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import os
import random
from typing import Callable, Dict, Optional, Tuple
import gradio as gr
import numpy as np
import PIL.Image
import spaces
import torch
from transformers import CLIPTextModel
from diffusers import AutoencoderKL, StableDiffusionXLPipeline, DDIMScheduler, DPMSolverMultistepScheduler, DPMSolverSinglestepScheduler, EulerAncestralDiscreteScheduler, EulerDiscreteScheduler
MODEL = "eienmojiki/Starry-XL-v5.2"
HF_TOKEN = os.getenv("HF_TOKEN")
MIN_IMAGE_SIZE = int(os.getenv("MIN_IMAGE_SIZE", "512"))
MAX_IMAGE_SIZE = int(os.getenv("MAX_IMAGE_SIZE", "2048"))
MAX_SEED = np.iinfo(np.int32).max
torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = False
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
if randomize_seed:
seed = random.randint(0, MAX_SEED)
return seed
def seed_everything(seed: int) -> torch.Generator:
torch.manual_seed(seed)
torch.cuda.manual_seed_all(seed)
np.random.seed(seed)
generator = torch.Generator()
generator.manual_seed(seed)
return generator
def get_scheduler(scheduler_config: Dict, name: str) -> Optional[Callable]:
scheduler_factory_map = {
"DPM++ 2M Karras": lambda: DPMSolverMultistepScheduler.from_config(
scheduler_config, use_karras_sigmas=True
),
"DPM++ SDE Karras": lambda: DPMSolverSinglestepScheduler.from_config(
scheduler_config, use_karras_sigmas=True
),
"DPM++ 2M SDE Karras": lambda: DPMSolverMultistepScheduler.from_config(
scheduler_config, use_karras_sigmas=True, algorithm_type="sde-dpmsolver++"
),
"Euler": lambda: EulerDiscreteScheduler.from_config(scheduler_config),
"Euler a": lambda: EulerAncestralDiscreteScheduler.from_config(scheduler_config),
"DDIM": lambda: DDIMScheduler.from_config(scheduler_config),
}
return scheduler_factory_map.get(name, lambda: None)()
def load_pipeline(model_name):
pipe = StableDiffusionXLPipeline.from_pretrained(
model_name,
torch_dtype=torch.float16,
custom_pipeline="lpw_stable_diffusion_xl",
use_safetensors=True,
add_watermarker=False,
use_auth_token=HF_TOKEN,
)
pipe.to(device)
return pipe
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