seed

optimus_dl.core.seed

Utilities for setting random seeds for reproducibility.

set_seed(seed, deterministic=False)

Set random seeds for reproducibility across different libraries.

Parameters:

Name	Type	Description	Default
seed	int	The integer seed to set.	required
deterministic	bool	If True, makes CUDA operations deterministic. Note: This can sometimes come with a performance penalty.	False

Source code in optimus_dl/core/seed.py

def set_seed(seed: int, deterministic: bool = False) -> None:
    """Set random seeds for reproducibility across different libraries.

    Args:
        seed: The integer seed to set.
        deterministic: If True, makes CUDA operations deterministic.
            Note: This can sometimes come with a performance penalty.
    """
    random.seed(seed)
    np.random.seed(seed)
    torch.manual_seed(seed)
    torch.cuda.manual_seed_all(seed)

    if deterministic:
        torch.backends.cudnn.benchmark = False
        torch.backends.cudnn.deterministic = True

        # Force determinism in PyTorch operations
        torch.use_deterministic_algorithms(True, warn_only=True)