### What this PR does / why we need it?
Add ut for qwen3_moe.py
### Does this PR introduce _any_ user-facing change?
No.
- vLLM version: v0.10.0
- vLLM main:
18cc33dd60
Signed-off-by: huangxialu <huangxialu1@huawei.com>
### What this PR does / why we need it?
Add ut for files in folder /attention
### Does this PR introduce _any_ user-facing change?
No
- vLLM version: v0.10.0
- vLLM main:
139a7f07bd
---------
Signed-off-by: lwq <liwenquan5@huawei.com>
Co-authored-by: lwq <liwenquan5@huawei.com>
### What this PR does / why we need it?
it'll execute allreduce and malmul seperately in vllm RowParallelLinear
forward funcion, this function use torch_npu.npu_mm_all_reduce_base to
execute allreduce and matmul in a fused kernel way. this will gain a 20%
performance
promotion in eager mode.
### Does this PR introduce _any_ user-facing change?
this PR introduce a new env `VLLM_ASCEND_ENABLE_MATMUL_ALLREDUCE` to
control whether enable the feature or not.
### How was this patch tested?
the patch is tested by adding a new test file `test_patch_linear.py` to
guard the ut
- vLLM version: v0.10.0
- vLLM main:
7728dd77bb
Signed-off-by: Ronald1995 <ronaldautomobile@163.com>
### What this PR does / why we need it?
A refactoring of forward_context and model_runner_v1, add some context
which is necessary in model inference into forward_context, and refactor
dummy_run logic, make it more reasonable.
Some details for this PR:
Add `ascend_forward_context`;
Update mc2_v2 op, and support `active_mask` param;
Update scripts in examples dir;
refactor `dummy_run` logic;
Add soc_version for A2 and A3;
### Does this PR introduce _any_ user-facing change?
No change at user-facing.
### How was this patch tested?
- vLLM version: v0.10.0
- vLLM main:
57c22e57f9
Signed-off-by: zzzzwwjj <1183291235@qq.com>
### What this PR does / why we need it?
Fix num_hidden_layers when Qwen2-Audio 7B and #1760 ：
```
INFO 07-15 04:38:53 [platform.py:174] PIECEWISE compilation enabled on NPU. use_inductor not supported - using only ACL Graph mode
Traceback (most recent call last):
File "/workspace/test1.py", line 58, in <module>
main(audio_count)
File "/workspace/test1.py", line 38, in main
llm = LLM(model="Qwen/Qwen2-Audio-7B-Instruct",
File "/vllm-workspace/vllm/vllm/entrypoints/llm.py", line 271, in __init__
self.llm_engine = LLMEngine.from_engine_args(
File "/vllm-workspace/vllm/vllm/engine/llm_engine.py", line 494, in from_engine_args
vllm_config = engine_args.create_engine_config(usage_context)
File "/vllm-workspace/vllm/vllm/engine/arg_utils.py", line 1286, in create_engine_config
config = VllmConfig(
File "/usr/local/python3.10.17/lib/python3.10/site-packages/pydantic/_internal/_dataclasses.py", line 123, in __init__
s.__pydantic_validator__.validate_python(ArgsKwargs(args, kwargs), self_instance=s)
File "/vllm-workspace/vllm/vllm/config.py", line 4624, in __post_init__
current_platform.check_and_update_config(self)
File "/vllm-workspace/vllm-ascend/vllm_ascend/platform.py", line 180, in check_and_update_config
update_aclgraph_sizes(vllm_config)
File "/vllm-workspace/vllm-ascend/vllm_ascend/utils.py", line 307, in update_aclgraph_sizes
num_hidden_layers = vllm_config.model_config.hf_config.num_hidden_layers
File "/usr/local/python3.10.17/lib/python3.10/site-packages/transformers/configuration_utils.py", line 211, in __getattribute__
return super().__getattribute__(key)
AttributeError: 'Qwen2AudioConfig' object has no attribute 'num_hidden_layers'
```
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
Closes: https://github.com/vllm-project/vllm-ascend/issues/1780https://github.com/vllm-project/vllm-ascend/issues/1760https://github.com/vllm-project/vllm-ascend/issues/1276https://github.com/vllm-project/vllm-ascend/issues/359
- vLLM version: v0.10.0
- vLLM main:
7728dd77bb
Signed-off-by: hfadzxy <starmoon_zhang@163.com>
### What this PR does / why we need it?
- Upgrade to v0.10.0
- Drop v0.9.2 version compatibility
- Add patch for
`vllm_ascend/patch/worker/patch_common/patch_sampler_gather_logprobs.py`
as workaround of
f3a683b7c9
for v0.10.0 and also add e2e test `test_models_prompt_logprobs`
- Pin transformers<4.54.0 as workaround of
https://github.com/vllm-project/vllm-ascend/issues/2034
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
- Test locally:
`VLLM_USE_MODELSCOPE=true pytest -sv
tests/e2e/singlecard/test_offline_inference.py::test_models_prompt_logprobs`
- CI passed
- vLLM version: v0.9.2
- vLLM main:
7728dd77bb
---------
Signed-off-by: Yikun Jiang <yikunkero@gmail.com>
### What this PR does / why we need it?
this pr is to add ut for qwen2_5_vl_without_padding.py
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
this is only a ut test
- vLLM version: v0.9.2
- vLLM main:
9c8b2c2a8a
Signed-off-by: Ronald1995 <ronaldautomobile@163.com>
### What this PR does / why we need it?
Add uts for files in folder /core
### Does this PR introduce _any_ user-facing change?
No
- vLLM version: v0.9.2
- vLLM main:
5a19a6c670
---------
Signed-off-by: lwq <liwenquan5@huawei.com>
Co-authored-by: lwq <liwenquan5@huawei.com>
### What this PR does / why we need it?
Add some uts for files in folder /multistream
### Does this PR introduce _any_ user-facing change?
No
- vLLM version: v0.9.2
- vLLM main:
b77c7d327f
Signed-off-by: lwq <liwenquan5@huawei.com>
Co-authored-by: lwq <liwenquan5@huawei.com>
### What this PR does / why we need it?
Add some ut for files in folder /distributed
### Does this PR introduce _any_ user-facing change?
No
- vLLM version: v0.9.2
- vLLM main:
107111a859
Signed-off-by: lwq <liwenquan5@huawei.com>
Co-authored-by: lwq <liwenquan5@huawei.com>
What this PR does / why we need it?
Add uts for deepseek_v2
Does this PR introduce any user-facing change?
No
How was this patch tested?
- vLLM version: v0.9.2
- vLLM main:
f3137cdd81
---------
Signed-off-by: 张帮政 <zhangbangzheng@huawei.com>
Before do attention module refactor, we can do some code cleanup to make
the next step easier.
What this PR does:
1. remove uesless `common_prefix_len` for attention builder
2. remove uesless `is_only_prefill` and `num_input_tokens` in attention
metadata.
3. remove `CommonAttentionMetadata` and ues `query_start_loc` instead,
`CommonAttentionMetadata` is over designed and uesless
4. update the attention backend input parameters to keep the same as
vLLM.
5. Rename attention name to the same style with `ASCEND` prefix
- vLLM version: v0.9.2
- vLLM main:
107111a859
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
### What this PR does / why we need it?
Add UT for patches in vLLM Ascend
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Irrelevant
- vLLM version: v0.9.2
- vLLM main:
107111a859
Signed-off-by: Pr0Wh1teGivee <calvin_zhu0210@outlook.com>
### What this PR does / why we need it?
Support pipeline parallel with ray backend in V1Engine.
Fixes#1751
### Does this PR introduce _any_ user-facing change?
Users could specify ray as distributed backend when inferencing with pp
### How was this patch tested?
CI passed with new added test.
- vLLM version: v0.9.2
- vLLM main:
32142b3c62
---------
Signed-off-by: MengqingCao <cmq0113@163.com>
What this PR does / why we need it?
According to issue
https://github.com/vllm-project/vllm-ascend/issues/1298 , this pull
request adds unit test code for schedule_config.py.
Does this PR introduce any user-facing change?
No
How was this patch tested?
CI passed with new added/existing test.
- vLLM version: v0.9.2
- vLLM main:
8d0a01a5f2
### What this PR does / why we need it?
Use base test to avoid patch everwhere.
Followup here: https://github.com/vllm-project/vllm-ascend/pull/1566
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
ut ci passed
- vLLM version: v0.9.2
- vLLM main:
8d0a01a5f2
Signed-off-by: Yikun Jiang <yikunkero@gmail.com>
There is a lot torchair specified logic in common code. It results hard
code maintenance. We will create a new torchair module to launch
torchair related logic there. I plan to add 4 PR.
