DŽg<ddlZddlZddlmZdgZGddeZy)N) IterDataPipeIterableWrapperIterDataPipec$eZdZdZddZdZdZy)ra Wraps an iterable object to create an IterDataPipe. Args: iterable: Iterable object to be wrapped into an IterDataPipe deepcopy: Option to deepcopy input iterable object for each iterator. The copy is made when the first element is read in ``iter()``. .. note:: If ``deepcopy`` is explicitly set to ``False``, users should ensure that the data pipeline doesn't contain any in-place operations over the iterable instance to prevent data inconsistency across iterations. Example: >>> # xdoctest: +SKIP >>> from torchdata.datapipes.iter import IterableWrapper >>> dp = IterableWrapper(range(10)) >>> list(dp) [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] c ||_||_yN)iterabledeepcopy)selfrr s m/home/mcse/projects/flask_80/flask-venv/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/utils.py__init__z$IterableWrapperIterDataPipe.__init__!s    c#K|j}|jr tj|j}|Ed{y#t$rt j dY+wxYw7)w)NzlThe input iterable can not be deepcopied, please be aware of in-place modification would affect source data.)rr copy TypeErrorwarningswarn)r source_datas r __iter__z$IterableWrapperIterDataPipe.__iter__%s`mm == "mmDMM:    Y  s3A,AA,A*A,A'$A,&A''A,c,t|jSr)lenr)r s r __len__z#IterableWrapperIterDataPipe.__len__5s4==!!r N)T)__name__ __module__ __qualname____doc__r rrr r rr s*! "r )rr#torch.utils.data.datapipes.datapiper__all__rrr r rs$ < ) )+",+"r