### What this PR does / why we need it?
Fix#3891.
The empty of `moe_comm_method` in the above issue is due to the wrong
check for MoE models. To be specific, the method `is_moe_model` only
checks whether a text-only model is a MoE model, without considering
multi-modal models, e.g., `VL` and `Omni`.
Check the config dict recursively to find if it has a key contains
"expert", without checking the model architecture.
It is worth noting that, we can't verify a model by if it contains
`FusedMoE` module because `is_moe_model` is called somewhere before the model loading, e.g., it's called when updating the ACLGraph config in
platform initialization.
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
---------
Signed-off-by: shen-shanshan <467638484@qq.com>
### What this PR does / why we need it?
Protect the scene where the first problem occurs. The execution should
be interrupted when the video memory application fails, rather than
waiting until an illegal address is accessed.
### Does this PR introduce _any_ user-facing change?
NA
### How was this patch tested?
NA
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
Signed-off-by: leo-pony <nengjunma@outlook.com>
### What this PR does / why we need it?
1、revert TND modify when dcp pcp, which is introduced by
f57bdb09fc
2、deal aclgraph pad border issue
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
Signed-off-by: weiguihua2 <weiguihua2@huawei.com>
### What this PR does / why we need it?
This PR upgrade CANN from 8.2rc1 to 8.3rc1 and remove the CANN version
check logic.
TODO: we notice that UT runs failed with CANN 8.3 image. So the base
image for UT is still 8.2. We'll fix it later.
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
### What this PR does / why we need it?
The current test cases lack end-to-end (e2e) testing for the
deepseek-v2-lite network in ge graph mode.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
---------
Signed-off-by: CodeNine-CJ <chenjian343@huawei.com>
### What this PR does / why we need it?
correct bug to fix the value of max_num_tokens
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
Signed-off-by: zouyida2052 <zouyida2002@gmail.com>
### What this PR does / why we need it?
- Add support for DeepSeek v3.2 in FULL_DECODE_ONLY mode.
- Add unit test for sfa_v1.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
---------
Signed-off-by: 1Fire4 <wangdingyi2@huawei.com>
### What this PR does / why we need it?
In the `update_*attn_params` functions, the
`torch.npu.stream(update_stream)` context manager was previously located
inside the for-loop that updates parameters for each layer. This
resulted in redundant stream initiations for every layer, adding
unnecessary overhead.
This commit refactors the code by moving the stream context manager to
wrap the entire for-loop. This ensures that the update stream is
initiated only once per function call, rather than for each layer. This
change reduces 90us in each decode model.
update stream in every layer:
<img width="1720" height="383" alt="image"
src="https://github.com/user-attachments/assets/70e4cb69-5bc1-4180-a67d-c99132134be6"
/>
remove update stream in every layer:
<img width="1269" height="175" alt="image"
src="https://github.com/user-attachments/assets/0e290edb-b0ce-48fe-b032-1b924ade6ae5"
/>
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
Signed-off-by: wangxiaoxin-sherie <wangxiaoxin7@huawei.com>
Co-authored-by: wangxiaoxin-sherie <wangxiaoxin7@huawei.com>
### What this PR does / why we need it?
Because the previous commit hash was accidentally deleted or
overwritten. This patch correct the commit hash available for
https://github.com/AscendTransport/Mooncake to make nightly ci happy
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
Signed-off-by: wangli <wangli858794774@gmail.com>
### What this PR does / why we need it?
Upgrade torch-npu to the official release version 2.7.1
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
---------
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
### What this PR does / why we need it?
support pcp + mtp (with pd disaggregate, only pcp in P nodes)
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
Signed-off-by: zhangsicheng5 <zhangsicheng5@huawei.com>
### What this PR does / why we need it?
As a validation for #3664, add end-to-end tests to monitor the InternVL
model and ensure its continuous proper operation. This PR is only for
single-card. So the models that have more parameters than 8B like 78B
are needed to test using multi-cards.
### Does this PR introduce _any_ user-facing change?
None.
### How was this patch tested?
`pytest -sv tests/e2e/singlecard/multi-modal/test_internvl.py`
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
---------
Signed-off-by: gcanlin <canlinguosdu@gmail.com>
### What this PR does / why we need it?
This PR temporarily bypasses the scenario where some models in vLLM
trigger a `ValueError` during the process of storing values in
`static_forward_context` when no `prefix` is specified for the linear
layers, which is a bug in some models in vLLM. The official fix will be
addressed by submitting a PR to the vLLM community that specifies a
prefix for the linear layers in each model.
