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#!/usr/bin/env python3
from diffusers import DiffusionPipeline, EulerDiscreteScheduler, StableDiffusionPipeline, KDPM2DiscreteScheduler, StableDiffusionImg2ImgPipeline, HeunDiscreteScheduler, KDPM2AncestralDiscreteScheduler, DDIMScheduler
from diffusers import StableDiffusionXLPipeline, StableDiffusionXLImg2ImgPipeline, AutoencoderKL
import time
from pytorch_lightning import seed_everything
import os
from huggingface_hub import HfApi
# from compel import Compel
import torch
import sys
from pathlib import Path
import requests
from PIL import Image
from io import BytesIO
import xformers
api = HfApi()
start_time = time.time()
# use_refiner = bool(int(sys.argv[1]))
use_refiner = False
use_diffusers = True
path = "stabilityai/stable-diffusion-xl-base-1.0"
refiner_path = "stabilityai/stable-diffusion-xl-refiner-1.0"
vae_path = "madebyollin/sdxl-vae-fp16-fix"
vae = AutoencoderKL.from_pretrained(vae_path, torch_dtype=torch.float16)
if use_diffusers:
# pipe = StableDiffusionXLPipeline.from_pretrained(path, vae=vae, torch_dtype=torch.float16, variant="fp16", use_safetensors=True, local_files_only=True)
pipe = StableDiffusionXLPipeline.from_pretrained(path, torch_dtype=torch.float16, vae=vae, variant="fp16", use_safetensors=True, local_files_only=True, add_watermarker=False)
import ipdb; ipdb.set_trace()
# pipe.enable_xformers_memory_efficient_attention()
print(time.time() - start_time)
pipe.to("cuda")
if use_refiner:
start_time = time.time()
refiner = StableDiffusionXLImg2ImgPipeline.from_pretrained(refiner_path, vae=vae, torch_dtype=torch.float16, use_safetensors=True, variant="fp16")
print(time.time() - start_time)
refiner.to("cuda")
# refiner.enable_sequential_cpu_offload()
else:
start_time = time.time()
pipe = StableDiffusionXLPipeline.from_single_file("https://huggingface.co/stabilityai/stable-diffusion-xl-base-0.9/blob/main/sd_xl_base_0.9.safetensors", torch_dtype=torch.float16, use_safetensors=True)
print(time.time() - start_time)
pipe.to("cuda")
if use_refiner:
start_time = time.time()
refiner = StableDiffusionXLImg2ImgPipeline.from_single_file("https://huggingface.co/stabilityai/stable-diffusion-xl-refiner-0.9/blob/main/sd_xl_refiner_0.9.safetensors", torch_dtype=torch.float16, use_safetensors=True)
print(time.time() - start_time)
refiner.to("cuda")
prompt = "An astronaut riding a green horse on Mars"
steps = 20
seed = 0
seed_everything(seed)
start_time = time.time()
image = pipe(prompt=prompt, num_inference_steps=steps, output_type="latent" if use_refiner else "pil").images[0]
print(time.time() - start_time)
if use_refiner:
image = refiner(prompt=prompt, num_inference_steps=steps - 10, image=image).images[0]
file_name = f"aaa"
path = os.path.join(Path.home(), "images", "ediffi_sdxl", f"{file_name}.png")
image.save(path)
api.upload_file(
path_or_fileobj=path,
path_in_repo=path.split("/")[-1],
repo_id="patrickvonplaten/images",
repo_type="dataset",
)
print(f"https://huggingface.co/datasets/patrickvonplaten/images/blob/main/{file_name}.png")
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