2025-02-05 10:53:12 +08:00
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-r requirements-lint.txt
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support aclgraph (#426)
<!-- Thanks for sending a pull request!
BEFORE SUBMITTING, PLEASE READ
https://docs.vllm.ai/en/latest/contributing/overview.html
-->
### What this PR does / why we need it?
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section is to outline the changes and how this PR fixes the issue.
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reviews in your PR.
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and bug description.
- Fixes #
-->
This PR supports the access of vllm-acend to the piecewise_graph feature
provided by the v1 engine.
1. register unifiled_ascend_attention_with_output for piecewise_graph to
split graph.
2. support NPUGraph to accelerate kernel launch.
### Does this PR introduce _any_ user-facing change?
<!--
Note that it means *any* user-facing change including all aspects such
as API, interface or other behavior changes.
Documentation-only updates are not considered user-facing changes.
-->
support npugraph to default， Users can disenable the npugraph feature by
configuring enforce_eager.
This has corresponding requirements for the versions of torch_npu and
CANN, and they need to support graph capture.
### How was this patch tested?
<!--
CI passed with new added/existing test.
If it was tested in a way different from regular unit tests, please
clarify how you tested step by step, ideally copy and paste-able, so
that other reviewers can test and check, and descendants can verify in
the future.
If tests were not added, please describe why they were not added and/or
why it was difficult to add.
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it turn to default
---------
Signed-off-by: Bug Hunter Yan <yanpq@zju.edu.cn>
Signed-off-by: Yizhou Liu <liu_yizhou@outlook.com>
Co-authored-by: Yizhou Liu <liu_yizhou@outlook.com>
2025-04-23 20:56:24 +08:00
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-r requirements.txt
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2025-02-05 10:53:12 +08:00
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modelscope
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2025-05-12 22:04:48 +08:00
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openai
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2025-11-11 15:31:00 +08:00
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pytest >= 6.0,<9.0.0
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2025-02-13 18:44:17 +08:00
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pytest-asyncio
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static EPLB fix bug, add unit test (#1186)
<!-- Thanks for sending a pull request!
BEFORE SUBMITTING, PLEASE READ
https://docs.vllm.ai/en/latest/contributing/overview.html
-->
### What this PR does / why we need it?
<!--
- Please clarify what changes you are proposing. The purpose of this
section is to outline the changes and how this PR fixes the issue.
If possible, please consider writing useful notes for better and faster
reviews in your PR.
- Please clarify why the changes are needed. For instance, the use case
and bug description.
- Fixes #
-->
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?
<!--
Note that it means *any* user-facing change including all aspects such
as API, interface or other behavior changes.
Documentation-only updates are not considered user-facing changes.
-->
### How was this patch tested?
<!--
CI passed with new added/existing test.
If it was tested in a way different from regular unit tests, please
clarify how you tested step by step, ideally copy and paste-able, so
that other reviewers can test and check, and descendants can verify in
the future.
If tests were not added, please describe why they were not added and/or
why it was difficult to add.
-->
Run the unit test.
