QVjiddlZddlZddlmZmZmZddlmZddlm Z edZ dgZ Gdde e Z dS)N)IterableIteratorSized)TypeVar) IterDataPipe_TIterableWrapperIterDataPipecXeZdZdZd deededdfdZdeefdZ de fd Z dS) r a Wraps an iterable object to create an IterDataPipe. Args: iterable: Iterable object to be wrapped into an IterDataPipe deepcopy: Option to deepcopy input iterable object for each iterator. The copy is made when the first element is read in ``iter()``. .. note:: If ``deepcopy`` is explicitly set to ``False``, users should ensure that the data pipeline doesn't contain any in-place operations over the iterable instance to prevent data inconsistency across iterations. Example: >>> # xdoctest: +SKIP >>> from torchdata.datapipes.iter import IterableWrapper >>> dp = IterableWrapper(range(10)) >>> list(dp) [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] TiterabledeepcopyreturnNc"||_||_dS)N)r r )selfr r s _/root/voice-cloning/.venv/lib/python3.11/site-packages/torch/utils/data/datapipes/iter/utils.py__init__z$IterableWrapperIterDataPipe.__init__$s    c#K|j}|jr? tj|j}n$#t$rt jdYnwxYw|Ed{VdS)NzlThe input iterable can not be deepcopied, please be aware of in-place modification would affect source data.)r r copy TypeErrorwarningswarn)r source_datas r__iter__z$IterableWrapperIterDataPipe.__iter__(sm =  "mDM::     Y  s,A  A ct|jtrt|jSt t |jd)Nz# instance doesn't have valid length) isinstancer rlenrtype__name__)rs r__len__z#IterableWrapperIterDataPipe.__len__8sF dmU + + &t}%% %4::.SSSTTTr)T) r __module__ __qualname____doc__rrboolrrrintrrrr r s*!!"!!!!!!(2, UUUUUUUr) rrcollections.abcrrrtypingr#torch.utils.data.datapipes.datapiperr__all__r r%rrr*s 5555555555<<<<<< WT]] ( )-U-U-U-U-U,r"2-U-U-U-U-Ur