pyabsa.framework.sampler_class.imblanced_sampler

Module Contents

Classes

ImbalancedDatasetSampler

Samples elements randomly from a given list of indices for imbalanced dataset
class pyabsa.framework.sampler_class.imblanced_sampler.ImbalancedDatasetSampler(dataset, labels: list = None, indices: list = None, num_samples: int = None, callback_get_label: Callable = None)[source]

Bases: torch.utils.data.sampler.Sampler

Samples elements randomly from a given list of indices for imbalanced dataset

Parameters:

  • indices – a list of indices

  • num_samples – number of samples to draw

  • callback_get_label – a callback-like function which takes two arguments - dataset and index

_get_labels(dataset)[source]
__iter__()[source]
__len__()[source]