+ jBaRt0t^RIHt.t]^kRRltRRltR#))ChunkStorageMetadatac<V^8dQhR\R\R\/#)shard1shard2return)rbool)formats"h/home/luca/screen-checking/.venv/lib/python3.14/site-packages/torch/distributed/checkpoint/resharding.py __annotate__r s$ *> cd\VP4p\V4FpVPV,VPV,VPV,,8dR#VPV,VPV,VPV,,8gKR# R#)zCheck if two shards overlap.FT)lenoffsetsrangesizes)rrndimsis&& r "_check_shard_metadata_pair_overlaprsy  E 5\ >>! q 1FLLO C C >>! q 1FLLO C C  r c V^8dQhR\R\R\\\\\\3,,/#)r saved_shard current_shardr)rlisttupleint)r s"r r r s7,,%,6J, %S#s" #$,r cV.p\\VPVPVPVP44Fcwpwpppp\ WF,WW,4pV\ WT4, p WE8d ^p WE, p M WT, p ^p VP W:W34Ke V#)aA Return the overlapping region between saved_shard and current_shard. The returned list has the same number of elements as the tensor's dimension. For each element, we produce a tuple with the following contents: (dimension, `saved_shard` offset, `current_shard` offset, length) Offsets are relative to each shard. ) enumerateziprrminmaxappend) rrnarrowsdimsaved_shard_offsetcurrent_shard_offsetsaved_shard_sizecurrent_shard_size min_range_endlengthoffset_for_saved_tensoroffset_for_current_tensors && r +_shards_get_overlap_region_wrt_saved_tensorr,sG      ! !             1 5 %9!NN  4&' #(:(Q %&:&O #() % +D M - 4 Nr cVV^8dQh/^\9d\\,;R&#)r__all__)__conditional_annotations__rstr)r s"r r r sFFcGr N)r/%torch.distributed.checkpoint.metadatarr.rr,r )r/s@r r2s FF$,r