Update app.py

app.py

@@ -117,9 +117,9 @@ def init_pipe():
             controlnet_transformer,
     )
 
-    # pipe.vae.enable_slicing()
-    # pipe.vae.enable_tiling()
-    # pipe.enable_model_cpu_offload()
+    pipe.vae.enable_slicing()
+    pipe.vae.enable_tiling()
+    pipe.enable_model_cpu_offload()
 
     return pipe
     
@@ -131,10 +131,9 @@ def inference(source_images,
         h, w, random_seed)->List[PIL.Image.Image]:
     torch.manual_seed(random_seed)
 
-    pipe.to(DEVICE)
-    # pipe.vae.to(DEVICE)
-    # pipe.transformer.to(DEVICE)
-    # pipe.controlnet_transformer.to(DEVICE)
+    pipe.vae.to(DEVICE)
+    pipe.transformer.to(DEVICE)
+    pipe.controlnet_transformer.to(DEVICE)
 
     source_pixel_values = source_images/127.5 - 1.0
     source_pixel_values = source_pixel_values.to(torch.float16).to(DEVICE)
@@ -172,13 +171,13 @@ def inference(source_images,
         height = h,
         width = w,
         num_frames = f,
-        num_inference_steps = 30,
+        num_inference_steps = 20,
         interval = 6,
         guidance_scale = guidance_scale,
         generator = torch.Generator(device=DEVICE).manual_seed(random_seed)
     ).frames[0]
     b=time.perf_counter()
-    print(f"Denoise 30 steps in {b-a}s")
+    print(f"Denoise 20 steps in {b-a}s")
 
     return video