Update app.py

app.py

@@ -233,36 +233,36 @@ def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
         seed = random.randint(0, MAX_SEED)
     return seed
 
-    @spaces.GPU(duration=60)
-    def generate(p, progress=gr.Progress(track_tqdm=True)):
-        negative_prompt = cfg.get("negative_prompt", "")
-        style_selection = ""
-        use_negative_prompt = True
-        seed = 0
-        width = cfg.get("width", 1024)
-        height = cfg.get("width", 768) 
-        inference_steps = cfg.get("inference_steps", 30)
-        randomize_seed = True
-        guidance_scale = cfg.get("guidance_scale", 7.5)
-        prompt_str = cfg.get("prompt", "{prompt}").replace("{prompt}", p)
-        seed = int(randomize_seed_fn(seed, randomize_seed))
-        generator = torch.Generator(pipe.device).manual_seed(seed)
-            
-        images = pipe(
-            prompt=prompt_str,
-            negative_prompt=negative_prompt,
-            width=width,
-            height=height,
-            guidance_scale=guidance_scale,
-            num_inference_steps=inference_steps,
-            generator=generator,
-            num_images_per_prompt=NUM_IMAGES_PER_PROMPT,
-            output_type="pil",
-        ).images
-        images = [save_image(img) for img in images]
-        image_paths = [i[1] for i in images]
-        print(prompt_str, image_paths)
-        return [i[0] for i in images]
+@spaces.GPU(duration=60)
+def generate(p, progress=gr.Progress(track_tqdm=True)):
+    negative_prompt = cfg.get("negative_prompt", "")
+    style_selection = ""
+    use_negative_prompt = True
+    seed = 0
+    width = cfg.get("width", 1024)
+    height = cfg.get("width", 768) 
+    inference_steps = cfg.get("inference_steps", 30)
+    randomize_seed = True
+    guidance_scale = cfg.get("guidance_scale", 7.5)
+    prompt_str = cfg.get("prompt", "{prompt}").replace("{prompt}", p)
+    seed = int(randomize_seed_fn(seed, randomize_seed))
+    generator = torch.Generator(pipe.device).manual_seed(seed)
+        
+    images = pipe(
+        prompt=prompt_str,
+        negative_prompt=negative_prompt,
+        width=width,
+        height=height,
+        guidance_scale=guidance_scale,
+        num_inference_steps=inference_steps,
+        generator=generator,
+        num_images_per_prompt=NUM_IMAGES_PER_PROMPT,
+        output_type="pil",
+    ).images
+    images = [save_image(img) for img in images]
+    image_paths = [i[1] for i in images]
+    print(prompt_str, image_paths)
+    return [i[0] for i in images]
 
 with gr.Blocks(css=css,head=js,fill_height=True) as demo:
     with gr.Row(equal_height=False):