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
Signed-off-by: rjg-lyh <1318825571@qq.com>
### What this PR does / why we need it?
add new test model for aclgraph single_request
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
ut
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
Signed-off-by: lilinsiman <lilinsiman@gmail.com>
### What this PR does / why we need it?
Fix the issue of MTP being enabled and setting
Imhead_tensor_parallel_size=16 causing the inference to hang.
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
Signed-off-by: wyh145 <1987244901@qq.com>
### What this PR does / why we need it?
1. Revert [bugfix for mtp in
fullgraph](0948483642)
and support it when vllm supports
2. raise error when cudagraph_capture_sizes can't be an integer multiple
of uniform_decode_query_len
3. bugfix when max_num_seqs=14 in mtp=2 scenario
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
---------
Signed-off-by: zouyida2052 <zouyida2002@gmail.com>
### What this PR does / why we need it?
add new e2e tests case for aclgraph memory
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
ut
- vLLM version: v0.11.0rc3
- vLLM main:
83f478bb19
Signed-off-by: lilinsiman <lilinsiman@gmail.com>
### What this PR does / why we need it?
cancel tokenize for layerwise_proxy
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
by ci
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
---------
Signed-off-by: wangxiaoteng <wangxiaoteng@huawei.com>
### What this PR does / why we need it?
This patch mainly fix the the problem of not being able to determine the
exit status of the pod's entrypoint script and some other tiny
optimizations:
1. Shorten wait for server timeout
2. fix typo
3. fix the issue of ais_bench failing to correctly access the proxy URL
in a PD separation scenario.
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
---------
Signed-off-by: wangli <wangli858794774@gmail.com>
### What this PR does / why we need it?
Refactored the layerwise code to send to the D node first, preventing
P-node hangs due to communication timeouts when DP > 1.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
By ci
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
---------
Signed-off-by: wangxiaoteng <wangxiaoteng@huawei.com>
Signed-off-by: liziyu <liziyu16@huawei.com>
Co-authored-by: liziyu <liziyu16@huawei.com>
### What this PR does / why we need it?
Fix the precision issue caused by the inconsistency between the group
list type used by mc2 and that of eplb.
- vLLM version: v0.11.0rc3
- vLLM main:
83f478bb19
---------
Signed-off-by: offline0806 <3337230449@qq.com>
### What this PR does / why we need it?
This PR adds MALPO for deepseek aclgraph, we need to test it nightly
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
By running the test
- vLLM version: v0.11.0
- vLLM main:
83f478bb19
---------
Signed-off-by: jiangyunfan1 <jiangyunfan1@h-partners.com>
This is the follow-up PR to PR #3189, which continues to refactor sfa
into mla and finally remove deepseek_v3_2.py. This is the last PR of
deepseek modeling refactoring. After this, all deepseek-related model
codes are removed from vllm_ascend.
FurtherMore, after this PR deepseek v3.2 can run chunk-prefill with
correct accuracy.
- vLLM version: v0.11.0rc3
- vLLM main:
83f478bb19
---------
Signed-off-by: whx-sjtu <2952154980@qq.com>
### What this PR does / why we need it?
1. Refactor the file `mtp_proposer.py`, splits torchair related codes
into `mtp_torchair_proposer.py`
2. According to https://github.com/vllm-project/vllm/pull/24539,
implements padded speculative decoding as described in
https://github.com/vllm-project/vllm/issues/21984.
### Does this PR introduce _any_ user-facing change?
User can use `disable_padded_drafter_batch` to disable/enable padded
speculation, default is `False`.
offline example:
```
speculative_config={"method": "deepseek_mtp", "num_speculative_tokens": 1, "disable_padded_drafter_batch": False}
```
### How was this patch tested?
- [x] egaer with pad/unpad:
- [x] aclgraph with pad/unpad
- [x] torchair with pad/unpad
performance test of deepseek-r1 with tp16、dp1
aclgraph with pad ITL: 168ms
aclgraph with unpad ITL: 169ms
original: 178ms
- vLLM version: v0.11.0rc3
- vLLM main:
83f478bb19
---------
Signed-off-by: xuyexiong <xuyexiong@huawei.com>
We notice that sometimes user build vllm-ascend with incorrect torch
version. In this case, the build is passed, but when running the code,
the error `AttributeError: '_OpNamespace' '_C_ascend' object has no
attribute 'weak_ref_tensor'` is raised. Let's force the torch version to
2.7.1 and check the torch version when build from source to fix the
issue.
closes: #3342
- vLLM version: v0.11.0rc3
- vLLM main:
c9461e05a4
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
### What this PR does / why we need it?
[UT] fix ut test for test_utils that
https://github.com/vllm-project/vllm-ascend/pull/3612 skipped.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
vLLM version: v0.11.0rc3
vLLM main:
17c540a993
- vLLM version: v0.11.0rc3
- vLLM main:
83f478bb19
---------
Signed-off-by: Meihan-chen <jcccx.cmh@gmail.com>
Added instructions for resolving 'invalid tar header' error on Kylin OS with an ARM64 architecture on Atlas300I hardware during docker
pull, including steps for offline loading of docker images.
