_to_fp16 = const()[name = tensor("op_151_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_152_cast = mul(x = input_15_cast, y = var_151_to_fp16)[name = tensor("op_152_cast")]; + tensor var_153_cast = sigmoid(x = var_152_cast)[name = tensor("op_153_cast")]; + tensor input_17_cast = mul(x = input_15_cast, y = var_153_cast)[name = tensor("input_17_cast")]; + tensor text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79495744))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81265280))), name = tensor("text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([768, 3072])]; + tensor text_encoder_text_model_encoder_layers_0_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_0_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81265472)))]; + tensor hidden_states_5_cast = linear(bias = text_encoder_text_model_encoder_layers_0_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_0_mlp_fc2_weight_to_fp16_palettized, x = input_17_cast)[name = tensor("hidden_states_5_cast")]; + tensor input_19_cast = add(x = input_11_cast, y = hidden_states_5_cast)[name = tensor("input_19_cast")]; + tensor hidden_states_7_axes_0 = const()[name = tensor("hidden_states_7_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_1_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81267072)))]; + tensor text_encoder_text_model_encoder_layers_1_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81268672)))]; + tensor hidden_states_7_cast = layer_norm(axes = hidden_states_7_axes_0, beta = text_encoder_text_model_encoder_layers_1_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_1_layer_norm1_weight_to_fp16, x = input_19_cast)[name = tensor("hidden_states_7_cast")]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81270272))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81712704))), name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81712896)))]; + tensor var_177_cast = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_7_cast)[name = tensor("op_177_cast")]; + tensor var_178_to_fp16 = const()[name = tensor("op_178_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_11_cast = mul(x = var_177_cast, y = var_178_to_fp16)[name = tensor("tensor_11_cast")]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81714496))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82156928))), name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82157120)))]; + tensor tensor_7_cast = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_7_cast)[name = tensor("tensor_7_cast")]; + tensor var_183 = const()[name = tensor("op_183"), val = tensor([1, -1, 12, 64])]; + tensor var_184_cast = reshape(shape = var_183, x = tensor_7_cast)[name = tensor("op_184_cast")]; + tensor var_185_perm_0 = const()[name = tensor("op_185_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82158720))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82601152))), name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82601344)))]; + tensor tensor_9_cast = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_7_cast)[name = tensor("tensor_9_cast")]; + tensor var_190 = const()[name = tensor("op_190"), val = tensor([1, -1, 12, 64])]; + tensor var_191_cast = reshape(shape = var_190, x = tensor_9_cast)[name = tensor("op_191_cast")]; + tensor var_192_perm_0 = const()[name = tensor("op_192_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_199 = const()[name = tensor("op_199"), val = tensor([1, 77, 12, 64])]; + tensor var_200_cast = reshape(shape = var_199, x = tensor_11_cast)[name = tensor("op_200_cast")]; + tensor var_201_perm_0 = const()[name = tensor("op_201_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_203 = const()[name = tensor("op_203"), val = tensor([12, -1, 64])]; + tensor transpose_54 = transpose(perm = var_201_perm_0, x = var_200_cast)[name = tensor("transpose_54")]; + tensor query_states_3_cast = reshape(shape = var_203, x = transpose_54)[name = tensor("query_states_3_cast")]; + tensor var_205 = const()[name = tensor("op_205"), val = tensor([12, -1, 64])]; + tensor transpose_53 = transpose(perm = var_185_perm_0, x = var_184_cast)[name = tensor("transpose_53")]; + tensor key_states_7_cast = reshape(shape = var_205, x = transpose_53)[name = tensor("key_states_7_cast")]; + tensor var_207 = const()[name = tensor("op_207"), val = tensor([12, -1, 64])]; + tensor transpose_52 = transpose(perm = var_192_perm_0, x = var_191_cast)[name = tensor("transpose_52")]; + tensor value_states_7_cast = reshape(shape = var_207, x = transpose_52)[name = tensor("value_states_7_cast")]; + tensor var_210_perm_0 = const()[name = tensor("op_210_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_7_transpose_x_0 = const()[name = tensor("attn_weights_7_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_7_transpose_y_0 = const()[name = tensor("attn_weights_7_transpose_y_0"), val = tensor(false)]; + tensor transpose_51 = transpose(perm = var_210_perm_0, x = key_states_7_cast)[name = tensor("transpose_51")]; + tensor attn_weights_7_cast = matmul(transpose_x = attn_weights_7_transpose_x_0, transpose_y = attn_weights_7_transpose_y_0, x = query_states_3_cast, y = transpose_51)[name = tensor("attn_weights_7_cast")]; + tensor var_212 = const()[name = tensor("op_212"), val = tensor([1, 12, 77, 77])]; + tensor var_213_cast = reshape(shape = var_212, x = attn_weights_7_cast)[name = tensor("op_213_cast")]; + tensor attn_weights_9_cast = add(x = var_213_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_9_cast")]; + tensor var_218 = const()[name = tensor("op_218"), val = tensor([12, 77, 77])]; + tensor input_21_cast = reshape(shape = var_218, x = attn_weights_9_cast)[name = tensor("input_21_cast")]; + tensor input_23_cast = softmax(axis = var_5, x = input_21_cast)[name = tensor("input_23_cast")]; + tensor attn_output_7_transpose_x_0 = const()[name = tensor("attn_output_7_transpose_x_0"), val = tensor(false)]; + tensor attn_output_7_transpose_y_0 = const()[name = tensor("attn_output_7_transpose_y_0"), val = tensor(false)]; + tensor attn_output_7_cast = matmul(transpose_x = attn_output_7_transpose_x_0, transpose_y = attn_output_7_transpose_y_0, x = input_23_cast, y = value_states_7_cast)[name = tensor("attn_output_7_cast")]; + tensor var_223 = const()[name = tensor("op_223"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_9_cast = reshape(shape = var_223, x = attn_output_7_cast)[name = tensor("attn_output_9_cast")]; + tensor attn_output_11_perm_0 = const()[name = tensor("attn_output_11_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_226 = const()[name = tensor("op_226"), val = tensor([1, 77, 768])]; + tensor transpose_50 = transpose(perm = attn_output_11_perm_0, x = attn_output_9_cast)[name = tensor("transpose_50")]; + tensor input_25_cast = reshape(shape = var_226, x = transpose_50)[name = tensor("input_25_cast")]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82602944))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83045376))), name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83045568)))]; + tensor hidden_states_9_cast = linear(bias = text_encoder_text_model_encoder_layers_1_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_self_attn_out_proj_weight_to_fp16_palettized, x = input_25_cast)[name = tensor("hidden_states_9_cast")]; + tensor input_27_cast = add(x = input_19_cast, y = hidden_states_9_cast)[name = tensor("input_27_cast")]; + tensor input_29_axes_0 = const()[name = tensor("input_29_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_1_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83047168)))]; + tensor text_encoder_text_model_encoder_layers_1_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83048768)))]; + tensor input_29_cast = layer_norm(axes = input_29_axes_0, beta = text_encoder_text_model_encoder_layers_1_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_1_layer_norm2_weight_to_fp16, x = input_27_cast)[name = tensor("input_29_cast")]; + tensor text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83050368))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84819904))), name = tensor("text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([3072, 768])]; + tensor text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84820096))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84822464))), name = tensor("text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor input_31_cast = linear(bias = text_encoder_text_model_encoder_layers_1_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_1_mlp_fc1_weight_to_fp16_palettized, x = input_29_cast)[name = tensor("input_31_cast")]; + tensor var_241_to_fp16 = const()[name = tensor("op_241_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_242_cast = mul(x = input_31_cast, y = var_241_to_fp16)[name = tensor("op_242_cast")]; + tensor var_243_cast = sigmoid(x = var_242_cast)[name = tensor("op_243_cast")]; + tensor input_33_cast = mul(x = input_31_cast, y = var_243_cast)[name = tensor("input_33_cast")]; + tensor text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84822656))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(86592192))), name = tensor("text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([768, 3072])]; + tensor text_encoder_text_model_encoder_layers_1_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_1_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(86592384)))]; + tensor hidden_states_11_cast = linear(bias = text_encoder_text_model_encoder_layers_1_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_1_mlp_fc2_weight_to_fp16_palettized, x = input_33_cast)[name = tensor("hidden_states_11_cast")]; + tensor input_35_cast = add(x = input_27_cast, y = hidden_states_11_cast)[name = tensor("input_35_cast")]; + tensor hidden_states_13_axes_0 = const()[name = tensor("hidden_states_13_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_2_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(86593984)))]; + tensor text_encoder_text_model_encoder_layers_2_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(86595584)))]; + tensor hidden_states_13_cast = layer_norm(axes = hidden_states_13_axes_0, beta = text_encoder_text_model_encoder_layers_2_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_2_layer_norm1_weight_to_fp16, x = input_35_cast)[name = tensor("hidden_states_13_cast")]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(86597184))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87039616))), name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87039808)))]; + tensor var_267_cast = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_13_cast)[name = tensor("op_267_cast")]; + tensor var_268_to_fp16 = const()[name = tensor("op_268_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_17_cast = mul(x = var_267_cast, y = var_268_to_fp16)[name = tensor("tensor_17_cast")]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87041408))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87483840))), name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87484032)))]; + tensor tensor_13_cast = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_13_cast)[name = tensor("tensor_13_cast")]; + tensor var_273 = const()[name = tensor("op_273"), val = tensor([1, -1, 12, 64])]; + tensor var_274_cast = reshape(shape = var_273, x = tensor_13_cast)[name = tensor("op_274_cast")]; + tensor var_275_perm_0 = const()[name = tensor("op_275_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87485632))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87928064))), name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87928256)))]; + tensor tensor_15_cast = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_13_cast)[name = tensor("tensor_15_cast")]; + tensor var_280 = const()[name = tensor("op_280"), val = tensor([1, -1, 12, 64])]; + tensor var_281_cast = reshape(shape = var_280, x = tensor_15_cast)[name = tensor("op_281_cast")]; + tensor var_282_perm_0 = const()[name = tensor("op_282_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_289 = const()[name = tensor("op_289"), val = tensor([1, 77, 12, 64])]; + tensor var_290_cast = reshape(shape = var_289, x = tensor_17_cast)[name = tensor("op_290_cast")]; + tensor var_291_perm_0 = const()[name = tensor("op_291_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_293 = const()[name = tensor("op_293"), val = tensor([12, -1, 64])]; + tensor transpose_49 = transpose(perm = var_291_perm_0, x = var_290_cast)[name = tensor("transpose_49")]; + tensor query_states_5_cast = reshape(shape = var_293, x = transpose_49)[name = tensor("query_states_5_cast")]; + tensor var_295 = const()[name = tensor("op_295"), val = tensor([12, -1, 64])]; + tensor transpose_48 = transpose(perm = var_275_perm_0, x = var_274_cast)[name = tensor("transpose_48")]; + tensor key_states_11_cast = reshape(shape = var_295, x = transpose_48)[name = tensor("key_states_11_cast")]; + tensor var_297 = const()[name = tensor("op_297"), val = tensor([12, -1, 64])]; + tensor transpose_47 = transpose(perm = var_282_perm_0, x = var_281_cast)[name = tensor("transpose_47")]; + tensor value_states_11_cast = reshape(shape = var_297, x = transpose_47)[name = tensor("value_states_11_cast")]; + tensor var_300_perm_0 = const()[name = tensor("op_300_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_13_transpose_x_0 = const()[name = tensor("attn_weights_13_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_13_transpose_y_0 = const()[name = tensor("attn_weights_13_transpose_y_0"), val = tensor(false)]; + tensor transpose_46 = transpose(perm = var_300_perm_0, x = key_states_11_cast)[name = tensor("transpose_46")]; + tensor attn_weights_13_cast = matmul(transpose_x = attn_weights_13_transpose_x_0, transpose_y = attn_weights_13_transpose_y_0, x = query_states_5_cast, y = transpose_46)[name = tensor("attn_weights_13_cast")]; + tensor var_302 = const()[name = tensor("op_302"), val = tensor([1, 12, 77, 77])]; + tensor var_303_cast = reshape(shape = var_302, x = attn_weights_13_cast)[name = tensor("op_303_cast")]; + tensor attn_weights_15_cast = add(x = var_303_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_15_cast")]; + tensor var_308 = const()[name = tensor("op_308"), val = tensor([12, 77, 77])]; + tensor input_37_cast = reshape(shape = var_308, x = attn_weights_15_cast)[name = tensor("input_37_cast")]; + tensor input_39_cast = softmax(axis = var_5, x = input_37_cast)[name = tensor("input_39_cast")]; + tensor attn_output_13_transpose_x_0 = const()[name = tensor("attn_output_13_transpose_x_0"), val = tensor(false)]; + tensor attn_output_13_transpose_y_0 = const()[name = tensor("attn_output_13_transpose_y_0"), val = tensor(false)]; + tensor attn_output_13_cast = matmul(transpose_x = attn_output_13_transpose_x_0, transpose_y = attn_output_13_transpose_y_0, x = input_39_cast, y = value_states_11_cast)[name = tensor("attn_output_13_cast")]; + tensor var_313 = const()[name = tensor("op_313"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_15_cast = reshape(shape = var_313, x = attn_output_13_cast)[name = tensor("attn_output_15_cast")]; + tensor attn_output_17_perm_0 = const()[name = tensor("attn_output_17_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_316 = const()[name = tensor("op_316"), val = tensor([1, 77, 768])]; + tensor transpose_45 = transpose(perm = attn_output_17_perm_0, x = attn_output_15_cast)[name = tensor("transpose_45")]; + tensor input_41_cast = reshape(shape = var_316, x = transpose_45)[name = tensor("input_41_cast")]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87929856))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88372288))), name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88372480)))]; + tensor hidden_states_15_cast = linear(bias = text_encoder_text_model_encoder_layers_2_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_self_attn_out_proj_weight_to_fp16_palettized, x = input_41_cast)[name = tensor("hidden_states_15_cast")]; + tensor input_43_cast = add(x = input_35_cast, y = hidden_states_15_cast)[name = tensor("input_43_cast")]; + tensor input_45_axes_0 = const()[name = tensor("input_45_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_2_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88374080)))]; + tensor text_encoder_text_model_encoder_layers_2_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88375680)))]; + tensor input_45_cast = layer_norm(axes = input_45_axes_0, beta = text_encoder_text_model_encoder_layers_2_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_2_layer_norm2_weight_to_fp16, x = input_43_cast)[name = tensor("input_45_cast")]; + tensor text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88377280))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90146816))), name = tensor("text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([3072, 768])]; + tensor text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90147008))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90149376))), name = tensor("text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor input_47_cast = linear(bias = text_encoder_text_model_encoder_layers_2_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_2_mlp_fc1_weight_to_fp16_palettized, x = input_45_cast)[name = tensor("input_47_cast")]; + tensor var_331_to_fp16 = const()[name = tensor("op_331_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_332_cast = mul(x = input_47_cast, y = var_331_to_fp16)[name = tensor("op_332_cast")]; + tensor var_333_cast = sigmoid(x = var_332_cast)[name = tensor("op_333_cast")]; + tensor input_49_cast = mul(x = input_47_cast, y = var_333_cast)[name = tensor("input_49_cast")]; + tensor text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90149568))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91919104))), name = tensor("text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([768, 3072])]; + tensor text_encoder_text_model_encoder_layers_2_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_2_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91919296)))]; + tensor hidden_states_17_cast = linear(bias = text_encoder_text_model_encoder_layers_2_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_2_mlp_fc2_weight_to_fp16_palettized, x = input_49_cast)[name = tensor("hidden_states_17_cast")]; + tensor input_51_cast = add(x = input_43_cast, y = hidden_states_17_cast)[name = tensor("input_51_cast")]; + tensor hidden_states_19_axes_0 = const()[name = tensor("hidden_states_19_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_3_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91920896)))]; + tensor text_encoder_text_model_encoder_layers_3_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91922496)))]; + tensor hidden_states_19_cast = layer_norm(axes = hidden_states_19_axes_0, beta = text_encoder_text_model_encoder_layers_3_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_3_layer_norm1_weight_to_fp16, x = input_51_cast)[name = tensor("hidden_states_19_cast")]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91924096))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(92366528))), name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(92366720)))]; + tensor var_357_cast = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_19_cast)[name = tensor("op_357_cast")]; + tensor var_358_to_fp16 = const()[name = tensor("op_358_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_23_cast = mul(x = var_357_cast, y = var_358_to_fp16)[name = tensor("tensor_23_cast")]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(92368320))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(92810752))), name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(92810944)))]; + tensor tensor_19_cast = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_19_cast)[name = tensor("tensor_19_cast")]; + tensor var_363 = const()[name = tensor("op_363"), val = tensor([1, -1, 12, 64])]; + tensor var_364_cast = reshape(shape = var_363, x = tensor_19_cast)[name = tensor("op_364_cast")]; + tensor var_365_perm_0 = const()[name = tensor("op_365_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(92812544))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93254976))), name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93255168)))]; + tensor tensor_21_cast = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_19_cast)[name = tensor("tensor_21_cast")]; + tensor var_370 = const()[name = tensor("op_370"), val = tensor([1, -1, 12, 64])]; + tensor var_371_cast = reshape(shape = var_370, x = tensor_21_cast)[name = tensor("op_371_cast")]; + tensor var_372_perm_0 = const()[name = tensor("op_372_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_379 = const()[name = tensor("op_379"), val = tensor([1, 77, 12, 64])]; + tensor var_380_cast = reshape(shape = var_379, x = tensor_23_cast)[name = tensor("op_380_cast")]; + tensor var_381_perm_0 = const()[name = tensor("op_381_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_383 = const()[name = tensor("op_383"), val = tensor([12, -1, 64])]; + tensor transpose_44 = transpose(perm = var_381_perm_0, x = var_380_cast)[name = tensor("transpose_44")]; + tensor query_states_7_cast = reshape(shape = var_383, x = transpose_44)[name = tensor("query_states_7_cast")]; + tensor var_385 = const()[name = tensor("op_385"), val = tensor([12, -1, 64])]; + tensor transpose_43 = transpose(perm = var_365_perm_0, x = var_364_cast)[name = tensor("transpose_43")]; + tensor key_states_15_cast = reshape(shape = var_385, x = transpose_43)[name = tensor("key_states_15_cast")]; + tensor var_387 = const()[name = tensor("op_387"), val = tensor([12, -1, 64])]; + tensor transpose_42 = transpose(perm = var_372_perm_0, x = var_371_cast)[name = tensor("transpose_42")]; + tensor value_states_15_cast = reshape(shape = var_387, x = transpose_42)[name = tensor("value_states_15_cast")]; + tensor var_390_perm_0 = const()[name = tensor("op_390_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_19_transpose_x_0 = const()[name = tensor("attn_weights_19_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_19_transpose_y_0 = const()[name = tensor("attn_weights_19_transpose_y_0"), val = tensor(false)]; + tensor transpose_41 = transpose(perm = var_390_perm_0, x = key_states_15_cast)[name = tensor("transpose_41")]; + tensor attn_weights_19_cast = matmul(transpose_x = attn_weights_19_transpose_x_0, transpose_y = attn_weights_19_transpose_y_0, x = query_states_7_cast, y = transpose_41)[name = tensor("attn_weights_19_cast")]; + tensor var_392 = const()[name = tensor("op_392"), val = tensor([1, 12, 77, 77])]; + tensor var_393_cast = reshape(shape = var_392, x = attn_weights_19_cast)[name = tensor("op_393_cast")]; + tensor attn_weights_21_cast = add(x = var_393_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_21_cast")]; + tensor var_398 = const()[name = tensor("op_398"), val = tensor([12, 77, 77])]; + tensor input_53_cast = reshape(shape = var_398, x = attn_weights_21_cast)[name = tensor("input_53_cast")]; + tensor input_55_cast = softmax(axis = var_5, x = input_53_cast)[name = tensor("input_55_cast")]; + tensor attn_output_19_transpose_x_0 = const()[name = tensor("attn_output_19_transpose_x_0"), val = tensor(false)]; + tensor attn_output_19_transpose_y_0 = const()[name = tensor("attn_output_19_transpose_y_0"), val = tensor(false)]; + tensor attn_output_19_cast = matmul(transpose_x = attn_output_19_transpose_x_0, transpose_y = attn_output_19_transpose_y_0, x = input_55_cast, y = value_states_15_cast)[name = tensor("attn_output_19_cast")]; + tensor var_403 = const()[name = tensor("op_403"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_21_cast = reshape(shape = var_403, x = attn_output_19_cast)[name = tensor("attn_output_21_cast")]; + tensor attn_output_23_perm_0 = const()[name = tensor("attn_output_23_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_406 = const()[name = tensor("op_406"), val = tensor([1, 77, 768])]; + tensor transpose_40 = transpose(perm = attn_output_23_perm_0, x = attn_output_21_cast)[name = tensor("transpose_40")]; + tensor input_57_cast = reshape(shape = var_406, x = transpose_40)[name = tensor("input_57_cast")]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93256768))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93699200))), name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93699392)))]; + tensor hidden_states_21_cast = linear(bias = text_encoder_text_model_encoder_layers_3_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_self_attn_out_proj_weight_to_fp16_palettized, x = input_57_cast)[name = tensor("hidden_states_21_cast")]; + tensor input_59_cast = add(x = input_51_cast, y = hidden_states_21_cast)[name = tensor("input_59_cast")]; + tensor input_61_axes_0 = const()[name = tensor("input_61_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_3_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93700992)))]; + tensor text_encoder_text_model_encoder_layers_3_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93702592)))]; + tensor input_61_cast = layer_norm(axes = input_61_axes_0, beta = text_encoder_text_model_encoder_layers_3_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_3_layer_norm2_weight_to_fp16, x = input_59_cast)[name = tensor("input_61_cast")]; + tensor text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93704192))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(95473728))), name = tensor("text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([3072, 768])]; + tensor text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(95473920))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(95476288))), name = tensor("text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor input_63_cast = linear(bias = text_encoder_text_model_encoder_layers_3_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_3_mlp_fc1_weight_to_fp16_palettized, x = input_61_cast)[name = tensor("input_63_cast")]; + tensor var_421_to_fp16 = const()[name = tensor("op_421_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_422_cast = mul(x = input_63_cast, y = var_421_to_fp16)[name = tensor("op_422_cast")]; + tensor var_423_cast = sigmoid(x = var_422_cast)[name = tensor("op_423_cast")]; + tensor input_65_cast = mul(x = input_63_cast, y = var_423_cast)[name = tensor("input_65_cast")]; + tensor text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(95476480))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97246016))), name = tensor("text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([768, 3072])]; + tensor text_encoder_text_model_encoder_layers_3_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_3_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97246208)))]; + tensor hidden_states_23_cast = linear(bias = text_encoder_text_model_encoder_layers_3_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_3_mlp_fc2_weight_to_fp16_palettized, x = input_65_cast)[name = tensor("hidden_states_23_cast")]; + tensor input_67_cast = add(x = input_59_cast, y = hidden_states_23_cast)[name = tensor("input_67_cast")]; + tensor hidden_states_25_axes_0 = const()[name = tensor("hidden_states_25_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_4_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97247808)))]; + tensor text_encoder_text_model_encoder_layers_4_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97249408)))]; + tensor hidden_states_25_cast = layer_norm(axes = hidden_states_25_axes_0, beta = text_encoder_text_model_encoder_layers_4_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_4_layer_norm1_weight_to_fp16, x = input_67_cast)[name = tensor("hidden_states_25_cast")]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97251008))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97693440))), name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97693632)))]; + tensor var_447_cast = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_25_cast)[name = tensor("op_447_cast")]; + tensor var_448_to_fp16 = const()[name = tensor("op_448_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_29_cast = mul(x = var_447_cast, y = var_448_to_fp16)[name = tensor("tensor_29_cast")]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97695232))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(98137664))), name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(98137856)))]; + tensor tensor_25_cast = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_25_cast)[name = tensor("tensor_25_cast")]; + tensor var_453 = const()[name = tensor("op_453"), val = tensor([1, -1, 12, 64])]; + tensor var_454_cast = reshape(shape = var_453, x = tensor_25_cast)[name = tensor("op_454_cast")]; + tensor var_455_perm_0 = const()[name = tensor("op_455_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(98139456))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(98581888))), name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(98582080)))]; + tensor tensor_27_cast = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_25_cast)[name = tensor("tensor_27_cast")]; + tensor var_460 = const()[name = tensor("op_460"), val = tensor([1, -1, 12, 64])]; + tensor var_461_cast = reshape(shape = var_460, x = tensor_27_cast)[name = tensor("op_461_cast")]; + tensor var_462_perm_0 = const()[name = tensor("op_462_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_469 = const()[name = tensor("op_469"), val = tensor([1, 77, 12, 64])]; + tensor var_470_cast = reshape(shape = var_469, x = tensor_29_cast)[name = tensor("op_470_cast")]; + tensor var_471_perm_0 = const()[name = tensor("op_471_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_473 = const()[name = tensor("op_473"), val = tensor([12, -1, 64])]; + tensor transpose_39 = transpose(perm = var_471_perm_0, x = var_470_cast)[name = tensor("transpose_39")]; + tensor query_states_9_cast = reshape(shape = var_473, x = transpose_39)[name = tensor("query_states_9_cast")]; + tensor var_475 = const()[name = tensor("op_475"), val = tensor([12, -1, 64])]; + tensor transpose_38 = transpose(perm = var_455_perm_0, x = var_454_cast)[name = tensor("transpose_38")]; + tensor key_states_19_cast = reshape(shape = var_475, x = transpose_38)[name = tensor("key_states_19_cast")]; + tensor var_477 = const()[name = tensor("op_477"), val = tensor([12, -1, 64])]; + tensor transpose_37 = transpose(perm = var_462_perm_0, x = var_461_cast)[name = tensor("transpose_37")]; + tensor value_states_19_cast = reshape(shape = var_477, x = transpose_37)[name = tensor("value_states_19_cast")]; + tensor var_480_perm_0 = const()[name = tensor("op_480_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_25_transpose_x_0 = const()[name = tensor("attn_weights_25_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_25_transpose_y_0 = const()[name = tensor("attn_weights_25_transpose_y_0"), val = tensor(false)]; + tensor transpose_36 = transpose(perm = var_480_perm_0, x = key_states_19_cast)[name = tensor("transpose_36")]; + tensor attn_weights_25_cast = matmul(transpose_x = attn_weights_25_transpose_x_0, transpose_y = attn_weights_25_transpose_y_0, x = query_states_9_cast, y = transpose_36)[name = tensor("attn_weights_25_cast")]; + tensor var_482 = const()[name = tensor("op_482"), val = tensor([1, 12, 77, 77])]; + tensor var_483_cast = reshape(shape = var_482, x = attn_weights_25_cast)[name = tensor("op_483_cast")]; + tensor attn_weights_27_cast = add(x = var_483_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_27_cast")]; + tensor var_488 = const()[name = tensor("op_488"), val = tensor([12, 77, 77])]; + tensor input_69_cast = reshape(shape = var_488, x = attn_weights_27_cast)[name = tensor("input_69_cast")]; + tensor input_71_cast = softmax(axis = var_5, x = input_69_cast)[name = tensor("input_71_cast")]; + tensor attn_output_25_transpose_x_0 = const()[name = tensor("attn_output_25_transpose_x_0"), val = tensor(false)]; + tensor attn_output_25_transpose_y_0 = const()[name = tensor("attn_output_25_transpose_y_0"), val = tensor(false)]; + tensor attn_output_25_cast = matmul(transpose_x = attn_output_25_transpose_x_0, transpose_y = attn_output_25_transpose_y_0, x = input_71_cast, y = value_states_19_cast)[name = tensor("attn_output_25_cast")]; + tensor var_493 = const()[name = tensor("op_493"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_27_cast = reshape(shape = var_493, x = attn_output_25_cast)[name = tensor("attn_output_27_cast")]; + tensor attn_output_29_perm_0 = const()[name = tensor("attn_output_29_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_496 = const()[name = tensor("op_496"), val = tensor([1, 77, 768])]; + tensor transpose_35 = transpose(perm = attn_output_29_perm_0, x = attn_output_27_cast)[name = tensor("transpose_35")]; + tensor input_73_cast = reshape(shape = var_496, x = transpose_35)[name = tensor("input_73_cast")]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(98583680))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99026112))), name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99026304)))]; + tensor hidden_states_27_cast = linear(bias = text_encoder_text_model_encoder_layers_4_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_self_attn_out_proj_weight_to_fp16_palettized, x = input_73_cast)[name = tensor("hidden_states_27_cast")]; + tensor input_75_cast = add(x = input_67_cast, y = hidden_states_27_cast)[name = tensor("input_75_cast")]; + tensor input_77_axes_0 = const()[name = tensor("input_77_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_4_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99027904)))]; + tensor text_encoder_text_model_encoder_layers_4_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99029504)))]; + tensor input_77_cast = layer_norm(axes = input_77_axes_0, beta = text_encoder_text_model_encoder_layers_4_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_4_layer_norm2_weight_to_fp16, x = input_75_cast)[name = tensor("input_77_cast")]; + tensor text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99031104))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(100800640))), name = tensor("text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([3072, 768])]; + tensor text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(100800832))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(100803200))), name = tensor("text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor input_79_cast = linear(bias = text_encoder_text_model_encoder_layers_4_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_4_mlp_fc1_weight_to_fp16_palettized, x = input_77_cast)[name = tensor("input_79_cast")]; + tensor var_511_to_fp16 = const()[name = tensor("op_511_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_512_cast = mul(x = input_79_cast, y = var_511_to_fp16)[name = tensor("op_512_cast")]; + tensor var_513_cast = sigmoid(x = var_512_cast)[name = tensor("op_513_cast")]; + tensor input_81_cast = mul(x = input_79_cast, y = var_513_cast)[name = tensor("input_81_cast")]; + tensor text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(100803392))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102572928))), name = tensor("text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([768, 3072])]; + tensor text_encoder_text_model_encoder_layers_4_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_4_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102573120)))]; + tensor hidden_states_29_cast = linear(bias = text_encoder_text_model_encoder_layers_4_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_4_mlp_fc2_weight_to_fp16_palettized, x = input_81_cast)[name = tensor("hidden_states_29_cast")]; + tensor input_83_cast = add(x = input_75_cast, y = hidden_states_29_cast)[name = tensor("input_83_cast")]; + tensor hidden_states_31_axes_0 = const()[name = tensor("hidden_states_31_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_5_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102574720)))]; + tensor text_encoder_text_model_encoder_layers_5_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102576320)))]; + tensor hidden_states_31_cast = layer_norm(axes = hidden_states_31_axes_0, beta = text_encoder_text_model_encoder_layers_5_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_5_layer_norm1_weight_to_fp16, x = input_83_cast)[name = tensor("hidden_states_31_cast")]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102577920))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103020352))), name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103020544)))]; + tensor var_537_cast = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_31_cast)[name = tensor("op_537_cast")]; + tensor var_538_to_fp16 = const()[name = tensor("op_538_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_35_cast = mul(x = var_537_cast, y = var_538_to_fp16)[name = tensor("tensor_35_cast")]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103022144))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103464576))), name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103464768)))]; + tensor tensor_31_cast = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_31_cast)[name = tensor("tensor_31_cast")]; + tensor var_543 = const()[name = tensor("op_543"), val = tensor([1, -1, 12, 64])]; + tensor var_544_cast = reshape(shape = var_543, x = tensor_31_cast)[name = tensor("op_544_cast")]; + tensor var_545_perm_0 = const()[name = tensor("op_545_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103466368))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103908800))), name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103908992)))]; + tensor tensor_33_cast = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_31_cast)[name = tensor("tensor_33_cast")]; + tensor var_550 = const()[name = tensor("op_550"), val = tensor([1, -1, 12, 64])]; + tensor var_551_cast = reshape(shape = var_550, x = tensor_33_cast)[name = tensor("op_551_cast")]; + tensor var_552_perm_0 = const()[name = tensor("op_552_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_559 = const()[name = tensor("op_559"), val = tensor([1, 77, 12, 64])]; + tensor var_560_cast = reshape(shape = var_559, x = tensor_35_cast)[name = tensor("op_560_cast")]; + tensor var_561_perm_0 = const()[name = tensor("op_561_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_563 = const()[name = tensor("op_563"), val = tensor([12, -1, 64])]; + tensor transpose_34 = transpose(perm = var_561_perm_0, x = var_560_cast)[name = tensor("transpose_34")]; + tensor query_states_11_cast = reshape(shape = var_563, x = transpose_34)[name = tensor("query_states_11_cast")]; + tensor var_565 = const()[name = tensor("op_565"), val = tensor([12, -1, 64])]; + tensor transpose_33 = transpose(perm = var_545_perm_0, x = var_544_cast)[name = tensor("transpose_33")]; + tensor key_states_23_cast = reshape(shape = var_565, x = transpose_33)[name = tensor("key_states_23_cast")]; + tensor var_567 = const()[name = tensor("op_567"), val = tensor([12, -1, 64])]; + tensor transpose_32 = transpose(perm = var_552_perm_0, x = var_551_cast)[name = tensor("transpose_32")]; + tensor value_states_23_cast = reshape(shape = var_567, x = transpose_32)[name = tensor("value_states_23_cast")]; + tensor var_570_perm_0 = const()[name = tensor("op_570_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_31_transpose_x_0 = const()[name = tensor("attn_weights_31_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_31_transpose_y_0 = const()[name = tensor("attn_weights_31_transpose_y_0"), val = tensor(false)]; + tensor transpose_31 = transpose(perm = var_570_perm_0, x = key_states_23_cast)[name = tensor("transpose_31")]; + tensor attn_weights_31_cast = matmul(transpose_x = attn_weights_31_transpose_x_0, transpose_y = attn_weights_31_transpose_y_0, x = query_states_11_cast, y = transpose_31)[name = tensor("attn_weights_31_cast")]; + tensor var_572 = const()[name = tensor("op_572"), val = tensor([1, 12, 77, 77])]; + tensor var_573_cast = reshape(shape = var_572, x = attn_weights_31_cast)[name = tensor("op_573_cast")]; + tensor attn_weights_33_cast = add(x = var_573_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_33_cast")]; + tensor var_578 = const()[name = tensor("op_578"), val = tensor([12, 77, 77])]; + tensor input_85_cast = reshape(shape = var_578, x = attn_weights_33_cast)[name = tensor("input_85_cast")]; + tensor input_87_cast = softmax(axis = var_5, x = input_85_cast)[name = tensor("input_87_cast")]; + tensor attn_output_31_transpose_x_0 = const()[name = tensor("attn_output_31_transpose_x_0"), val = tensor(false)]; + tensor attn_output_31_transpose_y_0 = const()[name = tensor("attn_output_31_transpose_y_0"), val = tensor(false)]; + tensor attn_output_31_cast = matmul(transpose_x = attn_output_31_transpose_x_0, transpose_y = attn_output_31_transpose_y_0, x = input_87_cast, y = value_states_23_cast)[name = tensor("attn_output_31_cast")]; + tensor var_583 = const()[name = tensor("op_583"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_33_cast = reshape(shape = var_583, x = attn_output_31_cast)[name = tensor("attn_output_33_cast")]; + tensor attn_output_35_perm_0 = const()[name = tensor("attn_output_35_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_586 = const()[name = tensor("op_586"), val = tensor([1, 77, 768])]; + tensor transpose_30 = transpose(perm = attn_output_35_perm_0, x = attn_output_33_cast)[name = tensor("transpose_30")]; + tensor input_89_cast = reshape(shape = var_586, x = transpose_30)[name = tensor("input_89_cast")]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103910592))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104353024))), name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104353216)))]; + tensor hidden_states_33_cast = linear(bias = text_encoder_text_model_encoder_layers_5_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_self_attn_out_proj_weight_to_fp16_palettized, x = input_89_cast)[name = tensor("hidden_states_33_cast")]; + tensor input_91_cast = add(x = input_83_cast, y = hidden_states_33_cast)[name = tensor("input_91_cast")]; + tensor input_93_axes_0 = const()[name = tensor("input_93_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_5_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104354816)))]; + tensor text_encoder_text_model_encoder_layers_5_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104356416)))]; + tensor input_93_cast = layer_norm(axes = input_93_axes_0, beta = text_encoder_text_model_encoder_layers_5_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_5_layer_norm2_weight_to_fp16, x = input_91_cast)[name = tensor("input_93_cast")]; + tensor text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104358016))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(106127552))), name = tensor("text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([3072, 768])]; + tensor text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(106127744))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(106130112))), name = tensor("text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor input_95_cast = linear(bias = text_encoder_text_model_encoder_layers_5_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_5_mlp_fc1_weight_to_fp16_palettized, x = input_93_cast)[name = tensor("input_95_cast")]; + tensor var_601_to_fp16 = const()[name = tensor("op_601_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_602_cast = mul(x = input_95_cast, y = var_601_to_fp16)[name = tensor("op_602_cast")]; + tensor var_603_cast = sigmoid(x = var_602_cast)[name = tensor("op_603_cast")]; + tensor input_97_cast = mul(x = input_95_cast, y = var_603_cast)[name = tensor("input_97_cast")]; + tensor text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(106130304))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107899840))), name = tensor("text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([768, 3072])]; + tensor text_encoder_text_model_encoder_layers_5_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_5_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107900032)))]; + tensor hidden_states_35_cast = linear(bias = text_encoder_text_model_encoder_layers_5_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_5_mlp_fc2_weight_to_fp16_palettized, x = input_97_cast)[name = tensor("hidden_states_35_cast")]; + tensor input_99_cast = add(x = input_91_cast, y = hidden_states_35_cast)[name = tensor("input_99_cast")]; + tensor hidden_states_37_axes_0 = const()[name = tensor("hidden_states_37_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_6_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107901632)))]; + tensor text_encoder_text_model_encoder_layers_6_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107903232)))]; + tensor hidden_states_37_cast = layer_norm(axes = hidden_states_37_axes_0, beta = text_encoder_text_model_encoder_layers_6_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_6_layer_norm1_weight_to_fp16, x = input_99_cast)[name = tensor("hidden_states_37_cast")]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(107904832))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108347264))), name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108347456)))]; + tensor var_627_cast = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_37_cast)[name = tensor("op_627_cast")]; + tensor var_628_to_fp16 = const()[name = tensor("op_628_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_41_cast = mul(x = var_627_cast, y = var_628_to_fp16)[name = tensor("tensor_41_cast")]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108349056))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108791488))), name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108791680)))]; + tensor tensor_37_cast = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_37_cast)[name = tensor("tensor_37_cast")]; + tensor var_633 = const()[name = tensor("op_633"), val = tensor([1, -1, 12, 64])]; + tensor var_634_cast = reshape(shape = var_633, x = tensor_37_cast)[name = tensor("op_634_cast")]; + tensor var_635_perm_0 = const()[name = tensor("op_635_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108793280))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109235712))), name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109235904)))]; + tensor tensor_39_cast = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_37_cast)[name = tensor("tensor_39_cast")]; + tensor var_640 = const()[name = tensor("op_640"), val = tensor([1, -1, 12, 64])]; + tensor var_641_cast = reshape(shape = var_640, x = tensor_39_cast)[name = tensor("op_641_cast")]; + tensor var_642_perm_0 = const()[name = tensor("op_642_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_649 = const()[name = tensor("op_649"), val = tensor([1, 77, 12, 64])]; + tensor var_650_cast = reshape(shape = var_649, x = tensor_41_cast)[name = tensor("op_650_cast")]; + tensor var_651_perm_0 = const()[name = tensor("op_651_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_653 = const()[name = tensor("op_653"), val = tensor([12, -1, 64])]; + tensor transpose_29 = transpose(perm = var_651_perm_0, x = var_650_cast)[name = tensor("transpose_29")]; + tensor query_states_13_cast = reshape(shape = var_653, x = transpose_29)[name = tensor("query_states_13_cast")]; + tensor var_655 = const()[name = tensor("op_655"), val = tensor([12, -1, 64])]; + tensor transpose_28 = transpose(perm = var_635_perm_0, x = var_634_cast)[name = tensor("transpose_28")]; + tensor key_states_27_cast = reshape(shape = var_655, x = transpose_28)[name = tensor("key_states_27_cast")]; + tensor var_657 = const()[name = tensor("op_657"), val = tensor([12, -1, 64])]; + tensor transpose_27 = transpose(perm = var_642_perm_0, x = var_641_cast)[name = tensor("transpose_27")]; + tensor value_states_27_cast = reshape(shape = var_657, x = transpose_27)[name = tensor("value_states_27_cast")]; + tensor var_660_perm_0 = const()[name = tensor("op_660_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_37_transpose_x_0 = const()[name = tensor("attn_weights_37_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_37_transpose_y_0 = const()[name = tensor("attn_weights_37_transpose_y_0"), val = tensor(false)]; + tensor transpose_26 = transpose(perm = var_660_perm_0, x = key_states_27_cast)[name = tensor("transpose_26")]; + tensor attn_weights_37_cast = matmul(transpose_x = attn_weights_37_transpose_x_0, transpose_y = attn_weights_37_transpose_y_0, x = query_states_13_cast, y = transpose_26)[name = tensor("attn_weights_37_cast")]; + tensor var_662 = const()[name = tensor("op_662"), val = tensor([1, 12, 77, 77])]; + tensor var_663_cast = reshape(shape = var_662, x = attn_weights_37_cast)[name = tensor("op_663_cast")]; + tensor attn_weights_39_cast = add(x = var_663_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_39_cast")]; + tensor var_668 = const()[name = tensor("op_668"), val = tensor([12, 77, 77])]; + tensor input_101_cast = reshape(shape = var_668, x = attn_weights_39_cast)[name = tensor("input_101_cast")]; + tensor input_103_cast = softmax(axis = var_5, x = input_101_cast)[name = tensor("input_103_cast")]; + tensor attn_output_37_transpose_x_0 = const()[name = tensor("attn_output_37_transpose_x_0"), val = tensor(false)]; + tensor attn_output_37_transpose_y_0 = const()[name = tensor("attn_output_37_transpose_y_0"), val = tensor(false)]; + tensor attn_output_37_cast = matmul(transpose_x = attn_output_37_transpose_x_0, transpose_y = attn_output_37_transpose_y_0, x = input_103_cast, y = value_states_27_cast)[name = tensor("attn_output_37_cast")]; + tensor