[MXFP8/FP4-param-gather] Post processing after forced param AG in eval#4562
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Signed-off-by: qiyuw <qiyuw@nvidia.com>
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Signed-off-by: qiyuw <qiyuw@nvidia.com>
Signed-off-by: qiyuw <qiyuw@nvidia.com>
Signed-off-by: qiyuw <qiyuw@nvidia.com>
Signed-off-by: qiyuw <qiyuw@nvidia.com>
Signed-off-by: qiyuw <qiyuw@nvidia.com>
Signed-off-by: qiyuw <qiyuw@nvidia.com>
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/ok to test b7a1243 |
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Signed-off-by: qiyuw <qiyuw@nvidia.com>
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/claude review |
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/ok to test a853e77 |
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NVIDIA#4562) Signed-off-by: qiyuw <qiyuw@nvidia.com>
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* origin/main: (50 commits) Drain predecessor reduce-scatter at dispatch time (NVIDIA#4940) ci: Add allow_failure flag to gpt and moe recipes that are failing in nightlies (NVIDIA#4905) fix(tests): initialize num_microbatches calculator in vision cudagraph tests (NVIDIA#4986) test: re-enable test_pp2_create_cudagraphs_first_stage on TE 2.15+ (NVIDIA#4985) ci: Add support for MBridge job gating based on PR labels (NVIDIA#4926) test(ci): re-enable 8experts2parallel_multi_dist_optimizer_instances_1node (NVIDIA#4984) test: re-enable paged stashing MoE tests (NVIDIA#4978) Fix elastification unwrap_model import (NVIDIA#4972) Avoid offsetting functional test master port (NVIDIA#4973) test: enable NVTE_CUTEDSL_FUSED_GROUPED_MLP via pytest fixture (NVIDIA#4931) chore(beep boop 🤖): Bump (main) (2026-05-25) test(release): add release goldens for deepseekv3/nemotron3 and set tp2pp2 exit-interval (NVIDIA#4932) Fix `get_batch` return order to ignore BlendedDataset provenance fields (NVIDIA#4952) ci: restore perf test torchrun logs (NVIDIA#4951) Various training utils (NVIDIA#4872) ci: Update training script paths in BERT and T5 (NVIDIA#4939) [MXFP8/FP4-param-gather] Post processing after forced param AG in eval (NVIDIA#4562) Fix mxfp8 param gather numerical issue when DP overlap is off (NVIDIA#4800) Add TEFusedDenseMLP for Dense+Grouped GEMM fusion on SM100+ (NVIDIA#4318) (NVIDIA#4786) Fix paged stashing test submodules lookup (NVIDIA#4925) ... # Conflicts: # megatron/training/training.py
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NVIDIA#4562) Signed-off-by: qiyuw <qiyuw@nvidia.com>
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What does this PR do ?
The same PR to dev has been merged: #4563
Fixes FP8/MXFP8/FP4 parameter-gather convergence when eval runs between training steps.
When eval disables forward pre-hooks, start_param_sync(force_sync=True) can complete parameter all-gather synchronously. In that path there is no async gather handle for the next train forward hook to wait on (line), so the usual post-all-gather processing was skipped in next train step. In eval, the post processing is also skipped if the job enables overlap_param_gather (line). With FP8 (blockwise scaling) or FP4 param gather, this can leave columnwise weight storage stale while rowwise storage has been refreshed, causing the next train backward to use staled weights. With MXFP8 param+reuse_grad_buff_for_mxfp8_param_ag, the AG'ed weights will not be copied(quantized) from param buffer to model weights, which is not correct.
In this PR we add post processing in bucket group's start_param_sync for synchronous gather, hence making sure the above cases are correctly handled.
Validated the fix on DSv3 proxy model pretraining for FP4 param gather:

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