brails.processors.foundation_classifier.csail_segmentation_tool.csail_seg.lib.utils.data.dataset module

class brails.processors.foundation_classifier.csail_segmentation_tool.csail_seg.lib.utils.data.dataset.ConcatDataset(datasets)

Bases: Dataset

Dataset to concatenate multiple datasets. Purpose: useful to assemble different existing datasets, possibly large-scale datasets as the concatenation operation is done in an on-the-fly manner.

Arguments:

datasets (iterable): List of datasets to be concatenated

property cummulative_sizes

static cumsum(sequence)

class brails.processors.foundation_classifier.csail_segmentation_tool.csail_seg.lib.utils.data.dataset.Dataset

Bases: object

An abstract class representing a Dataset.

All other datasets should subclass it. All subclasses should override __len__, that provides the size of the dataset, and __getitem__, supporting integer indexing in range from 0 to len(self) exclusive.

class brails.processors.foundation_classifier.csail_segmentation_tool.csail_seg.lib.utils.data.dataset.Subset(dataset, indices)

Bases: Dataset

class brails.processors.foundation_classifier.csail_segmentation_tool.csail_seg.lib.utils.data.dataset.TensorDataset(data_tensor, target_tensor)

Bases: Dataset

Dataset wrapping data and target tensors.

Each sample will be retrieved by indexing both tensors along the first dimension.

Arguments:

data_tensor (Tensor): contains sample data. target_tensor (Tensor): contains sample targets (labels).

brails.processors.foundation_classifier.csail_segmentation_tool.csail_seg.lib.utils.data.dataset.random_split(dataset, lengths)

Randomly split a dataset into non-overlapping new datasets of given lengths ds

Arguments:

dataset (Dataset): Dataset to be split lengths (iterable): lengths of splits to be produced