torchwrench.utils.data.sampler module¶

class torchwrench.utils.data.sampler.BalancedSampler(indices_per_class: Sequence[Sequence[int]], n_max_iterations: int, shuffle: bool = True, seed: Generator | None | 'default' | int = None)[source]¶

Bases: Sampler

class torchwrench.utils.data.sampler.SubsetCycleSampler(indices: Tensor | Iterable[int], n_max_iterations: int | 'inf' = 'inf', shuffle: bool = True, seed: Generator | None | 'default' | int = None)[source]¶

Bases: Sampler[int]

class torchwrench.utils.data.sampler.SubsetSampler(indices: list[int] | Tensor)[source]¶

Bases: Sampler[int]