Vh ddlmZddlmZddlmZddlmZddgZGddeZ Gdd eZ ed Gd de Z y ) )Sized)IntEnum)functional_datapipe) IterDataPipeSHARDING_PRIORITIESShardingFilterIterDataPipeceZdZdZdZdZy)rN)__name__ __module__ __qualname__DEFAULT DISTRIBUTEDMULTIPROCESSINGX/home/dcms/DCMS/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/sharding.pyrrsGKOrc eZdZdededefdZy)_ShardingIterDataPipenum_of_instances instance_idsharding_groupctN)NotImplementedErrorselfrrrs rapply_shardingz$_ShardingIterDataPipe.apply_shardings "!rN)r rrintrr rrrrrs#""", "rrsharding_filtercNeZdZdZd defdZejfdZdZ dZ dZ y) rao Wrapper that allows DataPipe to be sharded (functional name: ``sharding_filter``). After ``apply_sharding`` is called, each instance of the DataPipe (on different workers) will have every `n`-th element of the original DataPipe, where `n` equals to the number of instances. Args: source_datapipe: Iterable DataPipe that will be sharded Nsource_datapipecj||_||_i|_d|_d|_|j yNr r)r$sharding_group_filtergroupsrr_update_num_of_instances)rr$r's r__init__z#ShardingFilterIterDataPipe.__init__+s5.%:"24 ! %%'rc`||k\rtd|d|d|tjk(rycc}wr&)sortedr(keysr'reverserr)rkeysorted_sharding_groupsgroup_num_of_instancesgroup_instance_ids rr)z3ShardingFilterIterDataPipe._update_num_of_instancesGsdkk..01" ))1SDrHs`!E<   ' "L"&'EU!6EU(EUr