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@kanz-nv kanz-nv commented Dec 27, 2025

What does this PR do ?

⚠️ For major changes (either in lines of code or in its impact), please make sure to first share discuss a design-doc with the team.

Contribution process

flowchart LR
    A[Pre-checks] --> B[PR Tests]
    subgraph Code Review/Approval
        C1[Expert Review] --> C2[Final Review]
    end
    B --> C1
    C2 --> D[Merge]
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  • I want this PR in a versioned release and have added the appropriate Milestone (e.g., Core 0.8)
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@kanz-nv kanz-nv requested review from a team as code owners December 27, 2025 23:59
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copy-pr-bot bot commented Dec 27, 2025

This pull request requires additional validation before any workflows can run on NVIDIA's runners.

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@kanz-nv kanz-nv requested a review from santhnm2 December 27, 2025 23:59
@github-actions github-actions bot requested a review from Phlip79 December 27, 2025 23:59
@kanz-nv kanz-nv requested review from kvareddy and sidsingh-nvidia and removed request for Phlip79 December 27, 2025 23:59
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kanz-nv commented Dec 28, 2025

/ok to test 7b6bb2c

@ko3n1g ko3n1g added this to the Core 0.16 milestone Dec 28, 2025
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Thank you for your contribution!

NVIDIA Megatron-LM is currently transitioning to development on Github. We will aim to review your PR after we complete our transition and stabilize our Github development process.

Thank you for your understanding.

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tdene commented Dec 28, 2025

@kanz-nv Would it be a good idea to split up this PR into two halves, the first one focusing on the kv_cache.py refactor, including things such as splitting up of the num_attention_heads parameter; the second one focusing on introducing new AttnBackend for FlashInfer?

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@mathemakitten This will likely have significant perf implications, could you help us run RL benchmarks in addition to standalone inference tests so we avoid regressions?

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5 participants