[2/N][refactor] torchair deepseek mla backend refactor by linfeng-yuan · Pull Request #2459 · vllm-project/vllm-ascend

linfeng-yuan · 2025-08-20T08:40:59Z

What this PR does / why we need it?

This PR move current unified mla backend to torchair folder and remove torchair-related code in attention/mla_v1.py (1.3k -> 0.9k).

Does this PR introduce any user-facing change?

No.

How was this patch tested?

Running eager mode with mla backend, and torchair mode with code before 2445

vLLM version: v0.10.0
vLLM main: vllm-project/vllm@f571ff8

gemini-code-assist

Code Review

This pull request refactors the attention backend selection logic and introduces a new TorchAir MLA backend for DeepSeek models on Ascend NPUs. The refactoring in platform.py correctly handles the selection of different attention backends. The new implementation in vllm_ascend/torchair/torchair_mla.py adds the TorchAir-based MLA backend. I've found a critical issue in the decode path of this new implementation that needs to be addressed.

github-actions · 2025-08-20T09:02:32Z

👋 Hi! Thank you for contributing to the vLLM Ascend project. The following points will speed up your PR merge:‌‌

A PR should do only one thing, smaller PRs enable faster reviews.
Every PR should include unit tests and end-to-end tests ‌to ensure it works and is not broken by other future PRs.
Write the commit message by fulfilling the PR description to help reviewer and future developers understand.

If CI fails, you can run linting and testing checks locally according Contributing and Testing.

codecov · 2025-08-20T17:15:10Z

Codecov Report

❌ Patch coverage is 79.62264% with 216 lines in your changes missing coverage. Please review.
✅ Project coverage is 77.56%. Comparing base (2bb7e55) to head (0b5b5b2).
⚠️ Report is 24 commits behind head on main.

Files with missing lines	Patch %	Lines
vllm_ascend/torchair/torchair_mla.py	61.70%	211 Missing ⚠️
vllm_ascend/attention/mla_v1.py	85.29%	5 Missing ⚠️

❌ Your patch check has failed because the patch coverage (79.62%) is below the target coverage (80.00%). You can increase the patch coverage or adjust the target coverage.

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #2459      +/-   ##
==========================================
+ Coverage   76.18%   77.56%   +1.37%     
==========================================
  Files         120      130      +10     
  Lines       13532    17149    +3617     
==========================================
+ Hits        10310    13302    +2992     
- Misses       3222     3847     +625

Flag	Coverage Δ
unittests	`77.56% <79.62%> (+1.37%)`	⬆️

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github-actions · 2025-08-21T00:57:14Z

This pull request has conflicts, please resolve those before we can evaluate the pull request.

wangxiyuan · 2025-08-21T01:31:56Z

test passed here: https://github.com/vllm-project/vllm-ascend/actions/runs/17105103268?pr=2459

Signed-off-by: linfeng-yuan <1102311262@qq.com>

wangxiyuan · 2025-08-21T06:02:20Z

CI failue doesn't relate to this PR

…2459) ### What this PR does / why we need it? This PR move current unified mla backend to torchair folder and remove torchair-related code in attention/mla_v1.py (1.3k -> 0.9k). ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? Running eager mode with mla backend, and torchair mode with code before [2445](vllm-project#2445) - vLLM version: v0.10.0 - vLLM main: vllm-project/vllm@f571ff8 Signed-off-by: linfeng-yuan <1102311262@qq.com>

