Update app.py

app.py

@@ -2,28 +2,28 @@
 
 from __future__ import annotations
 
+import os
+import random
+
 import gradio as gr
 import numpy as np
+import PIL.Image
 import spaces
-import random
-from diffusers import AutoencoderKL, DiffusionPipeline
 import torch
+from diffusers import AutoencoderKL, DiffusionPipeline
 
-import os
-import PIL.Image 
-
-MARKDOWN = """
-The demo is based on <a href="https://huggingface.co/dataautogpt3/OpenDalleV1.1">OpenDalle V1.1</a> by @dataautogpt3
-The demo is based on the fusion of different models to provide better performance, comparatively. 
-
-You can try out the prompts and check for yourself. 
-
-**Parts of codes are adopted from [@hysts's SD-XL demo](https://huggingface.co/spaces/hysts/SD-XL) running on A10G GPU **
-
-You can check out more of my spaces. Demo by [Sunder Ali Khowaja](https://sander-ali.github.io) - [Github](https://github.com/sander-ali)
+DESCRIPTION = """
+# OpenDalle 1.1
+**Demo by [mrfakename](https://mrfake.name/) - [Twitter](https://twitter.com/realmrfakename) - [GitHub](https://github.com/fakerybakery/) - [Hugging Face](https://huggingface.co/mrfakename)**
+This is a demo of <a href="https://huggingface.co/dataautogpt3/OpenDalleV1.1">OpenDalle V1.1</a> by @dataautogpt3.
+It's a merge of several different models and is supposed to provide excellent performance. Try it out!
+[Not Working?](https://huggingface.co/spaces/mrfakename/OpenDalleV1.1-GPU-Demo/discussions/4)
+**The code for this demo is based on [@hysts's SD-XL demo](https://huggingface.co/spaces/hysts/SD-XL) running on a A10G GPU.**
+**NOTE: The model is licensed under a non-commercial license**
+Also see [OpenDalle Original Demo](https://huggingface.co/spaces/mrfakename/OpenDalle-GPU-Demo/)
 """
 if not torch.cuda.is_available():
-    MARKDOWN += "\n<h1>Running on CPU 🥶 This demo does not work on CPU. </h1>"
+    DESCRIPTION += "\n<h1>Running on CPU 🥶 This demo does not work on CPU. Please use <a href=\"https://huggingface.co/spaces/mrfakename/OpenDalleV1.1-GPU-Demo\">the online demo</a> instead</h1>"
 
 MAX_SEED = np.iinfo(np.int32).max
 CACHE_EXAMPLES = torch.cuda.is_available() and os.getenv("CACHE_EXAMPLES", "0") == "1"
@@ -32,14 +32,25 @@ USE_TORCH_COMPILE = os.getenv("USE_TORCH_COMPILE") == "1"
 ENABLE_CPU_OFFLOAD = os.getenv("ENABLE_CPU_OFFLOAD") == "1"
 ENABLE_REFINER = os.getenv("ENABLE_REFINER", "0") == "1"
 
-
 device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 if torch.cuda.is_available():
     vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
-    pipe = DiffusionPipeline.from_pretrained("dataautogpt3/OpenDalleV1.1", vae=vae, torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
-    pipe.enable_xformers_memory_efficient_attention()
+    pipe = DiffusionPipeline.from_pretrained(
+        "dataautogpt3/OpenDalleV1.1",
+        vae=vae,
+        torch_dtype=torch.float16,
+        use_safetensors=True,
+        variant="fp16",
+    )
     if ENABLE_REFINER:
-        refiner = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-1.0", vae=vae, torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
+        refiner = DiffusionPipeline.from_pretrained(
+            "stabilityai/stable-diffusion-xl-refiner-1.0",
+            vae=vae,
+            torch_dtype=torch.float16,
+            use_safetensors=True,
+            variant="fp16",
+        )
+
     if ENABLE_CPU_OFFLOAD:
         pipe.enable_model_cpu_offload()
         if ENABLE_REFINER:
@@ -48,19 +59,28 @@ if torch.cuda.is_available():
         pipe.to(device)
         if ENABLE_REFINER:
             refiner.to(device)
+
     if USE_TORCH_COMPILE:
-        pipe.unet = torch.compile(pipe.unet, mode='reduce-overhead', fullgraph=True)
+        pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
         if ENABLE_REFINER:
-            refiner.unet = torch.compile(refiner.unet, mode="reduce_overhead", fullgraph=True)
+            refiner.unet = torch.compile(refiner.unet, mode="reduce-overhead", fullgraph=True)
+
 
 def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
     return seed
 
-@spaces.GPU(enable_queue=True)
-def infer(
+
+@spaces.GPU
+def generate(
     prompt: str,
+    negative_prompt: str = "",
+    prompt_2: str = "",
+    negative_prompt_2: str = "",
+    use_negative_prompt: bool = False,
+    use_prompt_2: bool = False,
+    use_negative_prompt_2: bool = False,
     seed: int = 0,
     width: int = 1024,
     height: int = 1024,
@@ -69,12 +89,6 @@ def infer(
     num_inference_steps_base: int = 25,
     num_inference_steps_refiner: int = 25,
     apply_refiner: bool = False,
-    negative_prompt: str = "",
-    prompt_2: str = "",
-    negative_prompt_2: str = "",
-    use_negative_prompt: bool = False,
-    use_prompt_2: bool = False,
-    use_negative_prompt_2: bool = False,
     progress=gr.Progress(track_tqdm=True),
 ) -> PIL.Image.Image:
     print(f"** Generating image for: \"{prompt}\" **")
@@ -125,85 +139,22 @@ def infer(
         ).images[0]
         return image
 
