Adding code for Flextron - #4429
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https://gitlab-master.nvidia.com/ADLR/megatron-lm/-/jobs/309002773 |
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🔄 Merge queue validation started! You can track the progress here: https://github.com/NVIDIA/Megatron-LM/actions/runs/25196645789 |
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🔄 Merge queue validation started! You can track the progress here: https://github.com/NVIDIA/Megatron-LM/actions/runs/25225179430 |
Co-authored-by: claude[bot] <209825114+claude[bot]@users.noreply.github.com> Co-authored-by: Philip Petrakian <pgpetrak@gmail.com> Signed-off-by: yhgalaxy <yhgalaxy@outlook.com>
Co-authored-by: claude[bot] <209825114+claude[bot]@users.noreply.github.com> Co-authored-by: Philip Petrakian <pgpetrak@gmail.com> Signed-off-by: Jon Barker <jbarker@aws-cmh-slurm-1-vscode-02.cm.cluster>
Co-authored-by: claude[bot] <209825114+claude[bot]@users.noreply.github.com> Co-authored-by: Philip Petrakian <pgpetrak@gmail.com>
What does this PR do ?
This PR lands Flextron (also known as Nemotron Elastic / Star Elastic) into Megatron-LM. Flextron is a post-training method that converts a single parent LLM into a nested family of submodels at different parameter budgets — all produced from one training run, all sharing a single checkpoint. A learnable router maps a user-specified budget to per-axis architectural decisions (embedding width, attention heads, Mamba heads, MoE experts, FFN channels); smaller submodels are strict subsets of larger ones via importance-ranked contiguous slicing, and all variants are trained jointly with knowledge distillation from the frozen parent.
Flextron has been used to produce the elastic variants shipped with Nemotron Nano v2 (12B → 9B + 6B) and Nemotron Nano v3 (30B/3.6A MoE → 23B/2.8A + 12B/2.0A). Until now the implementation has lived on private dev branches. This PR consolidates that work into
mainso it can be open-sourced and maintained alongside the rest of the Megatron-LM post-training surface.Files at a glance
megatron/elastification/— new module (manager, hooks, router, budget math, config).pretrain_mamba_flex.py— training entry point with per-microbatch budget sampling.megatron/core/distributed/finalize_model_grads.py— all-reduces router grads across PP ranks, gated onconfig.flextron.megatron/post_training/model_builder.py— teacher-config overrides so KD teachers don't carry the router.tests/unit_tests/elastification/— 10 test files.tests/functional_tests/test_cases/hybrid/hybrid_flextron_nightly_*/+tests/test_utils/recipes/h100/flextron.yaml— nightly functional test.Contribution process
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