- ✅ **Review Quality:** He has completed [50+ reviews](https://github.com/vllm-project/vllm-ascend/pulls?q=is%3Apr+reviewed-by%3Alinfeng-yuan) since April 2025, covering graph mode, MoE, quantization, model support, and performance-related changes. In addition to regular review work, he has also participated in complex feature development and review, such as [#6670](#6670) (MoE MXFP8 quantization), where he helped with A5 MXFP8 integration, compatibility cleanup, dispatch updates, and implementation fixes. - ✅ **Sustained Contributions:** He has [60+ merged PRs](https://github.com/vllm-project/vllm-ascend/pulls?q=is%3Apr+is%3Amerged+author%3Alinfeng-yuan) since April 2025, with continuous activity across major release cycles. - ✅ **Quality Contributions:** **Torchair Graph Mode & Wide-EP / MoE — Feature Owner (2025 Q2~Q4):** He was the Feature Owner for DeepSeek high-throughput inference under torchair graph mode and the Wide-EP project. He drove graph mode performance optimization ([#731](#731)), landed super-kernel fusion for quantized DSR1 ([#3485](#3485)), and added initial MoE support for Model Runner v2 ([#7922](#7922)). **Ascend950 (A5) — Feature Owner:** He authored the [RFC roadmap (#7157)](#7157) for A5 support, landed initial build support ([#7151](#7151)), co-authored MXFP8 and MXFP4 quantization support for A5 ([#6670](#6670), [#7877](#7877)), and fixed the MXFP8 scale normalization issue that unblocked A5 quantized inference ([#7573](#7573)). **DeepSeek Low-Latency & Post-Processing:** He improved DSv3.2 performance by eliminating HD synchronization ([#4805](#4805)), improved rejection sampler performance and eliminated D2H sync in TopKTopPSampler ([#4154](#4154)), and added a penalty-related Triton kernel for sampling performance ([#7794](#7794)). - ✅ **Community Involvement:** He led a 2-part torchair modeling refactor ([#2384](#2384), [#2459](#2459)) and deleted ~2K lines of redundant DeepSeek modeling code as upstream absorbed the changes ([#2849](#2849)). He also replaced scattered business kwargs with typed request objects across MoE stage boundaries ([#7024](#7024)). Since March 2026, he has taken part in issue triage and user support, responding to [30+ issues](https://github.com/vllm-project/vllm-ascend/issues?q=is%3Aissue+commenter%3Alinfeng-yuan+updated%3A%3E2026-03-01) covering graph mode failures, quantization accuracy regressions, MoE deployment problems, and multi-node communication issues. - vLLM version: v0.19.1 - vLLM main: vllm-project/vllm@4d51588 Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>

- ✅ **Review Quality:** He has completed [50+ reviews](https://github.com/vllm-project/vllm-ascend/pulls?q=is%3Apr+reviewed-by%3Alinfeng-yuan) since April 2025, covering graph mode, MoE, quantization, model support, and performance-related changes. In addition to regular review work, he has also participated in complex feature development and review, such as [vllm-project#6670](vllm-project#6670) (MoE MXFP8 quantization), where he helped with A5 MXFP8 integration, compatibility cleanup, dispatch updates, and implementation fixes. - ✅ **Sustained Contributions:** He has [60+ merged PRs](https://github.com/vllm-project/vllm-ascend/pulls?q=is%3Apr+is%3Amerged+author%3Alinfeng-yuan) since April 2025, with continuous activity across major release cycles. - ✅ **Quality Contributions:** **Torchair Graph Mode & Wide-EP / MoE — Feature Owner (2025 Q2~Q4):** He was the Feature Owner for DeepSeek high-throughput inference under torchair graph mode and the Wide-EP project. He drove graph mode performance optimization ([vllm-project#731](vllm-project#731)), landed super-kernel fusion for quantized DSR1 ([vllm-project#3485](vllm-project#3485)), and added initial MoE support for Model Runner v2 ([vllm-project#7922](vllm-project#7922)). **Ascend950 (A5) — Feature Owner:** He authored the [RFC roadmap (vllm-project#7157)](vllm-project#7157) for A5 support, landed initial build support ([vllm-project#7151](vllm-project#7151)), co-authored MXFP8 and MXFP4 quantization support for A5 ([vllm-project#6670](vllm-project#6670), [vllm-project#7877](vllm-project#7877)), and fixed the MXFP8 scale normalization issue that unblocked A5 quantized inference ([vllm-project#7573](vllm-project#7573)). **DeepSeek Low-Latency & Post-Processing:** He improved DSv3.2 performance by eliminating HD synchronization ([vllm-project#4805](vllm-project#4805)), improved rejection sampler performance and eliminated D2H sync in TopKTopPSampler ([vllm-project#4154](vllm-project#4154)), and added a penalty-related Triton kernel for sampling performance ([vllm-project#7794](vllm-project#7794)). - ✅ **Community Involvement:** He led a 2-part torchair modeling refactor ([vllm-project#2384](vllm-project#2384), [vllm-project#2459](vllm-project#2459)) and deleted ~2K lines of redundant DeepSeek modeling code as upstream absorbed the changes ([vllm-project#2849](vllm-project#2849)). He also replaced scattered business kwargs with typed request objects across MoE stage boundaries ([vllm-project#7024](vllm-project#7024)). Since March 2026, he has taken part in issue triage and user support, responding to [30+ issues](https://github.com/vllm-project/vllm-ascend/issues?q=is%3Aissue+commenter%3Alinfeng-yuan+updated%3A%3E2026-03-01) covering graph mode failures, quantization accuracy regressions, MoE deployment problems, and multi-node communication issues. - vLLM version: v0.19.1 - vLLM main: vllm-project/vllm@4d51588 Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com> Signed-off-by: yangzhe-2026 <yangzhe@isrc.iscas.ac.cn>

