wangxiyuan 69b817ed65 [CI] Add unit test framework (#1201)
This PR added the unit test framework to enable ut for vLLM Ascend. Unit
test runs on CPU machines. It'll be ran once lint check is passed the
same as e2e test.

For unit test, this PR created a new folder called `ut` under `tests`
module. All the test file in `ut` should keep the same with the code in
`vllm-ascend`. The file name should be start with `test_` prefix. For
example, in this PR. the `test_ascend_config.py` is added for
`ascend_config.py` test.

A new fille `worker/test_worker_v1.py` is also added as the placeholder.
This file should be the unit test for `vllm-ascend/worker/worker_v1.py`.

Additional, a new `fake_weight` folder is added, it contains the
config.json from `facebook/opt-125m`, so that the test will not always
visit huggingface.

TODO:
We should add all the unit test file one by one in the future.

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
2025-06-16 18:32:28 +08:00
2025-02-05 10:53:12 +08:00
2025-06-11 16:33:11 +08:00
2025-06-16 18:32:28 +08:00
2025-01-29 02:44:13 -08:00
2025-04-01 09:25:33 +08:00

vllm-ascend

vLLM Ascend Plugin

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Overview

vLLM Ascend (vllm-ascend) is a community maintained hardware plugin for running vLLM seamlessly on the Ascend NPU.

It is the recommended approach for supporting the Ascend backend within the vLLM community. It adheres to the principles outlined in the [RFC]: Hardware pluggable, providing a hardware-pluggable interface that decouples the integration of the Ascend NPU with vLLM.

By using vLLM Ascend plugin, popular open-source models, including Transformer-like, Mixture-of-Expert, Embedding, Multi-modal LLMs can run seamlessly on the Ascend NPU.

Prerequisites

  • Hardware: Atlas 800I A2 Inference series, Atlas A2 Training series
  • OS: Linux
  • Software:
    • Python >= 3.9, < 3.12
    • CANN >= 8.1.RC1
    • PyTorch >= 2.5.1, torch-npu >= 2.5.1
    • vLLM (the same version as vllm-ascend)

Getting Started

Please refer to QuickStart and Installation for more details.

Contributing

See CONTRIBUTING for more details, which is a step-by-step guide to help you set up development environment, build and test.

We welcome and value any contributions and collaborations:

Branch

vllm-ascend has main branch and dev branch.

  • main: main branchcorresponds to the vLLM main branch, and is continuously monitored for quality through Ascend CI.
  • vX.Y.Z-dev: development branch, created with part of new releases of vLLM. For example, v0.7.3-dev is the dev branch for vLLM v0.7.3 version.

Below is maintained branches:

Branch Status Note
main Maintained CI commitment for vLLM main branch and vLLM 0.9.x branch
v0.7.1-dev Unmaintained Only doc fixed is allowed
v0.7.3-dev Maintained CI commitment for vLLM 0.7.3 version

Please refer to Versioning policy for more details.

Weekly Meeting

License

Apache License 2.0, as found in the LICENSE file.

Description
XC-LLM: A Specially Optimized LLM Inference Engine for ModelHub XC
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