+
 examples = [
-    "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
+    "A realistic photograph of an astronaut in a jungle, cold color palette, detailed, 8k",
     "An astronaut riding a green horse",
-    "A delicious ceviche cheesecake slice",
 ]
 
-css="""
-#col-container {
-    margin: 0 auto;
-    max-width: 520px;
-}
-"""
-
-# if torch.cuda.is_available():
-#     power_device = "GPU"
-# else:
-#     power_device = "CPU"
-theme = gr.themes.Glass(
-    primary_hue="blue",
-    secondary_hue="blue",
-    neutral_hue="gray",
-    text_size="md",
-    spacing_size="md",
-    radius_size="md",
-    font=[gr.themes.GoogleFont('Source Sans Pro'), 'ui-sans-serif', 'system-ui', 'sans-serif'],
-).set(
-    body_background_fill_dark='*background_fill_primary',
-    background_fill_primary_dark='*neutral_950',
-    background_fill_secondary='*neutral_50',
-    background_fill_secondary_dark='*neutral_900',
-    border_color_primary_dark='*neutral_700',
-    block_background_fill='*background_fill_primary',
-    block_background_fill_dark='*neutral_800',
-    block_border_width='1px',
-    block_label_background_fill='*background_fill_primary',
-    block_label_background_fill_dark='*background_fill_secondary',
-    block_label_text_color='*neutral_500',
-    block_label_text_size='*text_sm',
-    block_label_text_weight='400',
-    block_shadow='none',
-    block_shadow_dark='none',
-    block_title_text_color='*neutral_500',
-    block_title_text_weight='400',
-    panel_border_width='0',
-    panel_border_width_dark='0',
-    checkbox_background_color_dark='*neutral_800',
-    checkbox_border_width='*input_border_width',
-    checkbox_label_border_width='*input_border_width',
-    input_background_fill='*neutral_100',
-    input_background_fill_dark='*neutral_700',
-    input_border_color_focus_dark='*neutral_700',
-    input_border_width='0px',
-    input_border_width_dark='0px',
-    slider_color='#2563eb',
-    slider_color_dark='#2563eb',
-    table_even_background_fill_dark='*neutral_950',
-    table_odd_background_fill_dark='*neutral_900',
-    button_border_width='*input_border_width',
-    button_shadow_active='none',
-    button_primary_background_fill='*primary_200',
-    button_primary_background_fill_dark='*primary_700',
-    button_primary_background_fill_hover='*button_primary_background_fill',
-    button_primary_background_fill_hover_dark='*button_primary_background_fill',
-    button_secondary_background_fill='*neutral_200',
-    button_secondary_background_fill_dark='*neutral_600',
-    button_secondary_background_fill_hover='*button_secondary_background_fill',
-    button_secondary_background_fill_hover_dark='*button_secondary_background_fill',
-    button_cancel_background_fill='*button_secondary_background_fill',
-    button_cancel_background_fill_dark='*button_secondary_background_fill',
-    button_cancel_background_fill_hover='*button_cancel_background_fill',
-    button_cancel_background_fill_hover_dark='*button_cancel_background_fill'
+theme = gr.themes.Base(
+    font=[gr.themes.GoogleFont('Libre Franklin'), gr.themes.GoogleFont('Public Sans'), 'system-ui', 'sans-serif'],
 )
-
-
 with gr.Blocks(css="footer{display:none !important}", theme=theme) as demo:
-    
-    gr.Markdown(MARKDOWN)
-    gr.DuplicateButton()
-        
+    gr.Markdown(DESCRIPTION)
+    gr.DuplicateButton(
+        value="Duplicate Space for private use",
+        elem_id="duplicate-button",
+        visible=os.getenv("SHOW_DUPLICATE_BUTTON") == "1",
+    )
     with gr.Group():
         prompt = gr.Text(
             label="Prompt",
@@ -297,7 +248,7 @@ with gr.Blocks(css="footer{display:none !important}", theme=theme) as demo:
         examples=examples,
         inputs=prompt,
         outputs=result,
-        fn=infer,
+        fn=generate,
         cache_examples=CACHE_EXAMPLES,
     )
 
@@ -344,7 +295,7 @@ with gr.Blocks(css="footer{display:none !important}", theme=theme) as demo:
         queue=False,
         api_name=False,
     ).then(
-        fn=infer,
+        fn=generate,
         inputs=[
             prompt,
             negative_prompt,
@@ -365,5 +316,6 @@ with gr.Blocks(css="footer{display:none !important}", theme=theme) as demo:
         outputs=result,
         api_name="run",
     )
+
 if __name__ == "__main__":
-    demo.queue(max_size=20, api_open=False).launch(show_api=False, share=True)
+    demo.queue(max_size=20, api_open=False).launch(show_api=False)