Files
vllm-ascend/docs/source/user_guide/additional_config.md
Li Wang c7446438a9 [1/N][CI] Move linting system to pre-commits hooks (#1256)
### What this PR does / why we need it?

Follow vllm-project/vllm lint way:
https://github.com/vllm-project/vllm/blob/main/.pre-commit-config.yaml

Enable pre-commit to avoid some low level error  AMAP.

This pr is one step of #1241, The purpose is make linting system more
clear and convenient, on this step, Mainly did the following things:
yapf, actionlint, ruff, typos, isort, mypy, png-lint, signoff-commit,
enforce-import-regex-instead-of-re.

TODO: 
- clang-format(check for csrc with google style)
need clean code, disable for now 
- pymarkdown
need clean code, disable for now 
- shellcheck
need clean code, disable for now 

### Does this PR introduce _any_ user-facing change?

Only developer UX change:

https://vllm-ascend--1256.org.readthedocs.build/en/1256/developer_guide/contributing.html#run-lint-locally

```
pip install -r requirements-lint.txt && pre-commit install
bash format.sh
```

### How was this patch tested?

CI passed with new added/existing test.

Co-authored-by: Yikun [yikunkero@gmail.com](mailto:yikunkero@gmail.com)
Co-authored-by: wangli
[wangli858794774@gmail.com](mailto:wangli858794774@gmail.com)
- vLLM version: v0.9.1
- vLLM main:
5358cce5ff

---------

Signed-off-by: wangli <wangli858794774@gmail.com>
2025-07-10 14:17:15 +08:00

4.0 KiB

Additional Configuration

additional configuration is a mechanism provided by vLLM to allow plugins to control inner behavior by their own. vLLM Ascend uses this mechanism to make the project more flexible.

How to use

With either online mode or offline mode, users can use additional configuration. Take Qwen3 as an example:

Online mode:

vllm serve Qwen/Qwen3-8B --additional-config='{"config_key":"config_value"}'

Offline mode:

from vllm import LLM

LLM(model="Qwen/Qwen3-8B", additional_config={"config_key":"config_value"})

Configuration options

The following table lists the additional configuration options available in vLLM Ascend:

Name Type Default Description
torchair_graph_config dict {} The config options for torchair graph mode
ascend_scheduler_config dict {} The config options for ascend scheduler
expert_tensor_parallel_size str 0 Expert tensor parallel size the model to use.
refresh bool false Whether to refresh global ascend config content. This value is usually used by rlhf or ut/e2e test case.
expert_map_path str None When using expert load balancing for the MOE model, an expert map path needs to be passed in.
chunked_prefill_for_mla bool False Whether to enable the fused operator-like chunked_prefill.
kv_cache_dtype str None When using the kv cache quantization method, kv cache dtype needs to be set, currently only int8 is supported.

The details of each config option are as follows:

torchair_graph_config

Name Type Default Description
enabled bool False Whether to enable torchair graph mode. Currently only DeepSeek series models and PanguProMoE are supported to use torchair graph mode
enable_multistream_mla bool False Whether to put vector ops of MLA to another stream. This option only takes effects on models using MLA (e.g., DeepSeek).
enable_multistream_moe bool False Whether to enable multistream shared expert. This option only takes effects on DeepSeek moe models.
enable_view_optimize bool True Whether to enable torchair view optimization
use_cached_graph bool False Whether to use cached graph
graph_batch_sizes list[int] [] The batch size for torchair graph cache
graph_batch_sizes_init bool False Init graph batch size dynamically if graph_batch_sizes is empty
enable_kv_nz bool False Whether to enable kvcache NZ layout. This option only takes effects on models using MLA (e.g., DeepSeek).

ascend_scheduler_config

Name Type Default Description
enabled bool False Whether to enable ascend scheduler for V1 engine

ascend_scheduler_config also support the options from vllm scheduler config. For example, you can add enable_chunked_prefill: True to ascend_scheduler_config as well.

Example

An example of additional configuration is as follows:

{
    "torchair_graph_config": {
        "enabled": True,
        "use_cached_graph": True,
        "graph_batch_sizes": [1, 2, 4, 8],
        "graph_batch_sizes_init": False,
        "enable_multistream_moe": False,
        "enable_kv_nz": False
    },
    "ascend_scheduler_config": {
        "enabled": True,
        "enable_chunked_prefill": True,
    },
    "expert_tensor_parallel_size": 1,
    "refresh": False,
}