к ╘sg'ЦС<≈ddlZddlZddlmZdgZGd└de╚Zy)ИN)зMapDataPipeзSequenceWrapperMapDataPipecС$≈eZdZdZdd└Zd└Zd└Zy)raЖ Wraps a sequence object into a MapDataPipe. Args: sequence: Sequence object to be wrapped into an MapDataPipe deepcopy: Option to deepcopy input sequence object .. note:: If ``deepcopy`` is set to False explicitly, users should ensure that data pipeline doesn't contain any in-place operations over the iterable instance, in order to prevent data inconsistency across iterations. Example: >>> # xdoctest: +SKIP >>> from torchdata.datapipes.map import SequenceWrapper >>> dp = SequenceWrapper(range(10)) >>> list(dp) [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] >>> dp = SequenceWrapper({'a': 100, 'b': 200, 'c': 300, 'd': 400}) >>> dp['a'] 100 cСє≈|r tj|╚|_y||_y#t$rt j d╚||_YywxYw)NzkThe input sequence can not be deepcopied, please be aware of in-place modification would affect source data)зcopyзdeepcopyзsequenceз TypeErrorзwarningsзwarn)зselfr rs ЗW/var/www/html/venv/lib/python3.12/site-packages/torch/utils/data/datapipes/map/utils.pyз__init__z#SequenceWrapperMapDataPipe.__init__$sO─ыП )э $ї ║ ╗hс 7░∙ П%┬D█MЬТР )э≈ ▒ ПXТП!)░√ П )Зs└'ї%AаAcС ≈|j|S╘N)r )r зindexs rз__getitem__z&SequenceWrapperMapDataPipe.__getitem__1s─ь▐}┴}≤Uя#п#СcС,≈t|j╚Sr)зlenr )r s rз__len__z"SequenceWrapperMapDataPipe.__len__4s─э░4≈=▒=с!п!rN)T)з__name__з __module__з__qualname__з__doc__rrr╘rrrrs└ЯС0%Р$С"r)rrз#torch.utils.data.datapipes.datapiperз__all__rrrrЗrs$ПЦшЕ;П(п (─Т*"═У*"r