- ✅ **Review Quality:** He has completed [50+ reviews](https://github.com/vllm-project/vllm-ascend/pulls?q=is%3Apr+reviewed-by%3Alinfeng-yuan) since April 2025, covering graph mode, MoE, quantization, model support, and performance-related changes. In addition to regular review work, he has also participated in complex feature development and review, such as [vllm-project#6670](vllm-project#6670) (MoE MXFP8 quantization), where he helped with A5 MXFP8 integration, compatibility cleanup, dispatch updates, and implementation fixes. - ✅ **Sustained Contributions:** He has [60+ merged PRs](https://github.com/vllm-project/vllm-ascend/pulls?q=is%3Apr+is%3Amerged+author%3Alinfeng-yuan) since April 2025, with continuous activity across major release cycles. - ✅ **Quality Contributions:** **Torchair Graph Mode & Wide-EP / MoE — Feature Owner (2025 Q2~Q4):** He was the Feature Owner for DeepSeek high-throughput inference under torchair graph mode and the Wide-EP project. He drove graph mode performance optimization ([vllm-project#731](vllm-project#731)), landed super-kernel fusion for quantized DSR1 ([vllm-project#3485](vllm-project#3485)), and added initial MoE support for Model Runner v2 ([vllm-project#7922](vllm-project#7922)). **Ascend950 (A5) — Feature Owner:** He authored the [RFC roadmap (vllm-project#7157)](vllm-project#7157) for A5 support, landed initial build support ([vllm-project#7151](vllm-project#7151)), co-authored MXFP8 and MXFP4 quantization support for A5 ([vllm-project#6670](vllm-project#6670), [vllm-project#7877](vllm-project#7877)), and fixed the MXFP8 scale normalization issue that unblocked A5 quantized inference ([vllm-project#7573](vllm-project#7573)). **DeepSeek Low-Latency & Post-Processing:** He improved DSv3.2 performance by eliminating HD synchronization ([vllm-project#4805](vllm-project#4805)), improved rejection sampler performance and eliminated D2H sync in TopKTopPSampler ([vllm-project#4154](vllm-project#4154)), and added a penalty-related Triton kernel for sampling performance ([vllm-project#7794](vllm-project#7794)). - ✅ **Community Involvement:** He led a 2-part torchair modeling refactor ([vllm-project#2384](vllm-project#2384), [vllm-project#2459](vllm-project#2459)) and deleted ~2K lines of redundant DeepSeek modeling code as upstream absorbed the changes ([vllm-project#2849](vllm-project#2849)). He also replaced scattered business kwargs with typed request objects across MoE stage boundaries ([vllm-project#7024](vllm-project#7024)). Since March 2026, he has taken part in issue triage and user support, responding to [30+ issues](https://github.com/vllm-project/vllm-ascend/issues?q=is%3Aissue+commenter%3Alinfeng-yuan+updated%3A%3E2026-03-01) covering graph mode failures, quantization accuracy regressions, MoE deployment problems, and multi-node communication issues. - vLLM version: v0.19.1 - vLLM main: vllm-project/vllm@4d51588 Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>