---
### What this PR does / why we need it?
The primary motivation for this PR is to address a critical `docker
pull` failure that occurs on specific, yet important, enterprise
environments. Specifically, when operating on **Kylin OS (麒麟操作系统) with
an ARM64 architecture on Atlas300I hardware**, users frequently
encounter an `archive/tar: invalid tar header` error, which completely
blocks the setup process. This issue has been consistently reproduced,
with multiple retries failing with the same error, confirming that it is
a persistent environmental problem rather than a transient network
issue.
<img width="2060" height="525" alt="image"
src="https://github.com/user-attachments/assets/6c1c5728-de27-476f-8df4-723564fc290b"
/>
This guide provides a robust, step-by-step workaround using an
offline-loading method (`docker save` on a host machine and `docker
load` on the target machine). This solution is crucial for enabling
users on this platform to use vLLM.
This contribution does not directly fix an existing issue number, but it
proactively solves a significant environmental and usability problem for
a growing user base.
### Does this PR introduce _any_ user-facing change?
No.It does not alter any code, APIs, interfaces, or existing behavior of
the vLLM project.
### How was this patch tested?
The instructions and troubleshooting steps in this guide were validated
through a real-world, end-to-end test case on the my hardware and OS.
The testing process was as follows:
1. **Problem Reproduction**: An attempt was made to directly `docker
pull` the `vllm-ascend:v0.10.0rc1-310p` image on a target machine
running Kylin OS (ARM64). The `invalid tar header` failure was
successfully and consistently reproduced, confirming the existence of
the problem.
2. **Solution Implementation**: The workaround detailed in the guide was
executed:
* On a separate host machine (Ubuntu x86_64), the image was successfully
pulled using the `--platform linux/arm64` flag.
* The image was then saved to a `.tar` archive using `docker save`.
* The `.tar` archive was transferred to the target Kylin OS machine.
* The image was successfully loaded from the archive using `docker load
-i ...`.
3. **End-to-End Validation**: After loading the image, the vLLM
container was launched on the target machine following the instructions
in the guide. Both online inference (via `curl` to the API server) and
offline inference (via the Python script) were executed successfully,
confirming that the entire workflow described in the document is
accurate and effective.
Since this is a documentation-only change based on a validated workflow,
no new unit or integration tests were added to the codebase.
- vLLM version: v0.11.0rc3
- vLLM main:
83f478bb19
---------
Signed-off-by: Liwx <liweixuan1014@gmail.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
### What this PR does / why we need it?
Fix oom of deepseek-eplb nigtly test
- vLLM version: v0.11.0rc3
- vLLM main:
83f478bb19
---------
Signed-off-by: offline0806 <3337230449@qq.com>
Co-authored-by: offline0806 <3337230449@qq.com>
This PR fixes a mlapo accuracy problem related with weight processing.
Furthermore, add back mlapo related e2e test with quantized deepseek
model.
- vLLM version: v0.11.0rc3
- vLLM main:
83f478bb19
Signed-off-by: whx-sjtu <2952154980@qq.com>
### What this PR does / why we need it?
bugfix for mtp fullgraph
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
- vLLM version: v0.11.0rc3
- vLLM main:
83f478bb19
Signed-off-by: zouyida2052 <zouyida2002@gmail.com>
### What this PR does / why we need it?
When using multi connector, the multi connector does not define
get_finished_count, which will cause the kv cache to be released
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.11.0rc3
- vLLM main:
83f478bb19
---------
Signed-off-by: baxingpiaochong <771405853@qq.com>
### What this PR does / why we need it?
fix a typo in mooncake layerwise connector. There is only `requests`,
instead of `request` in `connector_metadata`. This pr fixes this typo
- vLLM version: v0.11.0rc3
- vLLM main:
83f478bb19
Signed-off-by: liziyu <liziyu16@huawei.com>
### What this PR does / why we need it?
Fix eplb nightly tests.
