Update app.py

app.py

@@ -42,6 +42,7 @@ upscaler = StableDiffusionLatentUpscalePipeline.from_pretrained("alfredplpl/x2-l
 if torch.cuda.is_available():
   pipe = pipe.to("cuda")
   pipe_i2i = pipe_i2i.to("cuda")
+  upscaler=upscaler.to("cuda")
 
 def error_str(error, title="Error"):
     return f"""#### {title}
@@ -157,8 +158,6 @@ def txt_to_img(prompt, neg_prompt, guidance, steps, width, height, generator,sup
         height = height,
         output_type="latent",
         generator = generator).images
-      pipe=pipe.to("cpu")
-      upscaler=upscaler.to("cuda")
       result = upscaler(
         prompt=prompt,
         negative_prompt = neg_prompt,
@@ -167,8 +166,6 @@ def txt_to_img(prompt, neg_prompt, guidance, steps, width, height, generator,sup
         guidance_scale=0,
         generator=generator,
       )
-      pipe=pipe.to("cuda")
-      upscaler=upscaler.to("cpu")
     else:  
       result = pipe(
         prompt,
@@ -197,8 +194,6 @@ def img_to_img(prompt, neg_prompt, img, strength, guidance, steps, width, height
         #height = height,
         output_type="latent",
         generator = generator).images
-      pipe=pipe.to("cpu")
-      upscaler=upscaler.to("cuda")
       result = upscaler(
         prompt=prompt,
         negative_prompt = neg_prompt,
@@ -207,8 +202,6 @@ def img_to_img(prompt, neg_prompt, img, strength, guidance, steps, width, height
         guidance_scale=0,
         generator=generator,
       )
-      pipe=pipe.to("cuda")
-      upscaler=upscaler.to("cpu")
     else:  
       result = pipe_i2i(
         prompt,