Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63522
Supports sharding and batching on loader level
* **#63522 Adding IterableAsDataPipe IterDataPipe
usefull for tests and simple cases**
usefull for tests and simple cases
Test Plan: Imported from OSS
Reviewed By: ejguan
Differential Revision:
D30426528
Pulled By: VitalyFedyunin
fbshipit-source-id:
535b5cc1505bb58731fcca8170541ac5ee7bd417
from torch.utils.data.datapipes.iter.tobytes import (
ToBytesIterDataPipe as ToBytes,
)
+from torch.utils.data.datapipes.iter.utils import (
+ IterableAsDataPipeIterDataPipe as IterableAsDataPipe,
+)
__all__ = ['Batch',
'BucketBatcher',
'Filter',
'GroupByKey',
'HttpReader',
+ 'IterableAsDataPipe',
'ListDirFiles',
'LoadFilesFromDisk',
'Map',
--- /dev/null
+from torch.utils.data import IterDataPipe
+
+
+class IterableAsDataPipeIterDataPipe(IterDataPipe):
+ def __init__(self, iterable):
+ self.iterable = iterable
+
+ def __iter__(self):
+ for data in self.iterable:
+ yield data