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@BBuf BBuf commented Jun 28, 2025

Motivation

I use flashinfer 27060628c32e1217e27564adf24e33273f4c8287 commit to test.

In b200:

Acc:

图片

main:

图片

pr:

图片

13.5us->8.7us.

end2end benchmark

python3 -m sglang.launch_server --model-path /dev/shm/DeepSeek-R1-FP4 --trust-remote-code --quantization modelopt_fp4 --tp 8 --enable-flashinfer-moe --speculative-algorithm=EAGLE --enable-flashinfer-allreduce-fusion

Refer to trt-llm , I change max_token_num to 1024 and get a better result:

  sglang python3 test/srt/parse_results.py dsv3_main.jsonl

Saved summary to: dsv3_main_summary.csv

+----+-------------------+--------------------+---------------------+----------------+------------------+---------------+----------------+------------------+---------------+-----------------------+
|    |   max_concurrency |   input_throughput |   output_throughput |   mean_ttft_ms |   median_ttft_ms |   p99_ttft_ms |   mean_tpot_ms |   median_tpot_ms |   p99_tpot_ms |   per_user_throughput |
+====+===================+====================+=====================+================+==================+===============+================+==================+===============+=======================+
|  0 |             1.000 |            133.166 |             133.166 |        176.653 |          153.561 |       226.394 |          7.337 |            7.599 |         8.060 |               133.166 |
+----+-------------------+--------------------+---------------------+----------------+------------------+---------------+----------------+------------------+---------------+-----------------------+
|  1 |             4.000 |            390.269 |             390.269 |        254.178 |          207.857 |       646.446 |          9.880 |            9.689 |        11.796 |                97.567 |
+----+-------------------+--------------------+---------------------+----------------+------------------+---------------+----------------+------------------+---------------+-----------------------+
|  2 |            16.000 |           1018.889 |            1018.889 |        275.613 |          179.920 |       643.978 |         14.551 |           14.247 |        20.015 |                63.681 |
+----+-------------------+--------------------+---------------------+----------------+------------------+---------------+----------------+------------------+---------------+-----------------------+
➜  sglang python3 test/srt/parse_results.py dsv3_pr.jsonl  

Saved summary to: dsv3_pr_summary.csv

+----+-------------------+--------------------+---------------------+----------------+------------------+---------------+----------------+------------------+---------------+-----------------------+
|    |   max_concurrency |   input_throughput |   output_throughput |   mean_ttft_ms |   median_ttft_ms |   p99_ttft_ms |   mean_tpot_ms |   median_tpot_ms |   p99_tpot_ms |   per_user_throughput |
+====+===================+====================+=====================+================+==================+===============+================+==================+===============+=======================+
|  0 |             1.000 |            137.713 |             137.713 |        167.537 |          153.134 |       219.778 |          7.098 |            6.992 |         7.747 |               137.713 |
+----+-------------------+--------------------+---------------------+----------------+------------------+---------------+----------------+------------------+---------------+-----------------------+
|  1 |             4.000 |            409.847 |             409.847 |        208.332 |          156.417 |       537.090 |          9.388 |            9.090 |        11.284 |               102.462 |
+----+-------------------+--------------------+---------------------+----------------+------------------+---------------+----------------+------------------+---------------+-----------------------+
|  2 |            16.000 |           1055.758 |            1055.758 |        269.626 |          164.852 |       643.074 |         13.910 |           13.589 |        18.392 |                65.985 |
+----+-------------------+--------------------+---------------------+----------------+------------------+---------------+----------------+------------------+---------------+-----------------------+

bs=1, 3.4%+
bs=8, 5%+
bs=16, 3.6+%

Modifications

Checklist

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Summary of Changes

Hello @BBuf, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request focuses on optimizing the performance of distributed inference by integrating a fused allreduce and RMS normalization kernel. By leveraging the FlashInfer library, it aims to reduce latency for these common operations, particularly beneficial in multi-GPU environments for large language models.

Highlights

  • Performance Optimization: Introduced a new fused kernel for allreduce and RMSNorm operations, leveraging the FlashInfer library to improve performance in Tensor Parallelism setups, as demonstrated by a reported latency reduction from 13.5us to 8.7us.
  • FlashInfer Integration: Added a new module (flashinfer_fusion.py) to manage FlashInfer workspace and expose the fused allreduce_add_rmsnorm function, which utilizes FlashInfer's trtllm_allreduce_fusion API.
  • Conditional Execution: Modified the communicator and layernorm modules to conditionally utilize the new fused operation when FlashInfer is available and a multi-GPU environment is detected, falling back to existing implementations otherwise.
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Code Review

This pull request introduces a performance optimization by leveraging a fused all-reduce and RMS norm kernel from FlashInfer. The changes are well-structured, with a new flashinfer_fusion.py module to handle the integration and workspace management, and modifications in communicator.py and layernorm.py to enable this new path. The implementation looks promising, but a critical correctness issue in the fallback logic and a high-severity issue related to workspace management have been identified. Once these issues are addressed, this will be a great addition to improve performance.

Comment on lines 189 to 190

return self.forward(x, residual)
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critical

The fallback logic in forward_with_allreduce_fusion skips the tensor_model_parallel_all_reduce operation when the fused kernel is not available, leading to incorrect results in multi-GPU environments. The all-reduce operation must be performed before applying the layer norm to maintain correctness.

        if is_flashinfer_available() and residual is not None:
            from sglang.srt.layers.flashinfer_fusion import flashinfer_allreduce_add_rmsnorm
            from sglang.srt.distributed import get_tensor_model_parallel_world_size, tensor_model_parallel_all_reduce
            
            # Only use fusion operation in multi-GPU environment
            if get_tensor_model_parallel_world_size() > 1:
                fused_result = flashinfer_allreduce_add_rmsnorm(
                    input_tensor=x,
                    residual=residual,
                    weight=self.weight,
                    eps=self.variance_epsilon,
                )
                if fused_result[0] is not None:
                    return fused_result
        x = tensor_model_parallel_all_reduce(x)
        return self.forward(x, residual)

