Batcher

class torchdata.datapipes.map.Batcher(datapipe: MapDataPipe[T], batch_size: int, drop_last: bool = False, wrapper_class=List)

Create mini-batches of data (functional name: batch).

An outer dimension will be added as batch_size if drop_last is set to True, or length % batch_size for the last batch if drop_last is set to False.

Parameters:

• datapipe – Iterable DataPipe being batched

• batch_size – The size of each batch

• drop_last – Option to drop the last batch if it’s not full

Example

>>> # xdoctest: +SKIP
>>> from torchdata.datapipes.map import SequenceWrapper
>>> dp = SequenceWrapper(range(10))
>>> batch_dp = dp.batch(batch_size=2)
>>> list(batch_dp)
[[0, 1], [2, 3], [4, 5], [6, 7], [8, 9]]