LengthSetter

class torchdata.datapipes.iter.LengthSetter(source_datapipe: IterDataPipe[T_co], length: int)

Set the length attribute of the DataPipe, which is returned by __len__ (functional name: 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.

Note

This DataPipe differs from Header in 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.

Parameters:

• source_datapipe – a DataPipe

• length – the integer value that will be set as the length

Example

>>> 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