app.py

import torch
import gradio as gr
from diffusers import StableDiffusionXLPipeline
from utils import (
    cross_attn_init,
    register_cross_attention_hook,
    attn_maps,
    get_net_attn_map,
    resize_net_attn_map,
    return_net_attn_map,
)
# from transformers.utils.hub import move_cache

# move_cache()

cross_attn_init()
pipe = StableDiffusionXLPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0",
    # "stabilityai/sdxl-turbo",
    torch_dtype=torch.float16,
)
pipe.unet = register_cross_attention_hook(pipe.unet)
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
pipe = pipe.to(device)


def inference(prompt):
    image = pipe(
        prompt,
        num_inference_steps=15,
    ).images[0]
    net_attn_maps = get_net_attn_map(image.size)
    net_attn_maps = resize_net_attn_map(net_attn_maps, image.size)
    net_attn_maps = return_net_attn_map(net_attn_maps, pipe.tokenizer, prompt)

    # remove sos and eos
    net_attn_maps = [attn_map for attn_map in net_attn_maps if attn_map[1].split('_')[-1] != "<<|startoftext|>>"]
    net_attn_maps = [attn_map for attn_map in net_attn_maps if attn_map[1].split('_')[-1] != "<<|endoftext|>>"]
    
    return image, net_attn_maps


with gr.Blocks() as demo:
    gr.Markdown(
        """
        # 🚀 Text-to-Image Cross Attention Map for 🧨 Diffusers ⚡
        """
    )
    # prompt = gr.Textbox(value="A photo of a black puppy, christmas atmosphere", label="Prompt", lines=2)
    prompt = gr.Textbox(value="A portrait photo of a kangaroo wearing an orange hoodie and blue sunglasses standing on the grass in front of the Sydney Opera House holding a sign on the chest that says 'SDXL'!.", label="Prompt", lines=2)
    btn = gr.Button("Generate images", scale=0)
    
    with gr.Row():
        image = gr.Image(height=512,width=512,type="pil")
        gallery = gr.Gallery(
            value=None, label="Generated images", show_label=False,
            elem_id="gallery", object_fit="contain", height="auto"
        )
    
    btn.click(inference, prompt, [image, gallery])


if __name__ == "__main__":
    demo.launch(share=True)