Comment on lines 120 to 122
if (not _workspace_manager.initialized or
_workspace_manager.world_size != world_size):
_workspace_manager.initialize(
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high

The condition to check if the workspace needs re-initialization should also include a check for max_token_num and hidden_dim to ensure the workspace is re-initialized if these values change. If these parameters change without re-initialization, it could lead to memory corruption or crashes.

    if (not _workspace_manager.initialized or 
            _workspace_manager.world_size != world_size or
            _workspace_manager.max_token_num != max_token_num or
            _workspace_manager.hidden_dim != hidden_dim):

Comment on lines 400 to 404
if hasattr(layernorm, 'forward_with_allreduce_fusion'):
hidden_states, residual = layernorm.forward_with_allreduce_fusion(hidden_states, residual)
else:
hidden_states = tensor_model_parallel_all_reduce(hidden_states)
hidden_states, residual = layernorm(hidden_states, residual)
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medium

Consider using getattr with a default value to avoid checking for the attribute forward_with_allreduce_fusion before accessing it. This can simplify the code and make it more readable.

hidden_states, residual = getattr(layernorm, 'forward_with_allreduce_fusion', layernorm)(hidden_states, residual)

Comment on lines 90 to 101
if self.initialized and self.ipc_handles is not None:
try:
_flashinfer_comm.trtllm_destroy_ipc_workspace_for_all_reduce(
self.ipc_handles,
group=dist.group.WORLD
)
except Exception as e:
logger.warning(f"Failed to cleanup FlashInfer workspace: {e}")
finally:
self.workspace_tensor = None
self.ipc_handles = None
self.initialized = False
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medium

Consider adding a check to ensure self.initialized is False before attempting to clean up the workspace. This could prevent potential issues if cleanup is called multiple times without a corresponding initialize call.

        if self.initialized and self.ipc_handles is not None:
            if not self.initialized:
                return
            try:

@BBuf BBuf requested review from hnyls2002 and ByronHsu as code owners June 28, 2025 17:13
@BBuf BBuf requested a review from xiezhq-hermann as a code owner June 30, 2025 16:05
@BBuf
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BBuf commented Jun 30, 2025

Refer to trt-llm , I change max_token_num to 1024 and get a better result:

  sglang python3 test/srt/parse_results.py dsv3_main.jsonl

Saved summary to: dsv3_main_summary.csv

+----+-------------------+--------------------+---------------------+----------------+------------------+---------------+----------------+------------------+---------------+-----------------------+
|    |   max_concurrency |   input_throughput |   output_throughput |   mean_ttft_ms |   median_ttft_ms |   p99_ttft_ms |   mean_tpot_ms |   median_tpot_ms |   p99_tpot_ms |   per_user_throughput |
+====+===================+====================+=====================+================+==================+===============+================+==================+===============+=======================+
|  0 |             1.000 |            133.166 |             133.166 |        176.653 |          153.561 |       226.394 |          7.337 |            7.599 |         8.060 |               133.166 |
+----+-------------------+--------------------+---------------------+----------------+------------------+---------------+----------------+------------------+---------------+-----------------------+
|  1 |             4.000 |            390.269 |             390.269 |        254.178 |          207.857 |       646.446 |          9.880 |            9.689 |        11.796 |                97.567 |
+----+-------------------+--------------------+---------------------+----------------+------------------+---------------+----------------+------------------+---------------+-----------------------+
|  2 |            16.000 |           1018.889 |            1018.889 |        275.613 |          179.920 |       643.978 |         14.551 |           14.247 |        20.015 |                63.681 |
+----+-------------------+--------------------+---------------------+----------------+------------------+---------------+----------------+------------------+---------------+-----------------------+
➜  sglang python3 test/srt/parse_results.py dsv3_pr.jsonl  

Saved summary to: dsv3_pr_summary.csv

+----+-------------------+--------------------+---------------------+----------------+------------------+---------------+----------------+------------------+---------------+-----------------------+
|    |   max_concurrency |   input_throughput |   output_throughput |   mean_ttft_ms |   median_ttft_ms |   p99_ttft_ms |   mean_tpot_ms |   median_tpot_ms |   p99_tpot_ms |   per_user_throughput |
+====+===================+====================+=====================+================+==================+===============+================+==================+===============+=======================+
|  0 |             1.000 |            137.713 |             137.713 |        167.537 |          153.134 |       219.778 |          7.098 |            6.992 |         7.747 |               137.713 |
+----+-------------------+--------------------+---------------------+----------------+------------------+---------------+----------------+------------------+---------------+-----------------------+
|  1 |             4.000 |            409.847 |             409.847 |        208.332 |          156.417 |       537.090 |          9.388 |            9.090 |        11.284 |               102.462 |
+----+-------------------+--------------------+---------------------+----------------+------------------+---------------+----------------+------------------+---------------+-----------------------+
|  2 |            16.000 |           1055.758 |            1055.758 |        269.626 |          164.852 |       643.074 |         13.910 |           13.589 |        18.392 |                65.985 |
+----+-------------------+--------------------+---------------------+----------------+------------------+---------------+----------------+------------------+---------------+-----------------------+

bs=1, 3.4%+
bs=8, 5%+
bs=16, 3.6+%

and is_flashinfer_available()
and hasattr(layernorm, "forward_with_allreduce_fusion")
and global_server_args_dict["enable_flashinfer_allreduce_fusion"]
and hidden_states.shape[0] <= 1024
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hidden_state.numel() * hidden_state.element_size() < THRESHOLD

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Make sense, I'll update it.

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I think this feature could also be applied to other models. However, since different models may have varying hidden_size values, directly checking max_token_num seems more general. Regarding the token number 1024: This value was estimated based on the workspace threshold in trt_llm, using ds-v3's hidden_size as a reference. With 1024 tokens, it only allocates an additional ~10MB buffer, so the memory overhead is minimal.

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Hi,

I think the max_workspace settings in trt-llm are not for these flashinfer kernels (allreduce_fusion_xxx).

