o wZŽh'ã@s6ddlZddlZddlmZdgZGdd„deƒZdS)éN)Ú MapDataPipeÚSequenceWrapperMapDataPipec@s*eZdZdZd dd„Zdd„Zdd„Zd S) raö Wraps a sequence object into a MapDataPipe. Args: sequence: Sequence object to be wrapped into an MapDataPipe deepcopy: Option to deepcopy input sequence object .. note:: If ``deepcopy`` is set to False explicitly, users should ensure that data pipeline doesn't contain any in-place operations over the iterable instance, in order to prevent data inconsistency across iterations. Example: >>> # xdoctest: +SKIP >>> from torchdata.datapipes.map import SequenceWrapper >>> dp = SequenceWrapper(range(10)) >>> list(dp) [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] >>> dp = SequenceWrapper({'a': 100, 'b': 200, 'c': 300, 'd': 400}) >>> dp['a'] 100 TcCsF|rz t |¡|_WdStyt d¡||_YdSw||_dS)NzkThe input sequence can not be deepcopied, please be aware of in-place modification would affect source data)ÚcopyÚdeepcopyÚsequenceÚ TypeErrorÚwarningsÚwarn)Úselfrr©r úS/var/www/auris/lib/python3.10/site-packages/torch/utils/data/datapipes/map/utils.pyÚ__init__$s ÿ û z#SequenceWrapperMapDataPipe.__init__cCs |j|S©N)r)r Úindexr r r Ú __getitem__1ó z&SequenceWrapperMapDataPipe.__getitem__cCs t|jƒSr)Úlenr)r r r r Ú__len__4rz"SequenceWrapperMapDataPipe.__len__N)T)Ú__name__Ú __module__Ú __qualname__Ú__doc__r rrr r r r r s   )rrZ#torch.utils.data.datapipes.datapiperÚ__all__rr r r r Ús