chainer.datasets.TupleDataset

class chainer.datasets.TupleDataset(*datasets)

Dataset of tuples from multiple equal-length datasets.

A TupleDataset combines multiple equal-length datasets into a single dataset of tuples. The i-th tuple contains the i-th example from each of the argument datasets, in the same order that they were supplied.

Recall that in Chainer, a dataset is defined as an iterable that supports both __getitem__ and __len__. The __getitem__ method should support indexing by both an integer and a slice.

As an example, consider creating a TupleDataset from two argument datasets d1 = [8, 0, 5, 1] and d2 = [3, 1, 7, 4] as tuple_dataset = TupleDataset(d1, d2). The tuple_dataset will then contain the examples (8, 3), (0, 1), (5, 7), (1, 4). Note that this behavior is similar to that of the built-in zip() function.

Parameters

datasets – Underlying datasets that will be aggregated. Each dataset must be an iterable that implements __getitem__ and __len__. The j-th dataset will be used for the j-th item of each example tuple. All datasets must have the same length.

Methods

__getitem__(index)

__len__()

__eq__(value, /)

Return self==value.

__ne__(value, /)

Return self!=value.

__lt__(value, /)

Return self<value.

__le__(value, /)

Return self<=value.

__gt__(value, /)

Return self>value.

__ge__(value, /)

Return self>=value.