Update app.py

app.py

@@ -31,7 +31,7 @@ torch.backends.cuda.matmul.allow_bf16_reduced_precision_reduction = False
 torch.backends.cuda.matmul.allow_fp16_reduced_precision_reduction = False
 torch.backends.cudnn.allow_tf32 = False
 torch.backends.cudnn.deterministic = False
-#torch.backends.cudnn.benchmark = False
+torch.backends.cudnn.benchmark = False
 torch.backends.cuda.preferred_blas_library="cublas"
 # torch.backends.cuda.preferred_linalg_library="cusolver"
 torch.set_float32_matmul_precision("highest")
@@ -243,9 +243,9 @@ def generate_30(
     denoise: float = 0.3,
     progress=gr.Progress(track_tqdm=True)  # Add progress as a keyword argument
 ):
-    torch.backends.cudnn.benchmark = False
-    torch.cuda.empty_cache()
-    gc.collect()
+    #torch.backends.cudnn.benchmark = False
+    #torch.cuda.empty_cache()
+    #gc.collect()
     global models
     pipe = models[model_choice]
     #if juggernaut == True:
@@ -302,9 +302,9 @@ def generate_60(
     denoise: float = 0.3,
     progress=gr.Progress(track_tqdm=True)  # Add progress as a keyword argument
 ):
-    torch.backends.cudnn.benchmark = True
-    torch.cuda.empty_cache()
-    gc.collect()
+    #torch.backends.cudnn.benchmark = True
+    #torch.cuda.empty_cache()
+    #gc.collect()
     global models
     pipe = models[model_choice]
     #if juggernaut == True:
@@ -361,9 +361,9 @@ def generate_90(
     denoise: float = 0.3,
     progress=gr.Progress(track_tqdm=True)  # Add progress as a keyword argument
 ):
-    torch.backends.cudnn.benchmark = True
-    torch.cuda.empty_cache()
-    gc.collect()
+    #torch.backends.cudnn.benchmark = True
+    #torch.cuda.empty_cache()
+    #gc.collect()
     global models
     pipe = models[model_choice]
     #if juggernaut == True: