Update app.py

app.py

@@ -112,15 +112,17 @@ sdulers =[
     "VQDiffusionScheduler",
 ]
 
+generator = torch.Generator(device="cpu").manual_seed(random.randint(0, MAX_SEED))
+
 def plex(mput, prompt, neg_prompt, stips, modal_id, dula, blip, blop):
     modal_id = ""+modal_id+""
     dula=""+dula+"" ## shedulers todo
     pope = accelerator.prepare(StableDiffusionPipeline.from_pretrained(modal_id, use_safetensors=False, safety_checker=None,torch_dtype=torch.float32))
+    pope.unet.to(memory_format=torch.channels_last)
     pope = accelerator.prepare(pope.to("cpu"))
     pipe = accelerator.prepare(StableDiffusionControlNetPipeline.from_pretrained(modal_id, use_safetensors=False,controlnet=controlnet, safety_checker=None,torch_dtype=torch.float32))
     pipe = accelerator.prepare(pipe.to("cpu"))
     pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
-    generator = torch.Generator("cpu").manual_seed(random.randint(0, MAX_SEED))
     
     tilage = pope(prompt,num_inference_steps=5,height=512,width=512,generator=generator).images[0]
     cannyimage = np.array(tilage)