1. Refactor worker
2. Refactor utils (this PR)
- simple change that move all torchair related util function to torchair
module
3. Refactor model_runner
4. Refactor attention
- vLLM version: v0.9.2
- vLLM main:
8188196a1c
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
There is a lot torchair specified logic in common code. It results hard
code maintenance. We will create a new torchair module to launch
torchair related logic there. I plan to add 4 PR.
1. Refactor worker (this PR)
- create torchair module and move torchair related code in worker to the
new module
3. Refactor utils
4. Refactor model_runner
5. Refactor attention
- vLLM version: v0.9.2
- vLLM main:
8188196a1c
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
### What this PR does / why we need it?
Remove ETP/EP maintained in branch main. We drop this as there is no
relevant scenarios to use ETP now, and we may subsequently advocate
implementing expert tensor parallelism in vLLM to support scenarios
where the expert is needed to be sliced
This is a part of #1422 backport.
Fixes https://github.com/vllm-project/vllm-ascend/issues/1396https://github.com/vllm-project/vllm-ascend/issues/1154
### Does this PR introduce _any_ user-facing change?
We'll not maintain etp/ep in vllm-ascend anymore, and use the tp/ep in
vllm instead.
### How was this patch tested?
CI passed with new added and existing test.
- vLLM version: v0.9.2
- vLLM main:
fe8a2c544a
Signed-off-by: MengqingCao <cmq0113@163.com>
vLLM commit
752c6ade2e
removed `blocksparse_params` for attention backend. This PR does the
same change to make CI happy.
- vLLM version: v0.9.2
- vLLM main:
9499e26e2a
---------
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
Signed-off-by: Yikun Jiang <yikunkero@gmail.com>
Co-authored-by: Yikun Jiang <yikunkero@gmail.com>
### What this PR does / why we need it?
maybe fixes
[#1728](https://github.com/vllm-project/vllm-ascend/issues/1728#issuecomment-3065083433)
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Test Qwen3-32B tp=4 with:
```bash
vllm serve --port 1234 Qwen/Qwen3-32B \
--served-model-name Qwen3-32B \
--tensor-parallel-size 4 \
--swap-space 16 \
--max-model-len 6000 \
--load-format dummy \
--disable-log-stats \
--disable-log-requests \
```
Request batch_size=128 input/output token=1024
**In 0.9.2rc1**
```text
=====================================================
Total TPS with prefill(tokens/s) : 785.1395
Total TPS without prefill : 846.6809
Mean TPS with prefill : 6.1339
Mean TPS without prefill : 6.6147
=====================================================
Mean TTFT(ms) : 10307.8123
Max TTFT(ms) : 21423.0733
Min TTFT(ms) : 362.3602
=====================================================
Mean TPOT(ms) : 151.3051
Max TPOT(ms) : 159.4649
Min TPOT(ms) : 140.899
=====================================================
Total Time(s) : 175.6032
Request Throughput(requests/s) : 0.7289
=====================================================
```
**Apply this PR**
```text
=====================================================
Total TPS with prefill(tokens/s) : 811.0014
Total TPS without prefill : 876.4423
Mean TPS with prefill : 6.3359
Mean TPS without prefill : 6.8472
=====================================================
Mean TTFT(ms) : 10263.8382
Max TTFT(ms) : 21151.2547
Min TTFT(ms) : 375.9136
=====================================================
Mean TPOT(ms) : 146.1686
Max TPOT(ms) : 154.0957
Min TPOT(ms) : 136.8879
=====================================================
Total Time(s) : 169.8579
Request Throughput(requests/s) : 0.7536
=====================================================
```
The TPOT performance gap between these two sets of data is about 3%.
- vLLM version: v0.9.2
- vLLM main:
8dfb45ca33
Signed-off-by: lianyibo <lianyibo1@kunlunit.com>
### What this PR does / why we need it?
We'll refator `CustomOp` in vllm-ascend from this pr on.
Use function `CustomOp.register_oot` to achieve the customop registery,
taking `AscendQuickGELU` as an example:
```python
from vllm_ascend.ops.activation import AscendQuickGELU
CustomOp.register_oot(_decorated_op_cls=AscendQuickGELU, name="QuickGELU")
```
This is a quick adapt for `CustomOp.register_oot` mechanism from vllm
0.9.2. For further step, we can remove inherit from `QuickGELU` can
write our own `QuickGELU` at all.