The max_token_number should be set as the actual max token number.
The default value of use_oneshot should be False. In these two cases it could be set as True. (https://github.com/NVIDIA/TensorRT-LLM/blob/a1235ee9781050e562bbce2c86f714c38d434dbe/cpp/tensorrt_llm/thop/allreduceOp.cpp#L416-L429)

yzh119 pushed a commit to flashinfer-ai/flashinfer that referenced this pull request Jun 30, 2025
<!-- .github/pull_request_template.md -->

## 📌 Description

ref sgl-project/sglang#7621

<!-- What does this PR do? Briefly describe the changes and why they’re
needed. -->

## 🔍 Related Issues

<!-- Link any related issues here -->

## 🚀 Pull Request Checklist

Thank you for contributing to FlashInfer! Before we review your pull
request, please make sure the following items are complete.

### ✅ Pre-commit Checks

- [x] I have installed `pre-commit` by running `pip install pre-commit`
(or used your preferred method).
- [x] I have installed the hooks with `pre-commit install`.
- [x] I have run the hooks manually with `pre-commit run --all-files`
and fixed any reported issues.

> If you are unsure about how to set up `pre-commit`, see [the
pre-commit documentation](https://pre-commit.com/).

## 🧪 Tests

- [x] Tests have been added or updated as needed.
- [x] All tests are passing (`unittest`, etc.).

## Reviewer Notes

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@BBuf BBuf changed the title support trt-llm allreduce fuse rms_norm_add kernel [b200] support trt-llm allreduce fuse rms_norm_add kernel Jul 1, 2025
@zhyncs zhyncs merged commit 8e64140 into main Jul 3, 2025
48 of 56 checks passed
@zhyncs zhyncs deleted the support_allreduce_rmsnorm_add_fusion branch July 3, 2025 02:36
yzh119 pushed a commit to flashinfer-ai/flashinfer that referenced this pull request Jul 8, 2025
<!-- .github/pull_request_template.md -->

## 📌 Description

<!-- What does this PR do? Briefly describe the changes and why they’re
needed. -->

We add some notes on each api to help integration to vllm/sgl.
And we try to fix the error in issues.

To avoid workspace size overflow, the max lamport communication size
MAX_COMM_SIZE (computed as hidden * max_token) should be less than
round_down(INT_32_MAX, 2MB). For any larger size, it would be rewritten
to this value with a warning "warning: lamport_comm_size 2147483648 is
greater than MAX_COMM_SIZE 2145386496, set to MAX_COMM_SIZE".

If the actual lamport communication size (computed as hidden *
token_num) exceeds this MAX_COMM_SIZE, always set use_oneshot to be
False.
Otherwise, you could set use_oneshot on your preference; and for the
min-latency case, set it to be (token_num <= 128).


## 🔍 Related Issues

#1223 

sgl-project/sglang#7621

## 🚀 Pull Request Checklist

Thank you for contributing to FlashInfer! Before we review your pull
request, please make sure the following items are complete.

### ✅ Pre-commit Checks

- [x] I have installed `pre-commit` by running `pip install pre-commit`
(or used your preferred method).
- [x] I have installed the hooks with `pre-commit install`.
- [x] I have run the hooks manually with `pre-commit run --all-files`
and fixed any reported issues.

> If you are unsure about how to set up `pre-commit`, see [the
pre-commit documentation](https://pre-commit.com/).

## 🧪 Tests

- [x] Tests have been added or updated as needed.
- [x] All tests are passing (`unittest`, etc.).

## Reviewer Notes

<!-- Optional: anything you'd like reviewers to focus on, concerns, etc.
-->

---------

Co-authored-by: averyh <averyh@nvidia.com>
chenxijun1029 pushed a commit to chenxijun1029/sglang that referenced this pull request Jul 17, 2025
pi314ever pushed a commit to pi314ever/sglang that referenced this pull request Jul 17, 2025
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Co-authored-by: kavioyu <kavioyu@tencent.com>

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Signed-off-by: Xinyuan Tong <justinning0323@outlook.com>

* OAI Server Skeleton & Core Utility Endpoints (sgl-project#7179)

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Co-authored-by: wunhuang <wunhuang@amd.com>

* update ci node for xeon (sgl-project#7265)

* feat: mtp support dp-attention (sgl-project#6081)

Co-authored-by: austindeng <austindeng@tencent.com>
Co-authored-by: tianqilin.99 <tianqilin.99@bytedance.com>
Co-authored-by: Qiaolin Yu <liin1211@outlook.com>
Co-authored-by: ch-wan <cwan39@gatech.edu>

* support qwen2 running on ascend npu device (sgl-project#7022)

Co-authored-by: 刁莹煜 <diaoyingyu1@hisilicon.com>

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* Fix AWQ Dequant and Weight Loading of deepseek v2 (sgl-project#6842)

* fix: resolve b200 dsv3 mtp issue (sgl-project#7286)

* ci: Fix test_ebnf_generate_all_optional_function_params (sgl-project#7288)

* fix: only enable flash_attn test on sm80 sm90 (sgl-project#7289)

* [PD] Support get local ip from NIC for PD disaggregation (sgl-project#7237)

Signed-off-by: Shangming Cai <caishangming@linux.alibaba.com>

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Signed-off-by: Shangming Cai <caishangming@linux.alibaba.com>

* Upstreaming hicache bug fixes (sgl-project#7267)

* Update python API of activation, topk, norm and rope and remove vllm dependency (sgl-project#6614)

Co-authored-by: Wu, Chunyuan <chunyuan.wu@intel.com>
Co-authored-by: jianan-gu <jianan.gu@intel.com>
Co-authored-by: sdp <sdp@gnr799219.jf.intel.com>

* Fix hicache benchmark script bug - some sampled input_request is [] (sgl-project#7300)

* chore: change logs from`INFO` to `DEBUG` for dp and add force quit for tokenizer manager (sgl-project#7251)

* update invalid link in doc (sgl-project#7297)

* Fix mini_lb for PD with long output: limit chunk size of decode response (sgl-project#7301)

Signed-off-by: ch-tiger1 <xyz@ch-tech.ip-ddns.com>
Co-authored-by: ch-tiger1 <xyz@ch-tech.ip-ddns.com>

* Fix profiler error when there are idle passes (sgl-project#7003)

* [pd] optimize dockerfile for  pd disaggregation (sgl-project#7319)

