Support packed sequences in Gated Delta Net - #85
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Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
…rk#4) Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> Co-authored-by: Yueming Yuan <yym022502@gmail.com>
…adixark#5) Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
- Detach output layer params to prevent MTP gradient flowing to output layer - Add mtp_kwargs interface for flexible MTP label/loss_mask passing - Roll mtp_labels and loss_mask for RL training compatibility Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> Co-authored-by: Yueming Yuan <yym022502@gmail.com>
…yers (radixark#10) - Add is_mtp flag to MoE layers and multi_token_prediction module - Bypass routing replay for MTP layers (MTP uses fresh routing) - Replace rdxa/dev's built-in RouterReplay with miles.utils.routing_replay: - moe_utils.py: use get_routing_replay_compute_topk() wrapper - router.py: use register_routing_replay() for initialization Co-authored-by: Yueming Yuan <yym022502@gmail.com>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> Co-authored-by: Yueming Yuan <yym022502@gmail.com>
After bumping Megatron (rdxa/dev), colocated IPC weight update fails with torch.AcceleratorError: CUDA error: invalid argument during torch.multiprocessing serialization of CUDA tensors. Root cause: Megatron's new TMS hook (PR NVIDIA#3048) alters allocator behavior in training flow, causing allocations via cuMemCreate/cuMemMap which are incompatible with CUDA IPC (_share_cuda_() fails). Fix: resolve mapping.py and dynamic_context.py conflicts to isolate hook side effects so TMS/allocator state remains IPC-compatible during the weight update phase. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- merge(): truncate dp_reshardable padding on optimizer/param_state path - load_parameter_state_from_dp_reshardable: tolerate missing 'padding' key - ShardedTensor: relax flattened_range to deprecation warning Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This PR rebases from radixark Megatron fork [miles-20260218](https://github.com/radixark/Megatron-LM/tree/miles-20260218) and resolve conflicts. Upgrade Megatron from Dec 17 (3714d81) to Feb 13 (1dcf0da) PR link: radixark#13 Co-authored-by: Yueming Yuan <yym022502@gmail.com> Made-with: Cursor
…se `--disable-weight-backuper` in miles (radixark#18) Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: fzyzcjy <5236035+fzyzcjy@users.noreply.github.com>
…adixark#20) Co-authored-by: fzyzcjy <5236035+fzyzcjy@users.noreply.github.com>
Squash merge of the dense true-on-policy Megatron branch. Co-authored-by: zju-stu-lizheng <lizheng.cs@zju.edu.cn> Co-authored-by: zyxiyy02 <282300612+zyxiyy02@users.noreply.github.com> Co-authored-by: Yi Zhang <1109276519@qq.com> Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Co-authored-by: fzyzcjy <5236035+fzyzcjy@users.noreply.github.com>
…xark#58) Co-authored-by: Zhiyao Jiang <jessicajiang324@gmail.com>
…xark#60) Co-authored-by: zyzshishui <82826991+zyzshishui@users.noreply.github.com> Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
…rk#63) Co-authored-by: Zhichenzzz <zczeng@uw.edu>
Co-authored-by: yueming-yuan <yym022502@gmail.com>
…e host memory instead of pinned memory to avoid SegFault on ROCm (radixark#74)
…VIDIA#2645) Signed-off-by: yuzhongw <yuzhongw@nvidia.com> Co-authored-by: kunlunl <kunlunl@nvidia.com> Co-authored-by: Xuesong Ye <xuesongyey@gmail.com> Co-authored-by: Claude <noreply@anthropic.com> Co-authored-by: claude[bot] <209825114+claude[bot]@users.noreply.github.com> Co-authored-by: Daisy Gao <daisyg@nvidia.com>
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Summary
miles-mainMotivation
Qwen3.8-27B varlen training currently reaches the explicit
GDN does not support packed sequence for nowguard. Dense Qwen jobs do not exercise this path, which is why the same B300 stack worked for those models.Testing
ruff checkon all changed filesUpstream implementation: NVIDIA#2645