dataeval.config.set_seed¶
-
dataeval.config.set_seed(seed, all_generators=
False, deterministic=False)¶ Set the seed for use by classes that allow for a random state or seed.
- Parameters:¶
- seed : int or None¶
The seed to use. When None, clears the DataEval seed and resets all generators (NumPy, PyTorch) and deterministic settings regardless of other parameters.
- all_generators : bool, default False¶
Whether to set the seed for all generators, including NumPy and PyTorch.
- deterministic : bool, default False¶
Whether to force PyTorch to use deterministic algorithms. When True, calls
torch.use_deterministic_algorithms(True), which ensures reproducible results but may reduce performance.