pytorch/torch/utils/data/_utils/fetch.py
Aaron Gokaslan 8fce9a09cd [BE]: pyupgrade Python to 3.8 - imports and object inheritance only (#94308)
Apply parts of pyupgrade to torch (starting with the safest changes).
This PR only does two things: removes the need to inherit from object and removes unused future imports.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/94308
Approved by: https://github.com/ezyang, https://github.com/albanD
2023-02-07 21:10:56 +00:00

62 lines
2.1 KiB
Python

r""""Contains definitions of the methods used by the _BaseDataLoaderIter to fetch
data from an iterable-style or map-style dataset. This logic is shared in both
single- and multi-processing data loading.
"""
class _BaseDatasetFetcher:
def __init__(self, dataset, auto_collation, collate_fn, drop_last):
self.dataset = dataset
self.auto_collation = auto_collation
self.collate_fn = collate_fn
self.drop_last = drop_last
def fetch(self, possibly_batched_index):
raise NotImplementedError()
class _IterableDatasetFetcher(_BaseDatasetFetcher):
def __init__(self, dataset, auto_collation, collate_fn, drop_last):
super(_IterableDatasetFetcher, self).__init__(
dataset, auto_collation, collate_fn, drop_last
)
self.dataset_iter = iter(dataset)
self.ended = False
def fetch(self, possibly_batched_index):
if self.ended:
raise StopIteration
if self.auto_collation:
data = []
for _ in possibly_batched_index:
try:
data.append(next(self.dataset_iter))
except StopIteration:
self.ended = True
break
if len(data) == 0 or (
self.drop_last and len(data) < len(possibly_batched_index)
):
raise StopIteration
else:
data = next(self.dataset_iter)
return self.collate_fn(data)
class _MapDatasetFetcher(_BaseDatasetFetcher):
def __init__(self, dataset, auto_collation, collate_fn, drop_last):
super(_MapDatasetFetcher, self).__init__(
dataset, auto_collation, collate_fn, drop_last
)
def fetch(self, possibly_batched_index):
if self.auto_collation:
if hasattr(self.dataset, "__getitems__") and self.dataset.__getitems__:
data = self.dataset.__getitems__(possibly_batched_index)
else:
data = [self.dataset[idx] for idx in possibly_batched_index]
else:
data = self.dataset[possibly_batched_index]
return self.collate_fn(data)