结果固定代码

def seed_torch(seed):
    os.environ['PYTHONHASHSEED'] = str(seed)
    np.random.seed(seed)
    torch.manual_seed(seed)
    torch.cuda.manual_seed(seed)
    torch.backends.cudnn.benchmark = False
    torch.backends.cudnn.deterministic = True 

def seed_torch(seed):
    """
    Set the random seed for various modules to ensure reproducibility.
    
    Args:
    seed (int): The seed value to be set.
    """
    # Set PYTHONHASHSEED environment variable
    os.environ['PYTHONHASHSEED'] = str(seed)
    
    # Set random seed for Python's built-in random module
    random.seed(seed)
    
    # Set random seed for numpy
    np.random.seed(seed)
    
    # Set random seed for PyTorch
    torch.manual_seed(seed)
    
    # Set random seed for PyTorch (CUDA)
    if torch.cuda.is_available():
        torch.cuda.manual_seed(seed)
        torch.cuda.manual_seed_all(seed)  # if you are using multi-GPU.
    
    # Ensure that the cuDNN library's benchmark mode is disabled, and that 
    # cuDNN is deterministic.
    torch.backends.cudnn.benchmark = False
    torch.backends.cudnn.deterministic = True