Part of https://github.com/vllm-project/vllm-ascend/pull/1647
- vLLM version: v0.9.2
- vLLM main:
8dfb45ca33
---------
Signed-off-by: MengqingCao <cmq0113@163.com>
### What this PR does / why we need it?
test func wrapper file
### Does this PR introduce _any_ user-facing change?
N/A
### How was this patch tested?
CI passed with new added test.
- vLLM version: v0.9.2
- vLLM main:
8dfb45ca33
Signed-off-by: lixudong <lixudong@cmss.chinamobile.com>
V1 is enabled by default, no need to set it by hand now. This PR remove
the useless setting in example and tests
- vLLM version: v0.9.2
- vLLM main:
9ad0a4588b
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
### What this PR does / why we need it?
Performance optimization for apply_top_k_top_p
### Does this PR introduce _any_ user-facing change?
Use VLLM_ASCEND_ENABLE_TOPK_TOPP_OPTIMIZATION to enable this feature
### How was this patch tested?
e2e & ut
- vLLM version: v0.9.2
- vLLM main:
6a9e6b2abf
Signed-off-by: Pr0Wh1teGivee <calvin_zhu0210@outlook.com>
### What this PR does / why we need it?
If a small batch of short requests is sent first, forming a chunk with a
length <128, it will corrupt the `attn_mask_cache`, causing subsequent
requests that do not form a chunk to have accuracy issues.
The root cause of this problem is the use of in-place multiplication.
Modifying it to use out-of-place multiplication will resolve the
accuracy problem.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Yes.
- vLLM version: v0.9.2
- vLLM main:
ad6c2e1a0b
---------
Signed-off-by: ApsarasX <apsarax@outlook.com>
vllm has released 0.9.2. This PR drop 0.9.1 support.
- vLLM version: v0.9.1
- vLLM main:
b942c094e3
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
### What this PR does / why we need it?
1、Sometimes loading torchair cache will fail because of the floating of
npu memory, so this pr add a new cache to save the old kv cache bytes to
avoid the possible crash while loading the torchair graph cache.
2、When caching is enabled and does not exist, the first compilation
introduces the overhead of Dynamo Gurad. So in this case, we will
compile them directly twice to skip them (This will bring 3-4 ms of tpot
optimization)
### Does this PR introduce _any_ user-facing change?
Add a new env `VLLM_ASCEND_KV_CACHE_MEGABYTES_FLOATING_TOLERANCE` to
control kv cache floating tolerance
### How was this patch tested?
- vLLM version: v0.9.1
- vLLM main:
1fd471e957
Signed-off-by: boying <897013703@qq.com>
### What this PR does / why we need it?
Add ut for test_pooling_model_runner.py
### Does this PR introduce _any_ user-facing change? N/A
### How was this patch tested?
python -m unittest test_pooling_model_runner.py
- vLLM version: v0.9.1
- vLLM main:
2e610deb72
---------
Signed-off-by: wangyanhui-cmss <wangyanhui_yewu@cmss.chinamobile.com>
### What this PR does / why we need it?
Use Base test and cleanup all manaul patch code
- Cleanup EPLB config to avoid tmp test file
- Use BaseTest with global cache
- Add license
- Add a doc to setup unit test in local env
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
CI passed
Signed-off-by: Yikun Jiang <yikunkero@gmail.com>
This commit
78fe77534b
from vllm reverted the change for FusedMoEParallelConfig
This PR do the same to fix the CI error
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
### What this PR does / why we need it?
This PR supports torchair graph mode with non-mla backend on both 800IA2
and 300I Duo platforms. The main change is to add
`attention_v1_torchair.py` to support specific attention related
operations that are required by torchair.
### Does this PR introduce _any_ user-facing change?
Before this PR, vLLM-Ascend only allows deepseek to use torchair. Now we
can also use it with pangu. Besides, we add a support model list to
control which type of models that can use torchair.
### How was this patch tested?
We have test it with PanguProMoE on both 800IA2 and 300I Duo platforms,
and model generates answer normally.
---------
Signed-off-by: angazenn <zengyanjia@huawei.com>
Signed-off-by: tianyitang <tangtianyi4@huawei.com>
Co-authored-by: angazenn <zengyanjia@huawei.com>
Co-authored-by: tianyitang <tangtianyi4@huawei.com>
### What this PR does / why we need it?
This pr supports w8a8 on 300I Duo platform. The main change is to use
`npu_quant_grouped_matmul_dequant` to replace `npu_grouped_matmul`.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
offline inference on 310p runs normally.
