Add sequence packing support for hybrid model#2913
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duncanriach merged 24 commits intoNVIDIA:mainfrom Jan 16, 2026
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This is a cherry-pick of commit cd0a3206 from branch duncan/hybrid-packed-sequence-for-training-moe-june2025, which targets the training-moe-june2025 branch.
This is a cherry-pick of commit 77e69a6a from branch duncan/hybrid-packed-sequence-for-training-moe-june2025, which targets the training-moe-june2025 branch.
This is a cherry-pick of commit 16c5e363 from branch duncan/hybrid-packed-sequence-for-training-moe-june2025, which targets the training-moe-june2025 branch.
This is a cherry-pick of commit bfe73c8e from branch duncan/hybrid-packed-sequence-for-training-moe-june2025, which targets the training-moe-june2025 branch.
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Co-authored-by: Eric Harper <eharper@nvidia.com> Co-authored-by: Philip Petrakian <ppetrakian@nvidia.com>
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What does this PR do ?
Adds sequence packing support for the hybrid model and also enhances
--sft,SFTDataset, andpretrain_mamba.pyto feed packed sequence data into the model.Causes a regression in the functionality of
--sfton the GPT model; this functionality will no longer be supported. To maintain this functionality, packed-sequence related changes would need to be made topretrain_gpt.pyfollowingpretrain_mamba.pyand, ideally, GPT model SFT packed-sequence convergence testing would need to be run. I believe this functionality will be getting added by PR 2282 from @parthmannan, which will be merged after this current PR.This PR also does not contain functional tests for packed sequence support in the hybrid model. I believe that there are currently also no functional tests for packed sequence support in the GPT model.
See internal MR 4403
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