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.11.0rc3
- vLLM main:
83f478bb19
---------
Signed-off-by: offline0806 <3337230449@qq.com>
Co-authored-by: offline0806 <3337230449@qq.com>
### What this PR does / why we need it?
To adapt the torch_npu version to avoid the precision problem of
torchair deepseek. The torch_npu version may result in the different
branches in the ops register, the rms_norm ops has two branches
according to the verson_check, this pr unify the rms_norm in torchair by
patching quant_rms_norm to rms_norm to fix the accuracy issue in torchair scenario
- vLLM version: v0.11.0rc3
- vLLM main:
83f478bb19
Signed-off-by: hust17yixuan <303660421@qq.com>
### What this PR does / why we need it?
This patch optimize nightly CI:
1. Bug fixes ais_bench get None repo_type error
2. Fix A2 install kubectl error with arm arch
3. Fix the multi_node CI unable to determine whether the job was
successful error
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.11.0rc3
- vLLM main:
83f478bb19
---------
Signed-off-by: wangli <wangli858794774@gmail.com>
### What this PR does / why we need it?
the code of vllm is updated, pin vllm commit id to recover CI firstly
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.11.0rc3
- vLLM main:
https://github.com/vllm-project/vllm/commit/releases/v0.11.1
Signed-off-by: Meihan-chen <jcccx.cmh@gmail.com>
### What this PR does / why we need it?
After refactoring vllm_ascend/models and FusedMoE, we are unable to pass
`gate` from deepseekv2.py to `AscendFusedMoE.forward`, which will result
in error when running deepseek v3/r1 with allgather.
Hence, this pr removes `gate` related computations from FusedMoE module
in eager/aclgraph mode.
### Does this PR introduce _any_ user-facing change?
`rm_router_logits` is deprecated in eager/aclgraph.
### How was this patch tested?
e2e & ut
- vLLM version: v0.11.0rc3
- vLLM main:
https://github.com/vllm-project/vllm/commit/releases/v0.11.1
Signed-off-by: Pr0Wh1teGivee <calvin_zhu0210@outlook.com>
### What this PR does / why we need it?
Part of https://github.com/vllm-project/vllm-ascend/pull/3106
Fix Hybrid kvcache sharing bug in same attention type
Change the `shared_by` logic so that the same attention spec could share
the same buffer instead of allocating more hbm.
After this pr, kvcache memory saved 50% in qwen3-next compared with
before (`self_attn:linear_attn=1:3` in an `attn_group`), and
`gpu_memory_utilization` could increase to `0.8` on Qwen3-Next when
running on A2 64G/card with tp4
<img width="2833" height="1540" alt="image"
src="https://github.com/user-attachments/assets/2a91fa99-fb0f-447c-9e8b-acd587890fbe"
/>
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
Test pass with the latest e2e test case on qwen3-next
- vLLM version: v0.11.0rc3
- vLLM main:
c9461e05a4
---------
Signed-off-by: MengqingCao <cmq0113@163.com>
### What this PR does / why we need it?
force with_prefill true after allreduce in kv producer
- vLLM version: v0.11.0rc3
- vLLM main:
c9461e05a4
---------
Signed-off-by: liziyu <liziyu16@huawei.com>
### What this PR does / why we need it?
We have optimized the performance of long sequences：First,Modify the
input data format for attention calculation. Instead of using the
original BSND format, remove the logic for converting between TND and
BSND, and directly adopt the TND format.
The TND input format can be directly reused, which shortens the data
flow path. Converting to BSND is an unnecessary processing step.Second,
we switched the output update of the concatenated small operators to the
npu_attention_update fusion operator to improve performance.
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.11.0rc3
- vLLM main:
c9461e05a4
---------
Signed-off-by: pichangping <1337510399@qq.com>
### What this PR does / why we need it?
This PR adds 2 more A2 caces which we need to test daily. It also
enhances the logging for aisbench test failures to improve issues
identification
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
By running the test
- vLLM version: v0.11.0rc3
- vLLM main:
https://github.com/vllm-project/vllm/commit/releases/v0.11.1
---------
Signed-off-by: jiangyunfan1 <jiangyunfan1@h-partners.com>
### What this PR does / why we need it?
The current MatmulReduceScatter operator experiences performance
degradation in small-shape scenarios, so it determines whether to use
this operator by judging the size of the shape.
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.11.0rc3
- vLLM main:
https://github.com/vllm-project/vllm/commit/releases/v0.11.1
---------
Signed-off-by: ZYang6263 <zy626375@gmail.com>