var_673 = const()[name = tensor("op_673"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_39_cast = reshape(shape = var_673, x = attn_output_37_cast)[name = tensor("attn_output_39_cast")]; + tensor attn_output_41_perm_0 = const()[name = tensor("attn_output_41_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_676 = const()[name = tensor("op_676"), val = tensor([1, 77, 768])]; + tensor transpose_25 = transpose(perm = attn_output_41_perm_0, x = attn_output_39_cast)[name = tensor("transpose_25")]; + tensor input_105_cast = reshape(shape = var_676, x = transpose_25)[name = tensor("input_105_cast")]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109237504))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109679936))), name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109680128)))]; + tensor hidden_states_39_cast = linear(bias = text_encoder_text_model_encoder_layers_6_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_self_attn_out_proj_weight_to_fp16_palettized, x = input_105_cast)[name = tensor("hidden_states_39_cast")]; + tensor input_107_cast = add(x = input_99_cast, y = hidden_states_39_cast)[name = tensor("input_107_cast")]; + tensor input_109_axes_0 = const()[name = tensor("input_109_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_6_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109681728)))]; + tensor text_encoder_text_model_encoder_layers_6_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109683328)))]; + tensor input_109_cast = layer_norm(axes = input_109_axes_0, beta = text_encoder_text_model_encoder_layers_6_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_6_layer_norm2_weight_to_fp16, x = input_107_cast)[name = tensor("input_109_cast")]; + tensor text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(109684928))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(111454464))), name = tensor("text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([3072, 768])]; + tensor text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(111454656))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(111457024))), name = tensor("text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor input_111_cast = linear(bias = text_encoder_text_model_encoder_layers_6_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_6_mlp_fc1_weight_to_fp16_palettized, x = input_109_cast)[name = tensor("input_111_cast")]; + tensor var_691_to_fp16 = const()[name = tensor("op_691_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_692_cast = mul(x = input_111_cast, y = var_691_to_fp16)[name = tensor("op_692_cast")]; + tensor var_693_cast = sigmoid(x = var_692_cast)[name = tensor("op_693_cast")]; + tensor input_113_cast = mul(x = input_111_cast, y = var_693_cast)[name = tensor("input_113_cast")]; + tensor text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(111457216))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113226752))), name = tensor("text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([768, 3072])]; + tensor text_encoder_text_model_encoder_layers_6_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_6_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113226944)))]; + tensor hidden_states_41_cast = linear(bias = text_encoder_text_model_encoder_layers_6_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_6_mlp_fc2_weight_to_fp16_palettized, x = input_113_cast)[name = tensor("hidden_states_41_cast")]; + tensor input_115_cast = add(x = input_107_cast, y = hidden_states_41_cast)[name = tensor("input_115_cast")]; + tensor hidden_states_43_axes_0 = const()[name = tensor("hidden_states_43_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_7_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113228544)))]; + tensor text_encoder_text_model_encoder_layers_7_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113230144)))]; + tensor hidden_states_43_cast = layer_norm(axes = hidden_states_43_axes_0, beta = text_encoder_text_model_encoder_layers_7_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_7_layer_norm1_weight_to_fp16, x = input_115_cast)[name = tensor("hidden_states_43_cast")]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113231744))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113674176))), name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113674368)))]; + tensor var_717_cast = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_43_cast)[name = tensor("op_717_cast")]; + tensor var_718_to_fp16 = const()[name = tensor("op_718_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_47_cast = mul(x = var_717_cast, y = var_718_to_fp16)[name = tensor("tensor_47_cast")]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113675968))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(114118400))), name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(114118592)))]; + tensor tensor_43_cast = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_43_cast)[name = tensor("tensor_43_cast")]; + tensor var_723 = const()[name = tensor("op_723"), val = tensor([1, -1, 12, 64])]; + tensor var_724_cast = reshape(shape = var_723, x = tensor_43_cast)[name = tensor("op_724_cast")]; + tensor var_725_perm_0 = const()[name = tensor("op_725_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(114120192))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(114562624))), name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(114562816)))]; + tensor tensor_45_cast = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_43_cast)[name = tensor("tensor_45_cast")]; + tensor var_730 = const()[name = tensor("op_730"), val = tensor([1, -1, 12, 64])]; + tensor var_731_cast = reshape(shape = var_730, x = tensor_45_cast)[name = tensor("op_731_cast")]; + tensor var_732_perm_0 = const()[name = tensor("op_732_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_739 = const()[name = tensor("op_739"), val = tensor([1, 77, 12, 64])]; + tensor var_740_cast = reshape(shape = var_739, x = tensor_47_cast)[name = tensor("op_740_cast")]; + tensor var_741_perm_0 = const()[name = tensor("op_741_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_743 = const()[name = tensor("op_743"), val = tensor([12, -1, 64])]; + tensor transpose_24 = transpose(perm = var_741_perm_0, x = var_740_cast)[name = tensor("transpose_24")]; + tensor query_states_15_cast = reshape(shape = var_743, x = transpose_24)[name = tensor("query_states_15_cast")]; + tensor var_745 = const()[name = tensor("op_745"), val = tensor([12, -1, 64])]; + tensor transpose_23 = transpose(perm = var_725_perm_0, x = var_724_cast)[name = tensor("transpose_23")]; + tensor key_states_31_cast = reshape(shape = var_745, x = transpose_23)[name = tensor("key_states_31_cast")]; + tensor var_747 = const()[name = tensor("op_747"), val = tensor([12, -1, 64])]; + tensor transpose_22 = transpose(perm = var_732_perm_0, x = var_731_cast)[name = tensor("transpose_22")]; + tensor value_states_31_cast = reshape(shape = var_747, x = transpose_22)[name = tensor("value_states_31_cast")]; + tensor var_750_perm_0 = const()[name = tensor("op_750_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_43_transpose_x_0 = const()[name = tensor("attn_weights_43_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_43_transpose_y_0 = const()[name = tensor("attn_weights_43_transpose_y_0"), val = tensor(false)]; + tensor transpose_21 = transpose(perm = var_750_perm_0, x = key_states_31_cast)[name = tensor("transpose_21")]; + tensor attn_weights_43_cast = matmul(transpose_x = attn_weights_43_transpose_x_0, transpose_y = attn_weights_43_transpose_y_0, x = query_states_15_cast, y = transpose_21)[name = tensor("attn_weights_43_cast")]; + tensor var_752 = const()[name = tensor("op_752"), val = tensor([1, 12, 77, 77])]; + tensor var_753_cast = reshape(shape = var_752, x = attn_weights_43_cast)[name = tensor("op_753_cast")]; + tensor attn_weights_45_cast = add(x = var_753_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_45_cast")]; + tensor var_758 = const()[name = tensor("op_758"), val = tensor([12, 77, 77])]; + tensor input_117_cast = reshape(shape = var_758, x = attn_weights_45_cast)[name = tensor("input_117_cast")]; + tensor input_119_cast = softmax(axis = var_5, x = input_117_cast)[name = tensor("input_119_cast")]; + tensor attn_output_43_transpose_x_0 = const()[name = tensor("attn_output_43_transpose_x_0"), val = tensor(false)]; + tensor attn_output_43_transpose_y_0 = const()[name = tensor("attn_output_43_transpose_y_0"), val = tensor(false)]; + tensor attn_output_43_cast = matmul(transpose_x = attn_output_43_transpose_x_0, transpose_y = attn_output_43_transpose_y_0, x = input_119_cast, y = value_states_31_cast)[name = tensor("attn_output_43_cast")]; + tensor var_763 = const()[name = tensor("op_763"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_45_cast = reshape(shape = var_763, x = attn_output_43_cast)[name = tensor("attn_output_45_cast")]; + tensor attn_output_47_perm_0 = const()[name = tensor("attn_output_47_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_766 = const()[name = tensor("op_766"), val = tensor([1, 77, 768])]; + tensor transpose_20 = transpose(perm = attn_output_47_perm_0, x = attn_output_45_cast)[name = tensor("transpose_20")]; + tensor input_121_cast = reshape(shape = var_766, x = transpose_20)[name = tensor("input_121_cast")]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(114564416))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115006848))), name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115007040)))]; + tensor hidden_states_45_cast = linear(bias = text_encoder_text_model_encoder_layers_7_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_self_attn_out_proj_weight_to_fp16_palettized, x = input_121_cast)[name = tensor("hidden_states_45_cast")]; + tensor input_123_cast = add(x = input_115_cast, y = hidden_states_45_cast)[name = tensor("input_123_cast")]; + tensor input_125_axes_0 = const()[name = tensor("input_125_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_7_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115008640)))]; + tensor text_encoder_text_model_encoder_layers_7_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115010240)))]; + tensor input_125_cast = layer_norm(axes = input_125_axes_0, beta = text_encoder_text_model_encoder_layers_7_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_7_layer_norm2_weight_to_fp16, x = input_123_cast)[name = tensor("input_125_cast")]; + tensor text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115011840))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(116781376))), name = tensor("text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([3072, 768])]; + tensor text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(116781568))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(116783936))), name = tensor("text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor input_127_cast = linear(bias = text_encoder_text_model_encoder_layers_7_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_7_mlp_fc1_weight_to_fp16_palettized, x = input_125_cast)[name = tensor("input_127_cast")]; + tensor var_781_to_fp16 = const()[name = tensor("op_781_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_782_cast = mul(x = input_127_cast, y = var_781_to_fp16)[name = tensor("op_782_cast")]; + tensor var_783_cast = sigmoid(x = var_782_cast)[name = tensor("op_783_cast")]; + tensor input_129_cast = mul(x = input_127_cast, y = var_783_cast)[name = tensor("input_129_cast")]; + tensor text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(116784128))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(118553664))), name = tensor("text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([768, 3072])]; + tensor text_encoder_text_model_encoder_layers_7_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_7_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(118553856)))]; + tensor hidden_states_47_cast = linear(bias = text_encoder_text_model_encoder_layers_7_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_7_mlp_fc2_weight_to_fp16_palettized, x = input_129_cast)[name = tensor("hidden_states_47_cast")]; + tensor input_131_cast = add(x = input_123_cast, y = hidden_states_47_cast)[name = tensor("input_131_cast")]; + tensor hidden_states_49_axes_0 = const()[name = tensor("hidden_states_49_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_8_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(118555456)))]; + tensor text_encoder_text_model_encoder_layers_8_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(118557056)))]; + tensor hidden_states_49_cast = layer_norm(axes = hidden_states_49_axes_0, beta = text_encoder_text_model_encoder_layers_8_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_8_layer_norm1_weight_to_fp16, x = input_131_cast)[name = tensor("hidden_states_49_cast")]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(118558656))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119001088))), name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119001280)))]; + tensor var_807_cast = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_49_cast)[name = tensor("op_807_cast")]; + tensor var_808_to_fp16 = const()[name = tensor("op_808_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_53_cast = mul(x = var_807_cast, y = var_808_to_fp16)[name = tensor("tensor_53_cast")]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119002880))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119445312))), name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119445504)))]; + tensor tensor_49_cast = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_49_cast)[name = tensor("tensor_49_cast")]; + tensor var_813 = const()[name = tensor("op_813"), val = tensor([1, -1, 12, 64])]; + tensor var_814_cast = reshape(shape = var_813, x = tensor_49_cast)[name = tensor("op_814_cast")]; + tensor var_815_perm_0 = const()[name = tensor("op_815_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119447104))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119889536))), name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119889728)))]; + tensor tensor_51_cast = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_49_cast)[name = tensor("tensor_51_cast")]; + tensor var_820 = const()[name = tensor("op_820"), val = tensor([1, -1, 12, 64])]; + tensor var_821_cast = reshape(shape = var_820, x = tensor_51_cast)[name = tensor("op_821_cast")]; + tensor var_822_perm_0 = const()[name = tensor("op_822_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_829 = const()[name = tensor("op_829"), val = tensor([1, 77, 12, 64])]; + tensor var_830_cast = reshape(shape = var_829, x = tensor_53_cast)[name = tensor("op_830_cast")]; + tensor var_831_perm_0 = const()[name = tensor("op_831_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_833 = const()[name = tensor("op_833"), val = tensor([12, -1, 64])]; + tensor transpose_19 = transpose(perm = var_831_perm_0, x = var_830_cast)[name = tensor("transpose_19")]; + tensor query_states_17_cast = reshape(shape = var_833, x = transpose_19)[name = tensor("query_states_17_cast")]; + tensor var_835 = const()[name = tensor("op_835"), val = tensor([12, -1, 64])]; + tensor transpose_18 = transpose(perm = var_815_perm_0, x = var_814_cast)[name = tensor("transpose_18")]; + tensor key_states_35_cast = reshape(shape = var_835, x = transpose_18)[name = tensor("key_states_35_cast")]; + tensor var_837 = const()[name = tensor("op_837"), val = tensor([12, -1, 64])]; + tensor transpose_17 = transpose(perm = var_822_perm_0, x = var_821_cast)[name = tensor("transpose_17")]; + tensor value_states_35_cast = reshape(shape = var_837, x = transpose_17)[name = tensor("value_states_35_cast")]; + tensor var_840_perm_0 = const()[name = tensor("op_840_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_49_transpose_x_0 = const()[name = tensor("attn_weights_49_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_49_transpose_y_0 = const()[name = tensor("attn_weights_49_transpose_y_0"), val = tensor(false)]; + tensor transpose_16 = transpose(perm = var_840_perm_0, x = key_states_35_cast)[name = tensor("transpose_16")]; + tensor attn_weights_49_cast = matmul(transpose_x = attn_weights_49_transpose_x_0, transpose_y = attn_weights_49_transpose_y_0, x = query_states_17_cast, y = transpose_16)[name = tensor("attn_weights_49_cast")]; + tensor var_842 = const()[name = tensor("op_842"), val = tensor([1, 12, 77, 77])]; + tensor var_843_cast = reshape(shape = var_842, x = attn_weights_49_cast)[name = tensor("op_843_cast")]; + tensor attn_weights_51_cast = add(x = var_843_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_51_cast")]; + tensor var_848 = const()[name = tensor("op_848"), val = tensor([12, 77, 77])]; + tensor input_133_cast = reshape(shape = var_848, x = attn_weights_51_cast)[name = tensor("input_133_cast")]; + tensor input_135_cast = softmax(axis = var_5, x = input_133_cast)[name = tensor("input_135_cast")]; + tensor attn_output_49_transpose_x_0 = const()[name = tensor("attn_output_49_transpose_x_0"), val = tensor(false)]; + tensor attn_output_49_transpose_y_0 = const()[name = tensor("attn_output_49_transpose_y_0"), val = tensor(false)]; + tensor attn_output_49_cast = matmul(transpose_x = attn_output_49_transpose_x_0, transpose_y = attn_output_49_transpose_y_0, x = input_135_cast, y = value_states_35_cast)[name = tensor("attn_output_49_cast")]; + tensor var_853 = const()[name = tensor("op_853"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_51_cast = reshape(shape = var_853, x = attn_output_49_cast)[name = tensor("attn_output_51_cast")]; + tensor attn_output_53_perm_0 = const()[name = tensor("attn_output_53_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_856 = const()[name = tensor("op_856"), val = tensor([1, 77, 768])]; + tensor transpose_15 = transpose(perm = attn_output_53_perm_0, x = attn_output_51_cast)[name = tensor("transpose_15")]; + tensor input_137_cast = reshape(shape = var_856, x = transpose_15)[name = tensor("input_137_cast")]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(119891328))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120333760))), name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120333952)))]; + tensor hidden_states_51_cast = linear(bias = text_encoder_text_model_encoder_layers_8_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_self_attn_out_proj_weight_to_fp16_palettized, x = input_137_cast)[name = tensor("hidden_states_51_cast")]; + tensor input_139_cast = add(x = input_131_cast, y = hidden_states_51_cast)[name = tensor("input_139_cast")]; + tensor input_141_axes_0 = const()[name = tensor("input_141_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_8_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120335552)))]; + tensor text_encoder_text_model_encoder_layers_8_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120337152)))]; + tensor input_141_cast = layer_norm(axes = input_141_axes_0, beta = text_encoder_text_model_encoder_layers_8_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_8_layer_norm2_weight_to_fp16, x = input_139_cast)[name = tensor("input_141_cast")]; + tensor text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120338752))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122108288))), name = tensor("text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([3072, 768])]; + tensor text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122108480))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122110848))), name = tensor("text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor input_143_cast = linear(bias = text_encoder_text_model_encoder_layers_8_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_8_mlp_fc1_weight_to_fp16_palettized, x = input_141_cast)[name = tensor("input_143_cast")]; + tensor var_871_to_fp16 = const()[name = tensor("op_871_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_872_cast = mul(x = input_143_cast, y = var_871_to_fp16)[name = tensor("op_872_cast")]; + tensor var_873_cast = sigmoid(x = var_872_cast)[name = tensor("op_873_cast")]; + tensor input_145_cast = mul(x = input_143_cast, y = var_873_cast)[name = tensor("input_145_cast")]; + tensor text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122111040))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(123880576))), name = tensor("text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([768, 3072])]; + tensor text_encoder_text_model_encoder_layers_8_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_8_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(123880768)))]; + tensor hidden_states_53_cast = linear(bias = text_encoder_text_model_encoder_layers_8_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_8_mlp_fc2_weight_to_fp16_palettized, x = input_145_cast)[name = tensor("hidden_states_53_cast")]; + tensor input_147_cast = add(x = input_139_cast, y = hidden_states_53_cast)[name = tensor("input_147_cast")]; + tensor hidden_states_55_axes_0 = const()[name = tensor("hidden_states_55_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_9_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(123882368)))]; + tensor text_encoder_text_model_encoder_layers_9_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(123883968)))]; + tensor hidden_states_55_cast = layer_norm(axes = hidden_states_55_axes_0, beta = text_encoder_text_model_encoder_layers_9_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_9_layer_norm1_weight_to_fp16, x = input_147_cast)[name = tensor("hidden_states_55_cast")]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(123885568))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(124328000))), name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(124328192)))]; + tensor var_897_cast = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_55_cast)[name = tensor("op_897_cast")]; + tensor var_898_to_fp16 = const()[name = tensor("op_898_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_59_cast = mul(x = var_897_cast, y = var_898_to_fp16)[name = tensor("tensor_59_cast")]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(124329792))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(124772224))), name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(124772416)))]; + tensor tensor_55_cast = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_55_cast)[name = tensor("tensor_55_cast")]; + tensor var_903 = const()[name = tensor("op_903"), val = tensor([1, -1, 12, 64])]; + tensor var_904_cast = reshape(shape = var_903, x = tensor_55_cast)[name = tensor("op_904_cast")]; + tensor var_905_perm_0 = const()[name = tensor("op_905_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(124774016))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125216448))), name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125216640)))]; + tensor tensor_57_cast = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_55_cast)[name = tensor("tensor_57_cast")]; + tensor var_910 = const()[name = tensor("op_910"), val = tensor([1, -1, 12, 64])]; + tensor var_911_cast = reshape(shape = var_910, x = tensor_57_cast)[name = tensor("op_911_cast")]; + tensor var_912_perm_0 = const()[name = tensor("op_912_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_919 = const()[name = tensor("op_919"), val = tensor([1, 77, 12, 64])]; + tensor var_920_cast = reshape(shape = var_919, x = tensor_59_cast)[name = tensor("op_920_cast")]; + tensor var_921_perm_0 = const()[name = tensor("op_921_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_923 = const()[name = tensor("op_923"), val = tensor([12, -1, 64])]; + tensor transpose_14 = transpose(perm = var_921_perm_0, x = var_920_cast)[name = tensor("transpose_14")]; + tensor query_states_19_cast = reshape(shape = var_923, x = transpose_14)[name = tensor("query_states_19_cast")]; + tensor var_925 = const()[name = tensor("op_925"), val = tensor([12, -1, 64])]; + tensor transpose_13 = transpose(perm = var_905_perm_0, x = var_904_cast)[name = tensor("transpose_13")]; + tensor key_states_39_cast = reshape(shape = var_925, x = transpose_13)[name = tensor("key_states_39_cast")]; + tensor var_927 = const()[name = tensor("op_927"), val = tensor([12, -1, 64])]; + tensor transpose_12 = transpose(perm = var_912_perm_0, x = var_911_cast)[name = tensor("transpose_12")]; + tensor value_states_39_cast = reshape(shape = var_927, x = transpose_12)[name = tensor("value_states_39_cast")]; + tensor var_930_perm_0 = const()[name = tensor("op_930_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_55_transpose_x_0 = const()[name = tensor("attn_weights_55_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_55_transpose_y_0 = const()[name = tensor("attn_weights_55_transpose_y_0"), val = tensor(false)]; + tensor