Fix quantize.py script and support packed sequences in pretrain_gpt.py - #3564
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Signed-off-by: Asha Anoosheh <aanoosheh@nvidia.com>
Signed-off-by: Asha Anoosheh <aanoosheh@nvidia.com>
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- Add is_packed_sequence flag (True when args.sft is set) to get_batch and is_dataset_built_on_rank, mirroring pretrain_mamba.py behavior - Middle PP stages with packed sequences return (None×5, PackedSeqParams) carrying cu_seqlens/max_seqlen for attention masking, instead of early- returning None×6 - Import PackedSeqParams from megatron.core.packed_seq_params - is_dataset_built_on_rank: packed sequences build dataset on all TP rank-0 stages (not just first/last PP), consistent with THD format requirements - Add detailed docstring explaining packed sequence flow and differences from pretrain_mamba.py (return format, middle-stage handling, CP, MTP) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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cu_seqlens_q_padded may not be strictly monotonic when context parallelism slices sequences across ranks, or when padded cumulative lengths exceed total_tokens. The diff can go negative, causing torch.repeat_interleave to fail with "repeats can not be negative". Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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NVIDIA#3564) Signed-off-by: Asha Anoosheh <aanoosheh@nvidia.com> Co-authored-by: Chenhan Yu <chenhany@nvidia.com> Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> Co-authored-by: Charlie Truong <chtruong@nvidia.com>
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NVIDIA#3564) Signed-off-by: Asha Anoosheh <aanoosheh@nvidia.com> Co-authored-by: Chenhan Yu <chenhany@nvidia.com> Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> Co-authored-by: Charlie Truong <chtruong@nvidia.com> Signed-off-by: yhgalaxy <yhgalaxy@outlook.com>
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NVIDIA#3564) Signed-off-by: Asha Anoosheh <aanoosheh@nvidia.com> Co-authored-by: Chenhan Yu <chenhany@nvidia.com> Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> Co-authored-by: Charlie Truong <chtruong@nvidia.com> Signed-off-by: Jon Barker <jbarker@aws-cmh-slurm-1-vscode-02.cm.cluster>
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NVIDIA#3564) Signed-off-by: Asha Anoosheh <aanoosheh@nvidia.com> Co-authored-by: Chenhan Yu <chenhany@nvidia.com> Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> Co-authored-by: Charlie Truong <chtruong@nvidia.com>
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What does this PR do ?
pretrain_gpt.pyto support packed sequences, bringing it up to par withpretrain_mambaContribution process
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