Co-authored-by: zhyncs <me@zhyncs.com>

* Merge PDLB (Prefill-Decode Load Balancer) into SGLang Router (sgl-project#7096)

* Add more refactored openai test & in CI (sgl-project#7284)

* fix: resolve blackwell deepep image issue (sgl-project#7331)

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* Multi-Stage Awake: Support Resume and Pause KV Cache and Weights separately (sgl-project#7099)

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* [Refactor] Clean up radix cache related API (sgl-project#7303)

Co-authored-by: Zhiqiang Xie <xiezhq@stanford.edu>

* Put `_normalize_rid` before other normalization in `io_struct` (sgl-project#7363)

* [PD] Transfer hidden states for mtp when disaggregation (sgl-project#7242)

* [Bugfix][PD] Set conclude state before clear when failure happens (sgl-project#7362)

Signed-off-by: Shangming Cai <caishangming@linux.alibaba.com>

* docs: update installation (sgl-project#7366)

* [Docker] optimize dockerfile  remove deepep and blackwell merge it to… (sgl-project#7343)

Co-authored-by: Yineng Zhang <me@zhyncs.com>

* Clean unused import for mimo mtp model (sgl-project#7370)

* [Bugfix]Fix hang bug using dp attention with HiRadixCache (sgl-project#7159)

Signed-off-by: huanglong <huanglong@linux.alibaba.com>

* [Doc] add embedding rerank doc (sgl-project#7364)

* Fix judgment condition for enabling Deepseek V3/R1 shared expert fusion optimization (sgl-project#7371)

* Feat/refactor embedding server (sgl-project#7322)

* Purge VerlEngine (sgl-project#7326)

Signed-off-by: Ata Fatahi <immrata@gmail.com>

* support return logprobs for pipeline (sgl-project#7356)

Co-authored-by: Zhang Kaihong <zhangkaihong.zkh@alibaba-inc.com>

* [PD] Optimize custom mem pool usage and bump mooncake version (sgl-project#7393)

Signed-off-by: Shangming Cai <caishangming@linux.alibaba.com>

* Support THUDM/GLM-4-0414 (GLM-Z1) Glm4ForCausalLM architecture. (sgl-project#5485)

* Refine OpenAI serving entrypoint to remove batch requests (sgl-project#7372)

Signed-off-by: Xinyuan Tong <justinning0323@outlook.com>
Co-authored-by: Chang Su <csu272@usc.edu>

* [Feature] Comprehensive Hybrid Parallelism Support (sgl-project#6389)

* [DeepSeekNextN] fix: residual of head norm can be None (sgl-project#7398)

* [OAI refactor] Add rerank and score serving (sgl-project#7399)

Co-authored-by: Chang Su <chang.s.su@oracle.com>

* [OAI Server Refactor] [ChatCompletions & Completions] Implement UsageInfo Processor (sgl-project#7360)

Co-authored-by: Chang Su <chang.s.su@oracle.com>

* Fix All-Gather under world size one (sgl-project#7219)

* Optimize DP attn scheduling for speculative decoding (sgl-project#7285)

* Update usage_processor.py (sgl-project#7402)

* Fix 7285 Merge Conflicts (sgl-project#7403)

* chore: upgrade mooncake-transfer-engine 0.3.4 (sgl-project#7401)

* [OAI Server Refactor] [ChatCompletions & Completions] Support Return Hidden State (sgl-project#7329)

Signed-off-by: keru <rukeyang@gmail.com>

* Remove batches api in docs & example (sgl-project#7400)

* [BugFix]: fix EmbeddingReqInput single input error (sgl-project#7396)

* [BugFix]fix qwen25 invoke function call streaming responses with curly braces as the starting indicator (sgl-project#7394)

* fix overlap pagecount (sgl-project#6984)

Co-authored-by: Zhiqiang Xie <xiezhq@stanford.edu>

* fix: Fix CI test_function_call_parser.py (sgl-project#7425)

* Fix CPU offloading for MLA memory pool (sgl-project#7409)

* [fix] PD disaggregation when enable mtp and tp!=dp (sgl-project#7420)

* feat(oai refactor): Replace `openai_api` with `entrypoints/openai`  (sgl-project#7351)

Co-authored-by: Jin Pan <jpan236@wisc.edu>

* Refactor LoRAManager and LoRAMemoryPool state management logic for dynamic LoRA loading support (sgl-project#7412)

* refactor(test): reorganize OpenAI test file structure (sgl-project#7408)

* [minor] simplify the `TokenToKVPoolAllocator` (sgl-project#7414)

* Tiny add logging for GC  (sgl-project#7406)

* FlashInfer NVFP4 MoE with EP & 2-stream shared expert (sgl-project#7327)

Co-authored-by: JieXin Liang <Alcanderian@users.noreply.github.com>
Co-authored-by: alcanderian <alcanderian@gmail.com>

* Remove copy after bmm (sgl-project#7441)

* Fix torch compile run (sgl-project#7391)

Co-authored-by: wunhuang <wunhuang@amd.com>
Co-authored-by: Sai Enduri <saimanas.enduri@amd.com>

* [misc] Add PD service discovery support in router (sgl-project#7361)

* add fused moe config for qwen3 in triton3.3.1 (sgl-project#7445)

* Fix CUDA Graph Check under Deepep with DP FFN (sgl-project#7451)

* Update hyperparameter_tuning.md (sgl-project#7454)

* feat: integrate deepgemm into EPMoE (sgl-project#6821)

Co-authored-by: tianqilin.99 <tianqilin.99@bytedance.com>
Co-authored-by: TianQiLin666666 <1834987979@qq.com>
Co-authored-by: Cheng Wan <54331508+ch-wan@users.noreply.github.com>

* Solve docker build failed in the virtual machine (sgl-project#7290)

Co-authored-by: wunhuang <wunhuang@amd.com>
Co-authored-by: Sai Enduri <saimanas.enduri@amd.com>
Co-authored-by: HAI <hixiao@gmail.com>

* Fix a bug in BatchTokenIDOut & Misc style and dependency updates (sgl-project#7457)