transpose_11 = transpose(perm = var_930_perm_0, x = key_states_39_cast)[name = tensor("transpose_11")]; + tensor attn_weights_55_cast = matmul(transpose_x = attn_weights_55_transpose_x_0, transpose_y = attn_weights_55_transpose_y_0, x = query_states_19_cast, y = transpose_11)[name = tensor("attn_weights_55_cast")]; + tensor var_932 = const()[name = tensor("op_932"), val = tensor([1, 12, 77, 77])]; + tensor var_933_cast = reshape(shape = var_932, x = attn_weights_55_cast)[name = tensor("op_933_cast")]; + tensor attn_weights_57_cast = add(x = var_933_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_57_cast")]; + tensor var_938 = const()[name = tensor("op_938"), val = tensor([12, 77, 77])]; + tensor input_149_cast = reshape(shape = var_938, x = attn_weights_57_cast)[name = tensor("input_149_cast")]; + tensor input_151_cast = softmax(axis = var_5, x = input_149_cast)[name = tensor("input_151_cast")]; + tensor attn_output_55_transpose_x_0 = const()[name = tensor("attn_output_55_transpose_x_0"), val = tensor(false)]; + tensor attn_output_55_transpose_y_0 = const()[name = tensor("attn_output_55_transpose_y_0"), val = tensor(false)]; + tensor attn_output_55_cast = matmul(transpose_x = attn_output_55_transpose_x_0, transpose_y = attn_output_55_transpose_y_0, x = input_151_cast, y = value_states_39_cast)[name = tensor("attn_output_55_cast")]; + tensor var_943 = const()[name = tensor("op_943"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_57_cast = reshape(shape = var_943, x = attn_output_55_cast)[name = tensor("attn_output_57_cast")]; + tensor attn_output_59_perm_0 = const()[name = tensor("attn_output_59_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_946 = const()[name = tensor("op_946"), val = tensor([1, 77, 768])]; + tensor transpose_10 = transpose(perm = attn_output_59_perm_0, x = attn_output_57_cast)[name = tensor("transpose_10")]; + tensor input_153_cast = reshape(shape = var_946, x = transpose_10)[name = tensor("input_153_cast")]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125218240))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125660672))), name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125660864)))]; + tensor hidden_states_57_cast = linear(bias = text_encoder_text_model_encoder_layers_9_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_self_attn_out_proj_weight_to_fp16_palettized, x = input_153_cast)[name = tensor("hidden_states_57_cast")]; + tensor input_155_cast = add(x = input_147_cast, y = hidden_states_57_cast)[name = tensor("input_155_cast")]; + tensor input_157_axes_0 = const()[name = tensor("input_157_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_9_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125662464)))]; + tensor text_encoder_text_model_encoder_layers_9_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125664064)))]; + tensor input_157_cast = layer_norm(axes = input_157_axes_0, beta = text_encoder_text_model_encoder_layers_9_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_9_layer_norm2_weight_to_fp16, x = input_155_cast)[name = tensor("input_157_cast")]; + tensor text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125665664))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127435200))), name = tensor("text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([3072, 768])]; + tensor text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127435392))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127437760))), name = tensor("text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor input_159_cast = linear(bias = text_encoder_text_model_encoder_layers_9_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_9_mlp_fc1_weight_to_fp16_palettized, x = input_157_cast)[name = tensor("input_159_cast")]; + tensor var_961_to_fp16 = const()[name = tensor("op_961_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_962_cast = mul(x = input_159_cast, y = var_961_to_fp16)[name = tensor("op_962_cast")]; + tensor var_963_cast = sigmoid(x = var_962_cast)[name = tensor("op_963_cast")]; + tensor input_161_cast = mul(x = input_159_cast, y = var_963_cast)[name = tensor("input_161_cast")]; + tensor text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127437952))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129207488))), name = tensor("text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([768, 3072])]; + tensor text_encoder_text_model_encoder_layers_9_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_9_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129207680)))]; + tensor hidden_states_59_cast = linear(bias = text_encoder_text_model_encoder_layers_9_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_9_mlp_fc2_weight_to_fp16_palettized, x = input_161_cast)[name = tensor("hidden_states_59_cast")]; + tensor input_163_cast = add(x = input_155_cast, y = hidden_states_59_cast)[name = tensor("input_163_cast")]; + tensor hidden_states_61_axes_0 = const()[name = tensor("hidden_states_61_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_10_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129209280)))]; + tensor text_encoder_text_model_encoder_layers_10_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129210880)))]; + tensor hidden_states_61_cast = layer_norm(axes = hidden_states_61_axes_0, beta = text_encoder_text_model_encoder_layers_10_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_10_layer_norm1_weight_to_fp16, x = input_163_cast)[name = tensor("hidden_states_61_cast")]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129212480))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129654912))), name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129655104)))]; + tensor var_987_cast = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_61_cast)[name = tensor("op_987_cast")]; + tensor var_988_to_fp16 = const()[name = tensor("op_988_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_65_cast = mul(x = var_987_cast, y = var_988_to_fp16)[name = tensor("tensor_65_cast")]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129656704))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130099136))), name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130099328)))]; + tensor tensor_61_cast = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_61_cast)[name = tensor("tensor_61_cast")]; + tensor var_993 = const()[name = tensor("op_993"), val = tensor([1, -1, 12, 64])]; + tensor var_994_cast = reshape(shape = var_993, x = tensor_61_cast)[name = tensor("op_994_cast")]; + tensor var_995_perm_0 = const()[name = tensor("op_995_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130100928))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130543360))), name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130543552)))]; + tensor tensor_63_cast = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_61_cast)[name = tensor("tensor_63_cast")]; + tensor var_1000 = const()[name = tensor("op_1000"), val = tensor([1, -1, 12, 64])]; + tensor var_1001_cast = reshape(shape = var_1000, x = tensor_63_cast)[name = tensor("op_1001_cast")]; + tensor var_1002_perm_0 = const()[name = tensor("op_1002_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1009 = const()[name = tensor("op_1009"), val = tensor([1, 77, 12, 64])]; + tensor var_1010_cast = reshape(shape = var_1009, x = tensor_65_cast)[name = tensor("op_1010_cast")]; + tensor var_1011_perm_0 = const()[name = tensor("op_1011_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1013 = const()[name = tensor("op_1013"), val = tensor([12, -1, 64])]; + tensor transpose_9 = transpose(perm = var_1011_perm_0, x = var_1010_cast)[name = tensor("transpose_9")]; + tensor query_states_21_cast = reshape(shape = var_1013, x = transpose_9)[name = tensor("query_states_21_cast")]; + tensor var_1015 = const()[name = tensor("op_1015"), val = tensor([12, -1, 64])]; + tensor transpose_8 = transpose(perm = var_995_perm_0, x = var_994_cast)[name = tensor("transpose_8")]; + tensor key_states_43_cast = reshape(shape = var_1015, x = transpose_8)[name = tensor("key_states_43_cast")]; + tensor var_1017 = const()[name = tensor("op_1017"), val = tensor([12, -1, 64])]; + tensor transpose_7 = transpose(perm = var_1002_perm_0, x = var_1001_cast)[name = tensor("transpose_7")]; + tensor value_states_43_cast = reshape(shape = var_1017, x = transpose_7)[name = tensor("value_states_43_cast")]; + tensor var_1020_perm_0 = const()[name = tensor("op_1020_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_61_transpose_x_0 = const()[name = tensor("attn_weights_61_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_61_transpose_y_0 = const()[name = tensor("attn_weights_61_transpose_y_0"), val = tensor(false)]; + tensor transpose_6 = transpose(perm = var_1020_perm_0, x = key_states_43_cast)[name = tensor("transpose_6")]; + tensor attn_weights_61_cast = matmul(transpose_x = attn_weights_61_transpose_x_0, transpose_y = attn_weights_61_transpose_y_0, x = query_states_21_cast, y = transpose_6)[name = tensor("attn_weights_61_cast")]; + tensor var_1022 = const()[name = tensor("op_1022"), val = tensor([1, 12, 77, 77])]; + tensor var_1023_cast = reshape(shape = var_1022, x = attn_weights_61_cast)[name = tensor("op_1023_cast")]; + tensor attn_weights_63_cast = add(x = var_1023_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_63_cast")]; + tensor var_1028 = const()[name = tensor("op_1028"), val = tensor([12, 77, 77])]; + tensor input_165_cast = reshape(shape = var_1028, x = attn_weights_63_cast)[name = tensor("input_165_cast")]; + tensor input_167_cast = softmax(axis = var_5, x = input_165_cast)[name = tensor("input_167_cast")]; + tensor attn_output_61_transpose_x_0 = const()[name = tensor("attn_output_61_transpose_x_0"), val = tensor(false)]; + tensor attn_output_61_transpose_y_0 = const()[name = tensor("attn_output_61_transpose_y_0"), val = tensor(false)]; + tensor attn_output_61_cast = matmul(transpose_x = attn_output_61_transpose_x_0, transpose_y = attn_output_61_transpose_y_0, x = input_167_cast, y = value_states_43_cast)[name = tensor("attn_output_61_cast")]; + tensor var_1033 = const()[name = tensor("op_1033"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_63_cast = reshape(shape = var_1033, x = attn_output_61_cast)[name = tensor("attn_output_63_cast")]; + tensor attn_output_65_perm_0 = const()[name = tensor("attn_output_65_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1036 = const()[name = tensor("op_1036"), val = tensor([1, 77, 768])]; + tensor transpose_5 = transpose(perm = attn_output_65_perm_0, x = attn_output_63_cast)[name = tensor("transpose_5")]; + tensor input_169_cast = reshape(shape = var_1036, x = transpose_5)[name = tensor("input_169_cast")]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130545152))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130987584))), name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130987776)))]; + tensor hidden_states_63_cast = linear(bias = text_encoder_text_model_encoder_layers_10_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_self_attn_out_proj_weight_to_fp16_palettized, x = input_169_cast)[name = tensor("hidden_states_63_cast")]; + tensor input_171_cast = add(x = input_163_cast, y = hidden_states_63_cast)[name = tensor("input_171_cast")]; + tensor input_173_axes_0 = const()[name = tensor("input_173_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_10_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130989376)))]; + tensor text_encoder_text_model_encoder_layers_10_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130990976)))]; + tensor input_173_cast = layer_norm(axes = input_173_axes_0, beta = text_encoder_text_model_encoder_layers_10_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_10_layer_norm2_weight_to_fp16, x = input_171_cast)[name = tensor("input_173_cast")]; + tensor text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(130992576))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132762112))), name = tensor("text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([3072, 768])]; + tensor text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132762304))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132764672))), name = tensor("text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor input_175_cast = linear(bias = text_encoder_text_model_encoder_layers_10_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_10_mlp_fc1_weight_to_fp16_palettized, x = input_173_cast)[name = tensor("input_175_cast")]; + tensor var_1051_to_fp16 = const()[name = tensor("op_1051_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_1052_cast = mul(x = input_175_cast, y = var_1051_to_fp16)[name = tensor("op_1052_cast")]; + tensor var_1053_cast = sigmoid(x = var_1052_cast)[name = tensor("op_1053_cast")]; + tensor input_177_cast = mul(x = input_175_cast, y = var_1053_cast)[name = tensor("input_177_cast")]; + tensor text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(132764864))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134534400))), name = tensor("text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([768, 3072])]; + tensor text_encoder_text_model_encoder_layers_10_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_10_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134534592)))]; + tensor hidden_states_65_cast = linear(bias = text_encoder_text_model_encoder_layers_10_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_10_mlp_fc2_weight_to_fp16_palettized, x = input_177_cast)[name = tensor("hidden_states_65_cast")]; + tensor input_179_cast = add(x = input_171_cast, y = hidden_states_65_cast)[name = tensor("input_179_cast")]; + tensor input_179_cast_to_fp32_dtype_0 = const()[name = tensor("input_179_cast_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor hidden_states_67_axes_0 = const()[name = tensor("hidden_states_67_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_11_layer_norm1_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_layer_norm1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134536192)))]; + tensor text_encoder_text_model_encoder_layers_11_layer_norm1_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_layer_norm1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134537792)))]; + tensor hidden_states_67_cast = layer_norm(axes = hidden_states_67_axes_0, beta = text_encoder_text_model_encoder_layers_11_layer_norm1_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_11_layer_norm1_weight_to_fp16, x = input_179_cast)[name = tensor("hidden_states_67_cast")]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134539392))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134981824))), name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134982016)))]; + tensor var_1077_cast = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_q_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_q_proj_weight_to_fp16_palettized, x = hidden_states_67_cast)[name = tensor("op_1077_cast")]; + tensor var_1078_to_fp16 = const()[name = tensor("op_1078_to_fp16"), val = tensor(0x1p-3)]; + tensor tensor_cast = mul(x = var_1077_cast, y = var_1078_to_fp16)[name = tensor("tensor_cast")]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(134983616))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(135426048))), name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(135426240)))]; + tensor tensor_67_cast = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_k_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_k_proj_weight_to_fp16_palettized, x = hidden_states_67_cast)[name = tensor("tensor_67_cast")]; + tensor var_1083 = const()[name = tensor("op_1083"), val = tensor([1, -1, 12, 64])]; + tensor var_1084_cast = reshape(shape = var_1083, x = tensor_67_cast)[name = tensor("op_1084_cast")]; + tensor var_1085_perm_0 = const()[name = tensor("op_1085_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(135427840))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(135870272))), name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(135870464)))]; + tensor tensor_69_cast = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_v_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_v_proj_weight_to_fp16_palettized, x = hidden_states_67_cast)[name = tensor("tensor_69_cast")]; + tensor var_1090 = const()[name = tensor("op_1090"), val = tensor([1, -1, 12, 64])]; + tensor var_1091_cast = reshape(shape = var_1090, x = tensor_69_cast)[name = tensor("op_1091_cast")]; + tensor var_1092_perm_0 = const()[name = tensor("op_1092_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1099 = const()[name = tensor("op_1099"), val = tensor([1, 77, 12, 64])]; + tensor var_1100_cast = reshape(shape = var_1099, x = tensor_cast)[name = tensor("op_1100_cast")]; + tensor var_1101_perm_0 = const()[name = tensor("op_1101_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1103 = const()[name = tensor("op_1103"), val = tensor([12, -1, 64])]; + tensor transpose_4 = transpose(perm = var_1101_perm_0, x = var_1100_cast)[name = tensor("transpose_4")]; + tensor query_states_cast = reshape(shape = var_1103, x = transpose_4)[name = tensor("query_states_cast")]; + tensor var_1105 = const()[name = tensor("op_1105"), val = tensor([12, -1, 64])]; + tensor transpose_3 = transpose(perm = var_1085_perm_0, x = var_1084_cast)[name = tensor("transpose_3")]; + tensor key_states_cast = reshape(shape = var_1105, x = transpose_3)[name = tensor("key_states_cast")]; + tensor var_1107 = const()[name = tensor("op_1107"), val = tensor([12, -1, 64])]; + tensor transpose_2 = transpose(perm = var_1092_perm_0, x = var_1091_cast)[name = tensor("transpose_2")]; + tensor value_states_cast = reshape(shape = var_1107, x = transpose_2)[name = tensor("value_states_cast")]; + tensor var_1110_perm_0 = const()[name = tensor("op_1110_perm_0"), val = tensor([0, 2, 1])]; + tensor attn_weights_67_transpose_x_0 = const()[name = tensor("attn_weights_67_transpose_x_0"), val = tensor(false)]; + tensor attn_weights_67_transpose_y_0 = const()[name = tensor("attn_weights_67_transpose_y_0"), val = tensor(false)]; + tensor transpose_1 = transpose(perm = var_1110_perm_0, x = key_states_cast)[name = tensor("transpose_1")]; + tensor attn_weights_67_cast = matmul(transpose_x = attn_weights_67_transpose_x_0, transpose_y = attn_weights_67_transpose_y_0, x = query_states_cast, y = transpose_1)[name = tensor("attn_weights_67_cast")]; + tensor var_1112 = const()[name = tensor("op_1112"), val = tensor([1, 12, 77, 77])]; + tensor var_1113_cast = reshape(shape = var_1112, x = attn_weights_67_cast)[name = tensor("op_1113_cast")]; + tensor attn_weights_69_cast = add(x = var_1113_cast, y = causal_attention_mask_to_fp16_palettized)[name = tensor("attn_weights_69_cast")]; + tensor var_1118 = const()[name = tensor("op_1118"), val = tensor([12, 77, 77])]; + tensor input_181_cast = reshape(shape = var_1118, x = attn_weights_69_cast)[name = tensor("input_181_cast")]; + tensor input_183_cast = softmax(axis = var_5, x = input_181_cast)[name = tensor("input_183_cast")]; + tensor attn_output_67_transpose_x_0 = const()[name = tensor("attn_output_67_transpose_x_0"), val = tensor(false)]; + tensor attn_output_67_transpose_y_0 = const()[name = tensor("attn_output_67_transpose_y_0"), val = tensor(false)]; + tensor attn_output_67_cast = matmul(transpose_x = attn_output_67_transpose_x_0, transpose_y = attn_output_67_transpose_y_0, x = input_183_cast, y = value_states_cast)[name = tensor("attn_output_67_cast")]; + tensor var_1123 = const()[name = tensor("op_1123"), val = tensor([1, 12, 77, 64])]; + tensor attn_output_69_cast = reshape(shape = var_1123, x = attn_output_67_cast)[name = tensor("attn_output_69_cast")]; + tensor attn_output_perm_0 = const()[name = tensor("attn_output_perm_0"), val = tensor([0, 2, 1, 3])]; + tensor var_1126 = const()[name = tensor("op_1126"), val = tensor([1, 77, 768])]; + tensor transpose_0 = transpose(perm = attn_output_perm_0, x = attn_output_69_cast)[name = tensor("transpose_0")]; + tensor input_185_cast = reshape(shape = var_1126, x = transpose_0)[name = tensor("input_185_cast")]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(135872064))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(136314496))), name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([768, 768])]; + tensor text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(136314688)))]; + tensor hidden_states_69_cast = linear(bias = text_encoder_text_model_encoder_layers_11_self_attn_out_proj_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_self_attn_out_proj_weight_to_fp16_palettized, x = input_185_cast)[name = tensor("hidden_states_69_cast")]; + tensor input_187_cast = add(x = input_179_cast, y = hidden_states_69_cast)[name = tensor("input_187_cast")]; + tensor input_189_axes_0 = const()[name = tensor("input_189_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_encoder_layers_11_layer_norm2_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_layer_norm2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(136316288)))]; + tensor text_encoder_text_model_encoder_layers_11_layer_norm2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_layer_norm2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(136317888)))]; + tensor input_189_cast = layer_norm(axes = input_189_axes_0, beta = text_encoder_text_model_encoder_layers_11_layer_norm2_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_encoder_layers_11_layer_norm2_weight_to_fp16, x = input_187_cast)[name = tensor("input_189_cast")]; + tensor text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(136319488))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(138089024))), name = tensor("text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16_palettized"), shape = tensor([3072, 768])]; + tensor text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(138089216))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(138091584))), name = tensor("text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16_palettized"), shape = tensor([3072])]; + tensor input_191_cast = linear(bias = text_encoder_text_model_encoder_layers_11_mlp_fc1_bias_to_fp16_palettized, weight = text_encoder_text_model_encoder_layers_11_mlp_fc1_weight_to_fp16_palettized, x = input_189_cast)[name = tensor("input_191_cast")]; + tensor var_1141_to_fp16 = const()[name = tensor("op_1141_to_fp16"), val = tensor(0x1.b3cp+0)]; + tensor var_1142_cast = mul(x = input_191_cast, y = var_1141_to_fp16)[name = tensor("op_1142_cast")]; + tensor var_1143_cast = sigmoid(x = var_1142_cast)[name = tensor("op_1143_cast")]; + tensor input_193_cast = mul(x = input_191_cast, y = var_1143_cast)[name = tensor("input_193_cast")]; + tensor text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(138091776))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139861312))), name = tensor("text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16_palettized"), shape = tensor([768, 3072])]; + tensor text_encoder_text_model_encoder_layers_11_mlp_fc2_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_encoder_layers_11_mlp_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139861504)))]; + tensor hidden_states_cast = linear(bias = text_encoder_text_model_encoder_layers_11_mlp_fc2_bias_to_fp16, weight = text_encoder_text_model_encoder_layers_11_mlp_fc2_weight_to_fp16_palettized, x = input_193_cast)[name = tensor("hidden_states_cast")]; + tensor input_cast = add(x = input_187_cast, y = hidden_states_cast)[name = tensor("input_cast")]; + tensor last_hidden_state_axes_0 = const()[name = tensor("last_hidden_state_axes_0"), val = tensor([-1])]; + tensor text_encoder_text_model_final_layer_norm_weight_to_fp16 = const()[name = tensor("text_encoder_text_model_final_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139863104)))]; + tensor text_encoder_text_model_final_layer_norm_bias_to_fp16 = const()[name = tensor("text_encoder_text_model_final_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139864704)))]; + tensor last_hidden_state_cast = layer_norm(axes = last_hidden_state_axes_0, beta = text_encoder_text_model_final_layer_norm_bias_to_fp16, epsilon = var_13_to_fp16, gamma = text_encoder_text_model_final_layer_norm_weight_to_fp16, x = input_cast)[name = tensor("last_hidden_state_cast")]; + tensor last_hidden_state_cast_to_fp32_dtype_0 = const()[name = tensor("last_hidden_state_cast_to_fp32_dtype_0"), val = tensor("fp32")]; + tensor last_hidden_state = cast(dtype = input_179_cast_to_fp32_dtype_0, x = input_179_cast)[name = tensor("cast_0")]; + tensor pooled_outputs = cast(dtype = last_hidden_state_cast_to_fp32_dtype_0, x = last_hidden_state_cast)[name = tensor("cast_1")]; + } -> (last_hidden_state, pooled_outputs); +} \ No newline at end of file