- ✅ **Review Quality:** He has completed [50+ reviews](https://github.com/vllm-project/vllm-ascend/pulls?q=is%3Apr+reviewed-by%3Alinfeng-yuan) since April 2025, covering graph mode, MoE, quantization, model support, and performance-related changes. In addition to regular review work, he has also participated in complex feature development and review, such as [vllm-project#6670](vllm-project#6670) (MoE MXFP8 quantization), where he helped with A5 MXFP8 integration, compatibility cleanup, dispatch updates, and implementation fixes. - ✅ **Sustained Contributions:** He has [60+ merged PRs](https://github.com/vllm-project/vllm-ascend/pulls?q=is%3Apr+is%3Amerged+author%3Alinfeng-yuan) since April 2025, with continuous activity across major release cycles. - ✅ **Quality Contributions:** **Torchair Graph Mode & Wide-EP / MoE — Feature Owner (2025 Q2~Q4):** He was the Feature Owner for DeepSeek high-throughput inference under torchair graph mode and the Wide-EP project. He drove graph mode performance optimization ([vllm-project#731](vllm-project#731)), landed super-kernel fusion for quantized DSR1 ([vllm-project#3485](vllm-project#3485)), and added initial MoE support for Model Runner v2 ([vllm-project#7922](vllm-project#7922)). **Ascend950 (A5) — Feature Owner:** He authored the [RFC roadmap (vllm-project#7157)](vllm-project#7157) for A5 support, landed initial build support ([vllm-project#7151](vllm-project#7151)), co-authored MXFP8 and MXFP4 quantization support for A5 ([vllm-project#6670](vllm-project#6670), [vllm-project#7877](vllm-project#7877)), and fixed the MXFP8 scale normalization issue that unblocked A5 quantized inference ([vllm-project#7573](vllm-project#7573)). **DeepSeek Low-Latency & Post-Processing:** He improved DSv3.2 performance by eliminating HD synchronization ([vllm-project#4805](vllm-project#4805)), improved rejection sampler performance and eliminated D2H sync in TopKTopPSampler ([vllm-project#4154](vllm-project#4154)), and added a penalty-related Triton kernel for sampling performance ([vllm-project#7794](vllm-project#7794)). - ✅ **Community Involvement:** He led a 2-part torchair modeling refactor ([vllm-project#2384](vllm-project#2384), [vllm-project#2459](vllm-project#2459)) and deleted ~2K lines of redundant DeepSeek modeling code as upstream absorbed the changes ([vllm-project#2849](vllm-project#2849)). He also replaced scattered business kwargs with typed request objects across MoE stage boundaries ([vllm-project#7024](vllm-project#7024)). Since March 2026, he has taken part in issue triage and user support, responding to [30+ issues](https://github.com/vllm-project/vllm-ascend/issues?q=is%3Aissue+commenter%3Alinfeng-yuan+updated%3A%3E2026-03-01) covering graph mode failures, quantization accuracy regressions, MoE deployment problems, and multi-node communication issues. - vLLM version: v0.19.1 - vLLM main: vllm-project/vllm@4d51588 Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com> Signed-off-by: zhuqi <z00480217@china.huawei.com>

- ✅ **Review Quality:** He has completed [50+ reviews](https://github.com/vllm-project/vllm-ascend/pulls?q=is%3Apr+reviewed-by%3Alinfeng-yuan) since April 2025, covering graph mode, MoE, quantization, model support, and performance-related changes. In addition to regular review work, he has also participated in complex feature development and review, such as [vllm-project#6670](vllm-project#6670) (MoE MXFP8 quantization), where he helped with A5 MXFP8 integration, compatibility cleanup, dispatch updates, and implementation fixes. - ✅ **Sustained Contributions:** He has [60+ merged PRs](https://github.com/vllm-project/vllm-ascend/pulls?q=is%3Apr+is%3Amerged+author%3Alinfeng-yuan) since April 2025, with continuous activity across major release cycles. - ✅ **Quality Contributions:** **Torchair Graph Mode & Wide-EP / MoE — Feature Owner (2025 Q2~Q4):** He was the Feature Owner for DeepSeek high-throughput inference under torchair graph mode and the Wide-EP project. He drove graph mode performance optimization ([vllm-project#731](vllm-project#731)), landed super-kernel fusion for quantized DSR1 ([vllm-project#3485](vllm-project#3485)), and added initial MoE support for Model Runner v2 ([vllm-project#7922](vllm-project#7922)). **Ascend950 (A5) — Feature Owner:** He authored the [RFC roadmap (vllm-project#7157)](vllm-project#7157) for A5 support, landed initial build support ([vllm-project#7151](vllm-project#7151)), co-authored MXFP8 and MXFP4 quantization support for A5 ([vllm-project#6670](vllm-project#6670), [vllm-project#7877](vllm-project#7877)), and fixed the MXFP8 scale normalization issue that unblocked A5 quantized inference ([vllm-project#7573](vllm-project#7573)). **DeepSeek Low-Latency & Post-Processing:** He improved DSv3.2 performance by eliminating HD synchronization ([vllm-project#4805](vllm-project#4805)), improved rejection sampler performance and eliminated D2H sync in TopKTopPSampler ([vllm-project#4154](vllm-project#4154)), and added a penalty-related Triton kernel for sampling performance ([vllm-project#7794](vllm-project#7794)). - ✅ **Community Involvement:** He led a 2-part torchair modeling refactor ([vllm-project#2384](vllm-project#2384), [vllm-project#2459](vllm-project#2459)) and deleted ~2K lines of redundant DeepSeek modeling code as upstream absorbed the changes ([vllm-project#2849](vllm-project#2849)). He also replaced scattered business kwargs with typed request objects across MoE stage boundaries ([vllm-project#7024](vllm-project#7024)). Since March 2026, he has taken part in issue triage and user support, responding to [30+ issues](https://github.com/vllm-project/vllm-ascend/issues?q=is%3Aissue+commenter%3Alinfeng-yuan+updated%3A%3E2026-03-01) covering graph mode failures, quantization accuracy regressions, MoE deployment problems, and multi-node communication issues. - vLLM version: v0.19.1 - vLLM main: vllm-project/vllm@4d51588 Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com> Signed-off-by: zhuqi <z00480217@china.huawei.com> Signed-off-by: ZhuQi-seu <zhuqi12@huawei.com>

- ✅ **Review Quality:** He has completed [50+ reviews](https://github.com/vllm-project/vllm-ascend/pulls?q=is%3Apr+reviewed-by%3Alinfeng-yuan) since April 2025, covering graph mode, MoE, quantization, model support, and performance-related changes. In addition to regular review work, he has also participated in complex feature development and review, such as [vllm-project#6670](vllm-project#6670) (MoE MXFP8 quantization), where he helped with A5 MXFP8 integration, compatibility cleanup, dispatch updates, and implementation fixes. - ✅ **Sustained Contributions:** He has [60+ merged PRs](https://github.com/vllm-project/vllm-ascend/pulls?q=is%3Apr+is%3Amerged+author%3Alinfeng-yuan) since April 2025, with continuous activity across major release cycles. - ✅ **Quality Contributions:** **Torchair Graph Mode & Wide-EP / MoE — Feature Owner (2025 Q2~Q4):** He was the Feature Owner for DeepSeek high-throughput inference under torchair graph mode and the Wide-EP project. He drove graph mode performance optimization ([vllm-project#731](vllm-project#731)), landed super-kernel fusion for quantized DSR1 ([vllm-project#3485](vllm-project#3485)), and added initial MoE support for Model Runner v2 ([vllm-project#7922](vllm-project#7922)). **Ascend950 (A5) — Feature Owner:** He authored the [RFC roadmap (vllm-project#7157)](vllm-project#7157) for A5 support, landed initial build support ([vllm-project#7151](vllm-project#7151)), co-authored MXFP8 and MXFP4 quantization support for A5 ([vllm-project#6670](vllm-project#6670), [vllm-project#7877](vllm-project#7877)), and fixed the MXFP8 scale normalization issue that unblocked A5 quantized inference ([vllm-project#7573](vllm-project#7573)). **DeepSeek Low-Latency & Post-Processing:** He improved DSv3.2 performance by eliminating HD synchronization ([vllm-project#4805](vllm-project#4805)), improved rejection sampler performance and eliminated D2H sync in TopKTopPSampler ([vllm-project#4154](vllm-project#4154)), and added a penalty-related Triton kernel for sampling performance ([vllm-project#7794](vllm-project#7794)). - ✅ **Community Involvement:** He led a 2-part torchair modeling refactor ([vllm-project#2384](vllm-project#2384), [vllm-project#2459](vllm-project#2459)) and deleted ~2K lines of redundant DeepSeek modeling code as upstream absorbed the changes ([vllm-project#2849](vllm-project#2849)). He also replaced scattered business kwargs with typed request objects across MoE stage boundaries ([vllm-project#7024](vllm-project#7024)). Since March 2026, he has taken part in issue triage and user support, responding to [30+ issues](https://github.com/vllm-project/vllm-ascend/issues?q=is%3Aissue+commenter%3Alinfeng-yuan+updated%3A%3E2026-03-01) covering graph mode failures, quantization accuracy regressions, MoE deployment problems, and multi-node communication issues. - vLLM version: v0.19.1 - vLLM main: vllm-project/vllm@4d51588 Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com> Signed-off-by: ZhuQi-seu <zhuqi12@huawei.com>

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[2/N][refactor] torchair deepseek mla backend refactor

d8671e8

Signed-off-by: linfeng-yuan <1102311262@qq.com>

linfeng-yuan force-pushed the torchair_deepseek_modeling_refactore_01 branch from 2d4e437 to d8671e8 Compare August 21, 2025 04:51

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wangxiyuan merged commit 0ca3f48 into vllm-project:main Aug 21, 2025
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[Bug]: Remove outofdate commits to improve perf test #3051

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[Community] Nominate new maintainer @linfeng-yuan #8996

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[2/N][refactor] torchair deepseek mla backend refactor#2459

[2/N][refactor] torchair deepseek mla backend refactor#2459
wangxiyuan merged 1 commit into
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