Update app.py

app.py

@@ -33,7 +33,7 @@ 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"
 
@@ -192,8 +192,8 @@ def generate_60(
         options["use_resolution_binning"] = True
     images = []
     pipe.scheduler.set_timesteps(num_inference_steps,device)
-    with torch.no_grad():
-      for i in range(0, num_images, BATCH_SIZE):
+    #with torch.no_grad():
+    for i in range(0, num_images, BATCH_SIZE):
         batch_options = options.copy()
         batch_options["prompt"] = options["prompt"][i:i+BATCH_SIZE]
         if "negative_prompt" in batch_options:
@@ -243,8 +243,8 @@ def generate_90(
         options["use_resolution_binning"] = True
     images = []
     pipe.scheduler.set_timesteps(num_inference_steps,device)
-    with torch.no_grad():
-      for i in range(0, num_images, BATCH_SIZE):
+    #with torch.no_grad():
+    for i in range(0, num_images, BATCH_SIZE):
         batch_options = options.copy()
         batch_options["prompt"] = options["prompt"][i:i+BATCH_SIZE]
         if "negative_prompt" in batch_options: