SequenceWrapper

class torchdata.datapipes.map.SequenceWrapper(sequence, deepcopy=True)

Wraps a sequence object into a MapDataPipe.

Parameters:

• sequence – Sequence object to be wrapped into an MapDataPipe

• deepcopy – Option to deepcopy input sequence object

Note

If deepcopy is set to False explicitly, users should ensure that data pipeline doesn’t contain any in-place operations over the iterable instance, in order to prevent data inconsistency across iterations.

Example

>>> # xdoctest: +SKIP
>>> from torchdata.datapipes.map import SequenceWrapper
>>> dp = SequenceWrapper(range(10))
>>> list(dp)
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
>>> dp = SequenceWrapper({'a': 100, 'b': 200, 'c': 300, 'd': 400})
>>> dp['a']
100