utils.py

import numpy as np
import torch
import random
from PIL import Image

def enable_deterministic_execution():
    torch.backends.cudnn.benchmark = False
    torch.backends.cudnn.deterministic = True
    torch.backends.cudnn.allow_tf32 = False
    if torch.cuda.is_available():
        torch.backends.cuda.matmul.allow_tf32 = False
    torch.use_deterministic_algorithms(True)

def seed_everything(seed):
    random.seed(seed)
    np.random.seed(seed)
    torch.manual_seed(seed)
    if torch.cuda.is_available():
        torch.cuda.manual_seed(seed)
        torch.cuda.manual_seed_all(seed)

def denormalize(image):
    image = (image / 2 + 0.5).clamp(0, 1)
    image = image.cpu().permute(0, 2, 3, 1).numpy()
    return (image * 255).round().astype("uint8")

def save_image(image, filename):
    """
    Image should be in range (0, 255) and numpy array
    """
    image = Image.fromarray(image)
    image.save(filename)