pip install diffusers torch

import os
import torch

from accelerate.utils import set_seed

from diffusers import StableDiffusionPipeline
from diffusers.utils import load_image, make_image_grid
from diffusers.utils.torch_utils import randn_tensor

pipe = StableDiffusionPipeline.from_pretrained(
    "stable-diffusion-v1-5/stable-diffusion-v1-5",
    custom_pipeline="hyoungwoncho/sd_perturbed_attention_guidance",
    torch_dtype=torch.float16
)

device = "cuda"
pipe = pipe.to(device)

pag_scale = 5.0
pag_applied_layers_index = ['m0']

batch_size = 4
seed = 10

base_dir = "./results/"
grid_dir = base_dir + "/pag" + str(pag_scale) + "/"

if not os.path.exists(grid_dir):
    os.makedirs(grid_dir)

set_seed(seed)

latent_input = randn_tensor(shape=(batch_size,4,64,64), generator=None, device=device, dtype=torch.float16)

output_baseline = pipe(
    "",
    width=512,
    height=512,
    num_inference_steps=50,
    guidance_scale=0.0,
    pag_scale=0.0,
    pag_applied_layers_index=pag_applied_layers_index,
    num_images_per_prompt=batch_size,
    latents=latent_input
).images

output_pag = pipe(
    "",
    width=512,
    height=512,
    num_inference_steps=50,
    guidance_scale=0.0,
    pag_scale=5.0,
    pag_applied_layers_index=pag_applied_layers_index,
    num_images_per_prompt=batch_size,
    latents=latent_input
).images

grid_image = make_image_grid(output_baseline + output_pag, rows=2, cols=batch_size)
grid_image.save(grid_dir + "sample.png")