set_random_seed

Random seed setup method.

It sets up the random seeds for the RPN model prior to model training and testing.

Specifically, this method will set up the random seeds and related configurations of multiple packages, including * numpy * random * torch * torch.cuda * torch.cudnn * torch.mps

Parameters:

Name	Type	Description	Default
random_seed	int	The random seed to be setup.	0

Returns:

Type	Description
None	This method doesn't have any return values.

Source code in tinybig/util/util.py

def set_random_seed(random_seed: int = 0):
    """
    Random seed setup method.

    It sets up the random seeds for the RPN model prior to model training and testing.

    Specifically, this method will set up the random seeds and related configurations of multiple packages,
    including
    * numpy
    * random
    * torch
    * torch.cuda
    * torch.cudnn
    * torch.mps

    Parameters
    ----------
    random_seed: int, default = 0
        The random seed to be setup.

    Returns
    -------
    None
        This method doesn't have any return values.
    """
    torch.manual_seed(random_seed)
    random.seed(random_seed)
    np.random.seed(random_seed)
    torch.cuda.manual_seed(random_seed)
    torch.cuda.manual_seed_all(random_seed)  # if using multi-GPU.
    torch.backends.cudnn.deterministic = True
    torch.backends.cudnn.benchmark = False
    if torch.backends.mps.is_available():
        torch.mps.manual_seed(random_seed)