README.md

Cross Attention Map

For errors reports or feature requests, please raise an issue :)

Compatible models

UNet with attn2(cross attention module) is compatible

• stable-diffusion-2-1-base
• stable-diffusion-xl-base-1.0
• sdxl-turbo
• ...

Examples

6_kangaroo

10_hoodie

13_sunglasses

Initialize

python -m venv .venv
source .venv/bin/activate
pip install diffusers==0.24.0 accelerate==0.25.0 transformers==4.36.0 einops==0.7.0

Visualize

Visualize Cross Attention Map for Text-to-Image

python t2i.py

How to use

import torch
from diffusers import StableDiffusionXLPipeline
from utils import (
    attn_maps,
    cross_attn_init,
    register_cross_attention_hook,
    set_layer_with_name_and_path,
    preprocess,
    visualize_and_save_attn_map
)

##### 1. Init modules #####
cross_attn_init()
###########################

pipe = StableDiffusionXLPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0",
    torch_dtype=torch.float16,
)

##### 2. Replace modules and Register hook #####
pipe.unet = set_layer_with_name_and_path(pipe.unet)
pipe.unet = register_cross_attention_hook(pipe.unet)
################################################

height = 512
width = 768
prompt = "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'!."
pipe = pipe.to("cuda:0")
image = pipe(
    prompt,
    height=height,
    width=width,
).images[0]
image.save('test.png')

##### 3. Process and Save attention map #####
attn_map = preprocess(max_height=height, max_width=width)
visualize_and_save_attn_map(attn_map, pipe.tokenizer, prompt)
#############################################

TODO

1. Add options for how to combine attention maps for each layers and timsteps
2. Applications(prompt-to-prompt, ...)