Update app.py

app.py

@@ -12,7 +12,7 @@ from previewer.modules import Previewer
 
 from gallery_history import fetch_gallery_history, show_gallery_history
 
-os.environ["TOKENIZERS_PARALLELISM"] = "false"
+os.environ["TOKENIZERS_PARALLELISM"] = 'false'
 
 DESCRIPTION = "# Würstchen"
 DESCRIPTION += "\n<p style=\"text-align: center\"><a href='https://huggingface.co/warp-ai/wuerstchen' target='_blank'>Würstchen</a> is a new fast and efficient high resolution text-to-image architecture and model</p>"
@@ -29,12 +29,8 @@ PREVIEW_IMAGES = True
 dtype = torch.float16
 device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 if torch.cuda.is_available():
-    prior_pipeline = WuerstchenPriorPipeline.from_pretrained(
-        "warp-ai/wuerstchen-prior", torch_dtype=dtype
-    )
-    decoder_pipeline = WuerstchenDecoderPipeline.from_pretrained(
-        "warp-ai/wuerstchen", torch_dtype=dtype
-    )
+    prior_pipeline = WuerstchenPriorPipeline.from_pretrained("warp-ai/wuerstchen-prior", torch_dtype=dtype)
+    decoder_pipeline = WuerstchenDecoderPipeline.from_pretrained("warp-ai/wuerstchen", torch_dtype=dtype)
     if ENABLE_CPU_OFFLOAD:
         prior_pipeline.enable_model_cpu_offload()
         decoder_pipeline.enable_model_cpu_offload()
@@ -43,12 +39,8 @@ if torch.cuda.is_available():
         decoder_pipeline.to(device)
 
     if USE_TORCH_COMPILE:
-        prior_pipeline.prior = torch.compile(
-            prior_pipeline.prior, mode="reduce-overhead", fullgraph=True
-        )
-        decoder_pipeline.decoder = torch.compile(
-            decoder_pipeline.decoder, mode="reduce-overhead", fullgraph=True
-        )
+        prior_pipeline.prior = torch.compile(prior_pipeline.prior, mode="reduce-overhead", fullgraph=True)
+        decoder_pipeline.decoder = torch.compile(decoder_pipeline.decoder, mode="reduce-overhead", fullgraph=True)
 
     if PREVIEW_IMAGES:
         previewer = Previewer()
@@ -228,18 +220,18 @@ with gr.Blocks(css="style.css") as demo:
     history = show_gallery_history()
 
     inputs = [
-        prompt,
-        negative_prompt,
-        seed,
-        width,
-        height,
-        prior_num_inference_steps,
-        # prior_timesteps,
-        prior_guidance_scale,
-        decoder_num_inference_steps,
-        # decoder_timesteps,
-        decoder_guidance_scale,
-        num_images_per_prompt,
+            prompt,
+            negative_prompt,
+            seed,
+            width,
+            height,
+            prior_num_inference_steps,
+            # prior_timesteps,
+            prior_guidance_scale,
+            decoder_num_inference_steps,
+            # decoder_timesteps,
+            decoder_guidance_scale,
+            num_images_per_prompt,
     ]
     prompt.submit(
         fn=randomize_seed_fn,