- class torchdata.datapipes.iter.LengthSetter(source_datapipe: IterDataPipe[T_co], length: int)¶
Set the length attribute of the DataPipe, which is returned by
set_length). This can be used after DataPipes whose final length cannot be known in advance (e.g.
filter). If you know the final length with certainty, you can manually set it, which can then be used by DataLoader or other DataPipes.
This DataPipe differs from
Headerin that this doesn’t restrict the number of elements that can be yielded from the DataPipe; this is strictly used for setting an attribute so that it can be used later.
source_datapipe – a DataPipe
length – the integer value that will be set as the length
>>> from torchdata.datapipes.iter import IterableWrapper >>> dp = IterableWrapper(range(10)).filter(lambda x: x < 5).set_length(3) >>> list(dp) # Notice that the number of elements yielded is unchanged [0, 1, 2, 3, 4] >>> len(dp) 3 >>> header_dp = IterableWrapper(range(10)).filter(lambda x: x < 5).header(3) >>> list(header_dp) # Use `.header()` if you want to limit the number of elements yielded [0, 1, 2] >>> len(header_dp) 3