Upload pipeline.py

pipeline.py

@@ -1017,10 +1017,6 @@ class StableDiffusionControlNetPipeline(
     def apply_effective_region_mask(
         self, effective_region_mask: torch.Tensor, out: torch.Tensor
     ) -> torch.Tensor:
-        print("downblock dtype")
-        print(out.dtype)
-        print("mask dtype")
-        print(effective_region_mask.dtype)
         if effective_region_mask is None:
             return out
 
@@ -1384,13 +1380,6 @@ class StableDiffusionControlNetPipeline(
                 effective_region_mask, height=height, width=width
             ).to(dtype=torch.float16)
 
-            print("mask shape:")
-            print(effective_region_mask.shape)
-            print()
-
-            print(torch.min(effective_region_mask))
-            print(torch.max(effective_region_mask))
-
         # 5. Prepare timesteps
         timesteps, num_inference_steps = retrieve_timesteps(
             self.scheduler, num_inference_steps, device, timesteps, sigmas