Update app.py

app.py

@@ -16,8 +16,18 @@ dtype = torch.bfloat16
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
 taef1 = AutoencoderTiny.from_pretrained("madebyollin/taef1", torch_dtype=dtype).to(device)
-good_vae = AutoencoderKL.from_pretrained("black-forest-labs/FLUX.1-dev", subfolder="vae", torch_dtype=dtype, token=hf_token).to(device)
-pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=dtype, vae=taef1, token=hf_token).to(device)
+good_vae = AutoencoderKL.from_pretrained(
+    "black-forest-labs/FLUX.1-dev",
+    subfolder="vae",
+    torch_dtype=dtype,
+    token=hf_token
+).to(device)
+pipe = DiffusionPipeline.from_pretrained(
+    "black-forest-labs/FLUX.1-dev",
+    torch_dtype=dtype,
+    vae=taef1,
+    token=hf_token
+).to(device)
 torch.cuda.empty_cache()
 
 MAX_SEED = np.iinfo(np.int32).max
@@ -26,7 +36,16 @@ MAX_IMAGE_SIZE = 2048
 pipe.flux_pipe_call_that_returns_an_iterable_of_images = flux_pipe_call_that_returns_an_iterable_of_images.__get__(pipe)
 
 @spaces.GPU(duration=75)
-def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, guidance_scale=3.5, num_inference_steps=28, progress=gr.Progress(track_tqdm=True)):
+def infer(
+    prompt,
+    seed=42,
+    randomize_seed=False,
+    width=1024,
+    height=1024,
+    guidance_scale=3.5,
+    num_inference_steps=28,
+    progress=gr.Progress(track_tqdm=True)
+):
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
     generator = torch.Generator().manual_seed(seed)
@@ -98,15 +117,8 @@ body {
 }
 """
 
-# Define the dark theme correctly using the 'base' parameter
-dark_theme = gr.themes.Default(
-    primary_hue="blue",
-    neutral_hue="gray",
-    spacing_size="md",
-    font="default",
-    # Use 'base' instead of 'mode' to set the theme to dark
-    base="dark"
-)
+# Define the dark theme using gr.themes.Dark()
+dark_theme = gr.themes.Dark()
 
 with gr.Blocks(theme=dark_theme, css=css) as demo: