MoE expert parallelism + sequence parallelism#45408
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3outeille wants to merge 2 commits intorefactor-tp-dtensorfrom
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MoE expert parallelism + sequence parallelism#454083outeille wants to merge 2 commits intorefactor-tp-dtensorfrom
3outeille wants to merge 2 commits intorefactor-tp-dtensorfrom
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- Add PackedColwiseParallel for fused gate_up_proj weights - Add MoEExpertsParallel with per-expert DTensor sharding - Add PrepareModuleInputOutput for SP allgather/split hooks - Add _AllReduceBackward for MoE routing weight gradients - Extend TPStyle with moe_experts, packed_colwise, activation, module kinds - _StridedShard handling in core_model_loading for interleaved weights - MoE model configs: mixtral, deepseek_v3, qwen3 with SP plans - DTensor rotary_pos_emb guard for mixtral
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[For maintainers] Suggested jobs to run (before merge) run-slow: deepseek_v3, mixtral, qwen3 |
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Summary
PackedColwiseParallel,MoEExpertsParallel,PrepareModuleInputOutput,_AllReduceBackwardcustom ParallelStyle subclassesTPStylewithmoe_experts,packed_colwise,activation,module,loss_parallelkinds_StridedShardhandling incore_model_loading.pyfor interleavedgate_up_projweightsmixtral,deepseek_v3,qwen3with sequence parallelism plansPart of the distributed training API chain: #44989
Chain:
main ← #44989 ← #44083 ← #44974 ← #45028 ← this PR ← orchestration+save PRReview question
Are the custom
ParallelStylesubclasses correct for expert sharding + sequence parallelism?Test plan