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 asbatch_size
ifdrop_last
is set toTrue
, orlength % batch_size
for the last batch ifdrop_last
is set toFalse
.- 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]]