o eix@s:ddlmZddlmZddlmZeGdddZdS)) dataclass)reduce)_remote_devicec@speZdZUdZgdZeeed<eeed<edBed< d deedeede eBdBfddZ d d Z dS) ShardMetadataaH Represents a shard of the overall Tensor including its offsets, lengths and device placement. Args: shard_offsets(List[int]): Offsets in the original tensor indicating the start offsets for this shard. Should have the same rank as the original tensor. shard_sizes(List[int]): Integers indicating the size of each dimension for this shard. Should have the same rank as the original tensor. placement(:class:`torch.distributed._remote_device`): Specifies the placement of this shard. ) shard_offsets shard_sizes placementrrNrcCs||_||_t|trt||_n||_t|jt|jkr-tdt|jd|jdtt|jD]}|j|dkrAtd|j|dkrLtdq4dS)NzMshard_offsets and shard_sizes should have the same number of elements, found z and z respectivelyrzshard_offsets should be >=0zshard_sizes should be >= 0) rr isinstancestrrrlen ValueErrorrange)selfrrrirk/var/www/addictedbytheproject.nl/epg/venv/lib/python3.10/site-packages/torch/distributed/_shard/metadata.py__init__s(  zShardMetadata.__init__cCs4dd}t||jd}t||j|}|||j}|S)NcSs|d>t|S)N)hash)abrrr _hash_reduce9sz,ShardMetadata.__hash__.._hash_reduce%)rrrr)rrresrrr__hash__8s  zShardMetadata.__hash__)N) __name__ __module__ __qualname____doc__ __slots__listint__annotations__rr rrrrrrrs      rN) dataclassesr functoolsrtorch.distributed.remote_devicerrrrrrs