* [CI] Upgrade mooncake to 0.3.4.post1 to fix 8 gpu tests (sgl-project#7472)

Signed-off-by: Shangming Cai <caishangming@linux.alibaba.com>

* Fix prefill OOM due to wrong token calculation when page > 1  (sgl-project#7397)

* feat(func_call): Add more check in `BaseFormatDetector.parse_streaming_increment` (sgl-project#7479)

* Fix dtype for idle input in spec decoding (sgl-project#7456)

* update mooncake in dockerfile (sgl-project#7480)

* kvcache io kernels and test case (sgl-project#7382)

* [perf] slightly imporve DeepSeek-R1-FP4 TP8 (sgl-project#7481)

* Quick fix for DeepGemm requant to also cover MTP. (sgl-project#7378)

* Support weight loading without mmap (sgl-project#7469)

* ci: Revert openai_server related tests in AMD suites (sgl-project#7449)

* Perormance: Enable cuda graph for dp idle batch (sgl-project#7269)

Co-authored-by: austindeng <austindeng@tencent.com>
Co-authored-by: Cheng Wan <54331508+ch-wan@users.noreply.github.com>
Co-authored-by: ch-wan <cwan39@gatech.edu>

* bugfix: Prevent global mutation of conv.stop_str across requests (sgl-project#7347)

Co-authored-by: Chang Su <chang.s.su@oracle.com>

* Fix RequestValidationError response format (sgl-project#7487)

* Fix MTP with Deepseek R1 Fp4 (sgl-project#7376)

* chore: bump sgl-kernel v0.2.0 (sgl-project#7490)

* chore: bump v0.4.8 (sgl-project#7493)

* [AMD] add aiter fused moe in DeepEP path (sgl-project#7268)

* enable aiter_biased_grouped_topk kernel (sgl-project#7423)

* [PD Disaggregation] replace transfer with batch transfer for better performance (sgl-project#7236)

* Remove cumsum_buffer initilization (sgl-project#7439)

* [benchmark] fbgemm benchmark support bandwidth report and support fbgemm_cutlass_gmm (sgl-project#7422)

* Support multi-thread model weight loading (sgl-project#7277)

* [PD] NIXL: Register kv args in advance and cleanup finished requests (sgl-project#6717)

* fix: Add `--model` as an alias for `--model-path` in server_args (sgl-project#7505)

* misc: Improvement to serving_chat.py and add more ut (sgl-project#7489)

* Fuse sorted_token_ids padding to moe_align_block_size kernel (sgl-project#7437)

* [OAI] patch origin request_id logic (sgl-project#7508)

* [PD][Spec] Fix hidden state transfer for spec decode (sgl-project#7516)

Signed-off-by: Shangming Cai <caishangming@linux.alibaba.com>

* EPLB support for MTP (sgl-project#7510)

* clean duplicate code (sgl-project#7512)

* [ci] add router benchmark script and CI (sgl-project#7498)

* fix: force synchronization between TP workers when update_weights (sgl-project#6626)

Co-authored-by: dangkai.dk <dangkai.dk@alibaba-inc.com>

* [CPU] [BF16] Call fused_experts_cpu, weight_packed_linear and bmm_cpu kernel in DeepSeek model (sgl-project#6641)

Co-authored-by: Thien Tran <gau.nernst@yahoo.com.sg>

* [CI] Upgrade mooncake to v0.3.4.post2 to fix potential slice failed bug (sgl-project#7522)

Signed-off-by: Shangming Cai <caishangming@linux.alibaba.com>

* npu fused op (sgl-project#7386)

Co-authored-by: Li Junwen <lijunwen13@hisilicon.com>

* feat: send kvmetrics from sglang scheduler (sgl-project#6721)

* [PD] Add different TP sizes support for no-MLA models (sgl-project#6793)

Co-authored-by: shangmingc <csmthu@gmail.com>
Co-authored-by: Shangming Cai <caishangming@linux.alibaba.com>

* enable aiter fp8 blockscale quant (sgl-project#7520)

* take aiter get_rope back (sgl-project#7521)

* Fix typo of flash_cache (sgl-project#7513)

* feat: add return hidden_states at async generation (sgl-project#7507)

* minor: 'role' must be system/assistant/tool, but case insensitive for now (sgl-project#7499)

* Fix FP8 KV Cache Support in FA3 Backend (sgl-project#7148)

* Fix gathered_buffer issues in tbo (sgl-project#7531)

* [PD] Raise error for incompatible mooncake version and some minor fixes (sgl-project#7527)

Signed-off-by: Shangming Cai <caishangming@linux.alibaba.com>

* [CMake] Fix sgl-kernel CMakeLists for Blackwell (sgl-project#7543)

* Add Tencent HunYuanMoEV1 model support (sgl-project#7549)

* Update seed in CPU UTs to avoid flaky failure with single test (sgl-project#7544)

* chore: improve ci bug reporting (sgl-project#7542)

* chore: remove vlm unnecessary import (sgl-project#7541)

Signed-off-by: Xinyuan Tong <justinning0323@outlook.com>
Co-authored-by: yhyang201 <yhyang201@gmail.com>
Co-authored-by: Mick <mickjagger19@icloud.com>

* chore: bump v0.4.8.post1 (sgl-project#7559)

* [PD][NIXL] Set is_sorted=False to fix NIXL_ERR_NOT_FOUND (sgl-project#7330)

* [Fix] incorrect assert in EPLB (sgl-project#7575)

* Updates Gemma3n MLP layer to adapt latest transformers version (sgl-project#7573)

Signed-off-by: Xinyuan Tong <justinning0323@outlook.com>

* Fix MTP error when enabling two-batch overlap  (sgl-project#7569)

* Add e2e test for multi instance multi stage memory release/resume occupuation (sgl-project#7208)

Signed-off-by: Ata Fatahi <immrata@gmail.com>

* [CI] Add CI Testing for Prefill-Decode Disaggregation with Router (sgl-project#7540)

* Updates transformers and timm dependencies (sgl-project#7577)

Signed-off-by: Xinyuan Tong <justinning0323@outlook.com>

* feat: support compatibility between MTP and two-batch-overlap (sgl-project#7225)