---------
Signed-off-by: songshanhu07 <1763685535@qq.com>
2025-06-18 19:46:56 +08:00
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pytest-mock
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2026-01-07 14:15:53 +08:00
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lm-eval==0.4.9.2
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2025-04-22 17:50:06 +08:00
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types-jsonschema
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2025-05-12 22:04:48 +08:00
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xgrammar
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zmq
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2025-05-29 10:17:12 +08:00
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types-psutil
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2025-06-21 00:01:05 +08:00
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pytest-cov
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2025-07-15 12:49:57 +08:00
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regex
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[V1][ModelRunner] Support pooling model for v1 engine (#1359)
### 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>
2025-06-30 16:31:12 +08:00
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sentence_transformers
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2025-10-25 09:36:44 +08:00
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ray>=2.47.1,<=2.48.0
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2025-07-30 22:49:20 +08:00
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protobuf>3.20.0
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[Bugfix] Fix num_hidden_layers when Qwen2-Audio 7B (#1803)
### 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/1780
https://github.com/vllm-project/vllm-ascend/issues/1760
https://github.com/vllm-project/vllm-ascend/issues/1276
https://github.com/vllm-project/vllm-ascend/issues/359
- vLLM version: v0.10.0
- vLLM main:
https://github.com/vllm-project/vllm/commit/7728dd77bb802e1876012eb264df4d2fa2fc6f3c
Signed-off-by: hfadzxy <starmoon_zhang@163.com>
2025-07-26 20:13:00 +08:00
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librosa
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soundfile
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2025-10-25 09:36:44 +08:00
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pytest_mock
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2025-11-12 09:07:14 +08:00
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msserviceprofiler>=1.2.2
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2025-12-01 18:41:42 +08:00
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mindstudio-probe>=8.3.0
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2025-12-08 08:27:46 +08:00
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arctic-inference==0.1.1
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[Feat]Xlite Qwen3 MoE Support Data Parallel (#6715)
### What this PR does / why we need it?
This patch adds support for the Qwen3-MoE data parallel in Xlite. For
more details about Xlite, please refer to the following
link:[https://atomgit.com/openeuler/GVirt/blob/master/xlite/README.md](https://atomgit.com/openeuler/GVirt/blob/master/xlite/README.md).
online server config:
```shell
port=$1
log=$2
export VLLM_USE_V1=1
export TASK_QUEUE_ENABLE=1
export HCCL_BUFFSIZE=512
export HCCL_OP_EXPANSION_MODE="AIV"
export OMP_PROC_BIND=false
export VLLM_ASCEND_ENABLE_NZ=0
sysctl -w vm.swappiness=0
sysctl -w kernel.numa_balancing=0
sysctl kernel.sched_migration_cost_ns=50000
ip=127.0.0.1
python -m vllm.entrypoints.openai.api_server \
--model /mnt/nvme1n1/wy/models/Qwen3-30B-A3B \
--tensor-parallel-size 2 \
--enable-expert-parallel \
--data-parallel-size 4 \
--gpu-memory-utilization 0.9 \
--max-num-batched-tokens 32768 \
--data-parallel-size-local 4 \
--max-num-seqs=200 \
--block-size 128 \
--max-model-len 6656 \
--trust-remote-code \
--disable-log-requests \
--served-model-name qwen \
--no-enable-prefix-caching \
--additional-config '{"xlite_graph_config": {"enabled": true, "full_mode": true}, "enable_cpu_binding": true}' \
--compilation-config '{"cudagraph_capture_sizes":[1, 16, 32, 48, 64, 100, 150, 200], "cudagraph_mode": "FULL_DECODE_ONLY"}' \
--async-scheduling \
--host ${ip} \
--port ${port} > ${log} 2>&1 &
```
test_config:
```shell
vllm bench serve \
--max-concurrency ${maxconcurrency} \
--num-prompts ${num_prompts} \
--host ${HOST} \
--port ${PORT} \
--model ${MODEL_NAME} \
--dataset-name random \
--backend openai-chat \
--random-input-len 512 \
--random-output-len 512 \
--random-range-ratio 0.2 \
--temperature 0.6 \
--metric-percentiles "50,90,99" \
--tokenizer ${TOKENIZER_PATH} \
--endpoint /v1/chat/completions \
--ignore-eos
```
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
- vLLM version: v0.16.0
- vLLM main:
https://github.com/vllm-project/vllm/commit/c86cdcbcd2d49c4d4cd38339315bacb1d8b2a1c0
Signed-off-by: uuzWY <Ethan.wangyuan@huawei.com>
Co-authored-by: uuzWY <Ethan.wangyuan@huawei.com>
2026-03-09 17:53:35 +08:00
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xlite==0.1.0rc3
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2025-12-23 10:48:31 +08:00
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uc-manager
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