Update app.py

app.py

@@ -28,15 +28,15 @@ def genie (Model, Prompt, negative_prompt, height, width, scale, steps, seed, re
             torch.cuda.empty_cache()
         
             if upscale == "Yes":
-            upscaler = DiffusionPipeline.from_pretrained("stabilityai/sd-x2-latent-upscaler", torch_dtype=torch.float16, use_safetensors=True)
-            upscaler.enable_xformers_memory_efficient_attention()
-            upscaler = upscaler.to(device)
-            torch.cuda.empty_cache()
-            upscaled = upscaler(prompt=prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=15, guidance_scale=0).images[0]
-            torch.cuda.empty_cache()
-            return upscaled
-        else:
-            return image
+                upscaler = DiffusionPipeline.from_pretrained("stabilityai/sd-x2-latent-upscaler", torch_dtype=torch.float16, use_safetensors=True)
+                upscaler.enable_xformers_memory_efficient_attention()
+                upscaler = upscaler.to(device)
+                torch.cuda.empty_cache()
+                upscaled = upscaler(prompt=prompt, negative_prompt=negative_prompt, image=image, num_inference_steps=15, guidance_scale=0).images[0]
+                torch.cuda.empty_cache()
+                return upscaled
+            else:
+                return image
     else:
         image = pipe(Prompt, negative_prompt=negative_prompt, height=height, width=width, num_inference_steps=steps, guidance_scale=scale).images[0]
         torch.cuda.empty_cache()