Co-authored-by: Cheng Wan <54331508+ch-wan@users.noreply.github.com>

* Move multimodal processors into a separate folder (sgl-project#7581)

* Fix broken CI TestVILAServer (sgl-project#7610)

* [router] add centralized configuration module for sgl-router (sgl-project#7588)

* Fix: Minicpm (sgl-project#7612)

Signed-off-by: Xinyuan Tong <justinning0323@outlook.com>

* Hybrid kv cache for LLaMA4 (sgl-project#6563)

Co-authored-by: Cheng Wan <54331508+ch-wan@users.noreply.github.com>
Co-authored-by: tarinkk <rt572@physics.rutger.edu>
Co-authored-by: tarinkk <rt572@rutgers.physics.edu>
Co-authored-by: Hanming Lu <69857889+hanming-lu@users.noreply.github.com>

* [CPU] add optimizations for INT8 and FP8 DeepSeek (sgl-project#6769)

Co-authored-by: Zheng, Beilei <beilei.zheng@intel.com>

* Tiny add logs for expert location updater (sgl-project#7308)

* Fix flakiness in LoRA batch test. (sgl-project#7552)

* [BUG] fix local_rank in initialize_dp_attention (sgl-project#7584)

* Support dynamic LoRA loading / unloading in engine/server API (sgl-project#7446)

* [PD] Respect sampling_params.max_new_tokens when PD disaggregation is activated (sgl-project#7598)

Signed-off-by: Shangming Cai <caishangming@linux.alibaba.com>

* fix unit tests (sgl-project#7618)

* Let ep_scatter support arbitrary strides / ue8m0 format (sgl-project#7309)

* Let EP prefill support new DeepGEMM (sgl-project#7310)

* docs: add gb200 nvl72 and a16z grant (sgl-project#7620)

* oai: Adds support for OpenAI chat completions API in bench_serving (sgl-project#7036)

Signed-off-by: Xinyuan Tong <justinning0323@outlook.com>
Co-authored-by: yhyang201 <47235274+yhyang201@users.noreply.github.com>
Co-authored-by: Mick <mickjagger19@icloud.com>

* [bugfix] Remove PR comment posting from Rust benchmark workflow (sgl-project#7625)

* [Minor] clean up multimodal processor and tokenizer manager (sgl-project#7624)

* Add dsv3 fused a gemm to sgl-kernel (sgl-project#7630)

* Add @mickqian as the CODEOWNERS of multimodal (sgl-project#7636)

* Fix stream reasoning parser and Adds Kimi reasoning parser  (sgl-project#7432)

Signed-off-by: Xinyuan Tong <justinning0323@outlook.com>

* Fix sgl-router startup crash (sgl-project#7619)

* [bugfix] fix runtime dropping panic in editable (sgl-project#7628)

* Move files related to EPLB (sgl-project#7580)

* [misc] reduce weird rope_scaling_factor warning (sgl-project#7176)

* [AMD] Add unit-test-sgl-kernel-amd to AMD CI (sgl-project#7539)

* Update CODEOWNERS (sgl-project#7640)

* [EAGLE] remove a wrong adjustment for page_size > 1 & topk > 1 in server_args.py (sgl-project#7643)

* [CPU] add c++ kernel to bind CPU cores and memory node (sgl-project#7524)

* Improve streaming, log_level, memory report, weight loading, and benchmark script (sgl-project#7632)

Co-authored-by: Kan Wu <wukanustc@gmail.com>

* Add dsv3 router gemm kernel (sgl-project#7627)

* chore: upgrade flashinfer v0.2.7 jit (sgl-project#7663)

* [doc] update lws doc for pd (sgl-project#7318)

* Fix: sync prepare_fp8_layer_for_marlin with latest vllm changes (sgl-project#7648)

* Add small requirements for benchmark/parse_result tools (sgl-project#7671)

* [CPU] remove process_group from inputs of shm_allreduce and shm_allgather (sgl-project#7486)

* chore: bump sgl-kernel v0.2.1 (sgl-project#7675)

* support llama4 eagle3  (sgl-project#6985)

Co-authored-by: shuaills <shishuaiuoe@gmail.com>
Co-authored-by: Shenggui Li <somerlee.9@gmail.com>
Co-authored-by: Yingyi Huang <yingyihuang2000@outlook.com>
Co-authored-by: yizhang2077 <1109276519@qq.com>

* Refactor mm processors and Enable mixed modality processing (sgl-project#7629)

Signed-off-by: Xinyuan Tong <justinning0323@outlook.com>

* upgrade sgl kernel to 0.2.1 for main (sgl-project#7676)

* add description for llama4 eagle3 (sgl-project#7688)

* fix(model loader): use safe_open to prevent file handle leaks. (sgl-project#7684)

* chore: upgrade flashinfer v0.2.7.post1 (sgl-project#7698)

* Improve error handling for requests with unloaded LoRA path(s) (sgl-project#7642)

* Apply dsv3_fused_a_gemm kernel (sgl-project#7635)

* Fix GPTQMarlinMoE (sgl-project#7697)

* [1/n] apply wna16marlin kernel in moe weight only quantization (sgl-project#7683)

Co-authored-by: 晟海 <huangtingwei.htw@antgroup.com>
Co-authored-by: yych0745 <1398089567@qq.com>
Co-authored-by: HandH1998 <1335248067@qq.com>
Co-authored-by: 弋云 <yiyun.wyt@antgroup.com>
Co-authored-by: walker-ai <2398833647@qq.com>

* Apply dsv3 router gemm kernel for deepseek-r1 fp4 (sgl-project#7677)

* [AMD] Temporarily disable test_no_overlap_scheduler and test_vision_chunked_prefill (sgl-project#7717)

* [RL] add --skip-warmup (sgl-project#7416)

* [RL] support update_weights_from_distributed with different group and multiple weights (sgl-project#7292)

* [router] add --log-level to sgl-router (sgl-project#6512)

* [b200] support trt-llm allreduce fuse rms_norm_add kernel (sgl-project#7621)

* [CPU] Bind threads and numa node for each TP rank (sgl-project#6549)

