from_pretrained orchestration + distributed save/load#45409
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3outeille wants to merge 1 commit intomoe-sequence-parallelfrom
Open
from_pretrained orchestration + distributed save/load#454093outeille wants to merge 1 commit intomoe-sequence-parallelfrom
3outeille wants to merge 1 commit intomoe-sequence-parallelfrom
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- Add gather_full_state_dict() for DTensor→full tensor saving - Add convert_strided_to_shard() / restore_strided_from_shard() for DCP - Add _redistribute_dtensor() helper - Full distributed_config integration in from_pretrained/save_pretrained - Rename apply_fsdp2 → apply_fully_shard_data_parallel - save_optimizer() / load_optimizer() in distributed/utils - Trainer integration with distributed_config - Updated FSDP and TP tests for new orchestration API - DTensor shard-on-read test updates
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Summary
distributed_configintegration infrom_pretrained()— mesh creation, apply TP + FSDP, attachmodel.device_meshgather_full_state_dict()for streaming DTensor→full tensor saving (rank 0 only)convert_strided_to_shard()/restore_strided_from_shard()for DCP compatibility with_StridedShardsave_optimizer()/load_optimizer()indistributed/utils.pyapply_fsdp2→apply_fully_shard_data_paralleldistributed_configPart of the distributed training API chain: #44989
Chain:
main ← #44989 ← #44083 ← #44974 ← #45028 ← #45408 ← this PRReview question
Does
from_pretrainedwire things up in the right order? Is save/load round-trip correct?Test plan
from_pretrainedwith distributed_configgather_full_state_dict()roundtrip verificationsave_optimizer()/load_optimizer()roundtrip