---------
Signed-off-by: angazenn <zengyanjia@huawei.com>
Signed-off-by: tianyitang <tangtianyi4@huawei.com>
Co-authored-by: angazenn <zengyanjia@huawei.com>
Co-authored-by: tianyitang <tangtianyi4@huawei.com>
### What this PR does / why we need it?
1. drop some useless code for w8a8 fusedmoe
2. Add in8 kv cache check
3. Add more ut.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
CI passed with new added test.
---------
Signed-off-by: zhuyilin <809721801@qq.com>
Signed-off-by: tianyitang <tangtianyi4@huawei.com>
Co-authored-by: tianyitang <tangtianyi4@huawei.com>
### What this PR does / why we need it?
test kv data transfer contains connect,pipe,buffer
### Does this PR introduce _any_ user-facing change?
N/A
### How was this patch tested?
CI passed with new added test.
---------
Signed-off-by: lixudong <lixudong@cmss.chinamobile.com>
Signed-off-by: MengqingCao <cmq0113@163.com>
Co-authored-by: lixudong <lixudong@cmss.chinamobile.com>
Co-authored-by: MengqingCao <cmq0113@163.com>
### What this PR does / why we need it?
Change as little existing code as possible to add v1 pooling task's
support, notice that i move down the `vllm.v1.worker.gpu_input_batch` to
vllm-ascend, Considering the frequent changes in upstream interfaces, in
order to decouple, so i move it here
### How was this patch tested?
CI passed with new added/existing test, and I have a simple test was
first conducted locally which is adapted from
https://www.modelscope.cn/models/Qwen/Qwen3-Embedding-0.6B, just like
bellow：
```python
import os
import torch
from vllm import LLM
os.environ["VLLM_USE_MODELSCOPE"]="True"
def get_detailed_instruct(task_description: str, query: str) -> str:
return f'Instruct: {task_description}\nQuery:{query}'
# Each query must come with a one-sentence instruction that describes the task
task = 'Given a web search query, retrieve relevant passages that answer the query'
queries = [
get_detailed_instruct(task, 'What is the capital of China?'),
get_detailed_instruct(task, 'Explain gravity')
]
# No need to add instruction for retrieval documents
documents = [
"The capital of China is Beijing.",
"Gravity is a force that attracts two bodies towards each other. It gives weight to physical objects and is responsible for the movement of planets around the sun."
]
input_texts = queries + documents
model = LLM(model="Qwen/Qwen3-Embedding-0.6B", task="embed")
outputs = model.embed(input_texts)
embeddings = torch.tensor([o.outputs.embedding for o in outputs])
scores = (embeddings[:2] @ embeddings[2:].T)
print(scores.tolist())
# [[0.7620252966880798, 0.14078938961029053], [0.1358368694782257, 0.6013815999031067]]
```
---------
Signed-off-by: wangli <wangli858794774@gmail.com>
Signed-off-by: wangli <858794774@qq.com>
Co-authored-by: wangli <858794774@qq.com>
Add static build_info py file to show soc and sleep mode info. It helps
to make the code clean and the error info will be more friendly for
users
This PR also added the unit test for vllm_ascend/utils.py
This PR also added the base test class for all ut in tests/ut/base.py
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
### What this PR does / why we need it?
Add ut for parallel_state.py
### Does this PR introduce _any_ user-facing change?
N/A
### How was this patch tested?
python -m unittest test_parallel_state.py
---------
Signed-off-by: wangyanhui-cmss <wangyanhui_yewu@cmss.chinamobile.com>
### What this PR does / why we need it?
Use fused ops torch_npu.npu_top_k_top_p(logits, p, k) when p and k are
not None, otherwise fallback to the original one. The replacement will
take place automatically when `VLLM_ASCEND_ENABLE_TOPK_OPTIMIZE=1` .
This patch are using `npu_top_k_top_p` which required
torch_npu>=2.5.1.post1.dev20250619
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Tested by DeepSeek R1 and UT passed
Signed-off-by: Pr0Wh1teGivee <calvin_zhu0210@outlook.com>
<!-- Thanks for sending a pull request!
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### What this PR does / why we need it?
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- Fixes #
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1.add static EPLB unit test
2.fix bug: Tensor cannot be directly judged by if statements
### Does this PR introduce _any_ user-facing change?
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as API, interface or other behavior changes.
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### How was this patch tested?
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-->
Run the unit test.
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Signed-off-by: songshanhu07 <1763685535@qq.com>