Co-authored-by: srinarayan-srikanthan <srinarayan.srikanthan@intel.com>

* Support non-contiguous query input for extend/decode attention (sgl-project#7462)

* Support updating weights at once by stopping all requests (sgl-project#6698)

Signed-off-by: Tianyu Zhou <albert.zty@antgroup.com>
Co-authored-by: Zilin Zhu <zhuzilinallen@gmail.com>

* Fix num_tokens_pre_allocated in disaggregation log (sgl-project#7714)

* [CPU] [sgl-kernel] set dispatch key of initialize to CatchAll (sgl-project#7734)

* [CPU] fix all_reduce and all_gather (sgl-project#6770)

Co-authored-by: blzheng <beilei.zheng@intel.com>

* fix awq and dsv3 fused gemm compatible (sgl-project#7735)

* [CI][Router] Fix bench_one_batch_server for pd router test (sgl-project#7731)

Signed-off-by: Shangming Cai <caishangming@linux.alibaba.com>

* Add CUTLASS FP8 Blockscale MoE kernel for Hopper architecture (sgl-project#7278)

Co-authored-by: HydraQYH <QYH820@Outlook.com>
Co-authored-by: TianQiLin666666 <1834987979@qq.com>

* fix dsv3 fused proj check  (sgl-project#7738)

* Ascend attention backend(PA&MLA) (sgl-project#7722)

Co-authored-by: Maksim <makcum888e@mail.ru>
Co-authored-by: VDV1985 <vladdv85@mail.ru>

* [fix] fix dsv3_router_gemm filter (sgl-project#7750)

* [CPU] refine CPU integration code (sgl-project#7647)

* [CPU] support the case where num_attention_heads or intermediate_size is not divisible by the TP size (sgl-project#6771)

* support qwen3 dense model dp attention (sgl-project#7681)

* [optimize] add two stream norm for qwen3 (sgl-project#7740)

Co-authored-by: ispobock <ispobaoke@gmail.com>

* feat: use D2D instead of H2H in pp (sgl-project#7673)

Co-authored-by: alpha-baby <fujianhao1997@qq.com>

* [Bug] add flashinfer bool check for fusedmoe in Qwen moe models (sgl-project#7723)

* [fix] put cpu in the first priority in get_device() (sgl-project#7752)

* [optimize] fuse renormalize into moe_topk_softmax (sgl-project#7744)

Co-authored-by: ispobock <ispobaoke@gmail.com>

* chore: bump sgl-kernel 0.2.2 (sgl-project#7755)

* fix CI: update native api ipynb (sgl-project#7754)

Signed-off-by: Xinyuan Tong <justinning0323@outlook.com>

* fuse renormal into moe topk softmax kernel python code (sgl-project#7751)

Co-authored-by: ispobock <ispobaoke@gmail.com>
Co-authored-by: zhyncs <me@zhyncs.com>

* Remove type conversion and fix id map in topk (sgl-project#7759)

* Add V2-lite model test (sgl-project#7390)

Co-authored-by: DiweiSun <105627594+DiweiSun@users.noreply.github.com>

* refactor llama4 dp attention logic (sgl-project#7729)

* fix(docs): fix the broken link in `docs/references/production_metrics.md` (sgl-project#7741)

Signed-off-by: rudeigerc <rudeigerc@gmail.com>

* [fix] update bench_speculative.py for compatibility (sgl-project#7764)

Signed-off-by: Kay Yan <kay.yan@daocloud.io>

* Move mem_fraction_static adjustment for multimodal models to `server_args.py` & Fix session control & Other cleanups (sgl-project#7748)

* [RL] Add --nccl-port to prevent port conflict (sgl-project#7418)

* [RL] add pause and continue generation for async rl training (sgl-project#7419)

* [Fix] Alloc return type error (sgl-project#7778)

Signed-off-by: Capronir <839972205@qq.com>

* [feat] Support EAGLE3 for Qwen (sgl-project#7745)

Co-authored-by: 纬杭 <ximing.wxm@antgroup.com>
Co-authored-by: zyksir <zyksir@outlook.com>

* saving hidden_states.clone() (sgl-project#7705)

* [1/n]: add cutlass W4A8 moe kernel for hopper architecture (sgl-project#7772)

Signed-off-by: yangsijia.614 <yangsijia.614@bytedance.com>
Co-authored-by: yicwang <yichen.wang@bytedance.com>

* add model: qwen2-audio (sgl-project#7596)

* Optimize Hopper CUTLASS FP8 Blockwise Grouped GEMM Kernel in Small K Scenario (sgl-project#7782)

* Embedding parallel by attn_tp (sgl-project#7623)

* fix: fix apply_shuffle_mul_sum (sgl-project#7444)

* chore: bump sgl-kernel v0.2.3 (sgl-project#7784)

* fix: use nvidia-nccl-cu12 2.27.5 (sgl-project#7787)

* DP Attention with Auto DeepEP Dispatch (sgl-project#7222)

* chore: upgrade sgl-kernel v0.2.3 (sgl-project#7786)

* Fix incorrect spec_num_draft_tokens in draft_extend (sgl-project#7757)

* [fix] fix misusing of is_cuda (sgl-project#7790)

* Add treemask mode to build_eagle_tree & release sgl-kernel 0.2.3 (sgl-project#7756)

Co-authored-by: Pranjal Shankhdhar <pranjal.ssh@gmail.com>

* chore: bump sgl-kernel v0.2.4 (sgl-project#7800)

* ci: fix port args (sgl-project#7792)

* Fix CI test OOM issue. (sgl-project#7799)

* chore: upgrade sgl-kernel v0.2.4 (sgl-project#7801)

* chore: bump v0.4.9 (sgl-project#7802)

