Update app.py

app.py

@@ -117,27 +117,10 @@ pipe.to(device=DEVICE)
 pipe.unet = torch.compile(pipe.unet)
 pipe.vae = torch.compile(pipe.vae)
 
-
-im_embs = torch.zeros(1, 1, 1, 1280, device=DEVICE, dtype=dtype)
-output = pipe(prompt='a person', guidance_scale=0, added_cond_kwargs={}, ip_adapter_image_embeds=[im_embs], num_inference_steps=STEPS)
-leave_im_emb, _ = pipe.encode_image(
-                output.frames[0][len(output.frames[0])//2], DEVICE, 1, output_hidden_state
-)
-assert len(output.frames[0]) == 16
-
-im_embs = torch.zeros(1, 1, 1, 1280, device=DEVICE, dtype=dtype)
-output = pipe(prompt='a person', guidance_scale=0, added_cond_kwargs={}, ip_adapter_image_embeds=[im_embs], num_inference_steps=STEPS)
-leave_im_emb, _ = pipe.encode_image(
-                output.frames[0][len(output.frames[0])//2], DEVICE, 1, output_hidden_state
-)
-
-#leave_im_emb.detach().to('cpu')
-
 @spaces.GPU(duration=20)
 def generate_gpu(in_im_embs):
     print('start gen')
     in_im_embs = in_im_embs.to('cuda').unsqueeze(0).unsqueeze(0)
-    #im_embs = torch.cat((torch.zeros(1, 1280, device=DEVICE, dtype=dtype), in_im_embs), 0)
 
     output = pipe(prompt='a scene', guidance_scale=0, added_cond_kwargs={}, ip_adapter_image_embeds=[in_im_embs], num_inference_steps=STEPS)
     print('image is made')
@@ -148,6 +131,10 @@ def generate_gpu(in_im_embs):
     im_emb = im_emb.detach().to('cpu').to(torch.float32)
     return output, im_emb
 
+im_embs = torch.zeros(1, 1, 1, 1280, device=DEVICE, dtype=dtype)
+generate_gpu(im_embs)
+generate_gpu(im_embs)
+
 def generate(in_im_embs):
     
     output, im_emb = generate_gpu(in_im_embs)