* fix merge conflict issue

* fix hpu attention nonetyep issue

* fix alignment

* fix alignment2

* Ci failure fixes

* fix attention-backend choices

---------

Signed-off-by: Xinyuan Tong <justinning0323@outlook.com>
Signed-off-by: Shangming Cai <caishangming@linux.alibaba.com>
Signed-off-by: ch-tiger1 <xyz@ch-tech.ip-ddns.com>
Signed-off-by: huanglong <huanglong@linux.alibaba.com>
Signed-off-by: Ata Fatahi <immrata@gmail.com>
Signed-off-by: keru <rukeyang@gmail.com>
Signed-off-by: Tianyu Zhou <albert.zty@antgroup.com>
Signed-off-by: rudeigerc <rudeigerc@gmail.com>
Signed-off-by: Kay Yan <kay.yan@daocloud.io>
Signed-off-by: Capronir <839972205@qq.com>
Signed-off-by: yangsijia.614 <yangsijia.614@bytedance.com>
Signed-off-by: Mohit Sinha <msinha@habana.ai>
Co-authored-by: Lianmin Zheng <lianminzheng@gmail.com>
Co-authored-by: KavioYu <67678385+yukavio@users.noreply.github.com>
Co-authored-by: kavioyu <kavioyu@tencent.com>
Co-authored-by: Xinyuan Tong <115166877+JustinTong0323@users.noreply.github.com>
Co-authored-by: yhyang201 <47235274+yhyang201@users.noreply.github.com>
Co-authored-by: kk <43161300+kkHuang-amd@users.noreply.github.com>
Co-authored-by: wunhuang <wunhuang@amd.com>
Co-authored-by: DiweiSun <105627594+DiweiSun@users.noreply.github.com>
Co-authored-by: u4lr451 <u4lr451@gmail.com>
Co-authored-by: austindeng <austindeng@tencent.com>
Co-authored-by: tianqilin.99 <tianqilin.99@bytedance.com>
Co-authored-by: Qiaolin Yu <liin1211@outlook.com>
Co-authored-by: ch-wan <cwan39@gatech.edu>
Co-authored-by: Yijie Zhu <762412795@qq.com>
Co-authored-by: 刁莹煜 <diaoyingyu1@hisilicon.com>
Co-authored-by: Charles Chen <pychen96@gmail.com>
Co-authored-by: Chang Su <chang.s.su@oracle.com>
Co-authored-by: AniZpZ <zhuangsen.zp@antgroup.com>
Co-authored-by: Yineng Zhang <me@zhyncs.com>
Co-authored-by: shangmingc <caishangming@linux.alibaba.com>
Co-authored-by: Zhiqiang Xie <xiezhq@stanford.edu>
Co-authored-by: YanbingJiang <yanbing.jiang@intel.com>
Co-authored-by: Wu, Chunyuan <chunyuan.wu@intel.com>
Co-authored-by: jianan-gu <jianan.gu@intel.com>
Co-authored-by: sdp <sdp@gnr799219.jf.intel.com>
Co-authored-by: Binyao Jiang <byjiang1996@gmail.com>
Co-authored-by: ishandhanani <82981111+ishandhanani@users.noreply.github.com>
Co-authored-by: linzhuo <15313137931lz@gmail.com>
Co-authored-by: ch-tiger1 <tiger@ch-tech.ip-ddns.com>
Co-authored-by: ch-tiger1 <xyz@ch-tech.ip-ddns.com>
Co-authored-by: fzyzcjy <5236035+fzyzcjy@users.noreply.github.com>
Co-authored-by: ybyang <10629930+whybeyoung@users.noreply.github.com>
Co-authored-by: Simo Lin <linsimo.mark@gmail.com>
Co-authored-by: Jinn <47354855+jhinpan@users.noreply.github.com>
Co-authored-by: Stefan He <hebiaobuaa@gmail.com>
Co-authored-by: DarkSharpness <76582120+DarkSharpness@users.noreply.github.com>
Co-authored-by: Atream <80757050+Atream@users.noreply.github.com>
Co-authored-by: Li Hui <lambert80.ios@gmail.com>
Co-authored-by: Huang Long <121648372+LLLL114@users.noreply.github.com>
Co-authored-by: woodx <124784234+woodx9@users.noreply.github.com>
Co-authored-by: Ata Fatahi <immrata@gmail.com>
Co-authored-by: strgrb <zhangkaihong.zkh@antgroup.com>
Co-authored-by: Zhang Kaihong <zhangkaihong.zkh@alibaba-inc.com>
Co-authored-by: Wenbo Yang <solrex@users.noreply.github.com>
Co-authored-by: Chang Su <csu272@usc.edu>
Co-authored-by: Cheng Wan <54331508+ch-wan@users.noreply.github.com>
Co-authored-by: Keyang Ru <rukeyang@gmail.com>
Co-authored-by: ehuaa <ehuamail@163.com>
Co-authored-by: pansicheng <sicheng.pan.chn@gmail.com>
Co-authored-by: Liangsheng Yin <hnyls2002@gmail.com>
Co-authored-by: Jin Pan <jpan236@wisc.edu>
Co-authored-by: Lifu Huang <lifu.hlf@gmail.com>
Co-authored-by: Trevor Morris <tmorris@nvidia.com>
Co-authored-by: JieXin Liang <Alcanderian@users.noreply.github.com>
Co-authored-by: alcanderian <alcanderian@gmail.com>
Co-authored-by: Ke Bao <ISPObaoke@163.com>
Co-authored-by: Sai Enduri <saimanas.enduri@amd.com>
Co-authored-by: Yi Zhang <1109276519@qq.com>
Co-authored-by: xutizhou <xutingz@nvidia.com>
Co-authored-by: TianQiLin666666 <1834987979@qq.com>
Co-authored-by: HAI <hixiao@gmail.com>
Co-authored-by: Yuhong Guo <guoyuhong1985@outlook.com>
Co-authored-by: huangtingwei <141888744+huangtingwei9988@users.noreply.github.com>
Co-authored-by: Alex Sun <alex.s@amd.com>
Co-authored-by: valarLip <103567126+valarLip@users.noreply.github.com>
Co-authored-by: Francis <38564764+ssssnow@users.noreply.github.com>
Co-authored-by: Xiaoyu Zhang <35585791+BBuf@users.noreply.github.com>
Co-authored-by: xianzhiT <xianzhitang@tencent.com>
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Co-authored-by: jay <jthakur@habana.ai>
shuaills pushed a commit to shuaills/sglang that referenced this pull request Jul 21, 2025
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5 participants