### What this PR does / why we need it?
**Scope of Changes**:
| File Path |
| :--- |
|`vllm_ascend/worker/model_runner_v1.py`|
|`vllm_ascend/worker/pcp_utils.py`|
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.13.0
- vLLM main:
d68209402d
---------
Signed-off-by: MrZ20 <2609716663@qq.com>
### What this PR does / why we need it?
**Scope of Changes**:
| File Path |
| :--- |
| `vllm_ascend/distributed/kv_transfer/__init__.py` |
| `vllm_ascend/distributed/kv_transfer/kv_p2p/mooncake_connector.py` |
|
`vllm_ascend/distributed/kv_transfer/kv_p2p/mooncake_layerwise_connector.py`
|
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.14.0
- vLLM main:
d68209402d
Signed-off-by: MrZ20 <2609716663@qq.com>
### What this PR does / why we need it?
Upgrade PTA to 2.9.0
- vLLM version: v0.13.0
- vLLM main:
d68209402d
---------
Signed-off-by: wjunLu <wjunlu217@gmail.com>
### What this PR does / why we need it?
Convert `vllm-ascend/compilation` to ruff format.
### Does this PR introduce _any_ user-facing change?
During this migration, we encountered some **errors** in our CI and
testing environments, such as:
```
vllm_ascend/utils.py:653: in <module>
def register_ascend_customop(vllm_config: VllmConfig | None = None):
^^^^^^^^^^^^^^^^^
E TypeError: unsupported operand type(s) for |: 'NoneType' and 'NoneType'
```
**1. Root Cause Analysis:**
The project uses a common pattern to break circular dependencies:
```python
if TYPE_CHECKING:
from vllm.config import VllmConfig
else:
VllmConfig = None # Placeholder assigned at runtime
```
When Python parses the function definition `def
register_ascend_customop(vllm_config: VllmConfig | None)`, it attempts
to evaluate the expression `VllmConfig | None`.
Since `VllmConfig` is assigned `None` at runtime, the expression
effectively becomes `None | None`. In Python, `None` is an instance of
`NoneType`. While the `|` operator is implemented for Type objects
(classes), it is not supported for `NoneType` instances, leading to the
`TypeError` shown above.
**2. Solution:**
To maintain the modern `|` syntax required by our new linting standards
while preserving our dependency management strategy, I have introduced:
```python
from __future__ import annotations
```
at the top of the affected files. This enables **Postponed Evaluation of
Annotations (PEP 563)**.
**3. Impact and Benefits:**
- By enabling `annotations`, Python no longer executes the `VllmConfig |
None` operation during module load. Instead, it stores the annotation as
a string literal, completely avoiding the `None | None` calculation.
- We can keep the `VllmConfig = None` placeholders. This ensures that
other modules can still import these symbols without triggering an
`ImportError`, maintaining a stable dependency graph.
- IDEs and static type checkers (MyPy/Pyright) continue to resolve the
types correctly. This allows us to use modern syntax without sacrificing
type safety or runtime stability.
- The only side effect is that `__annotations__` will now return strings
instead of type objects. Since this module does not use runtime type
enforcement or reflection, this change has zero negative impact on
existing functionality.
### How was this patch tested?
- vLLM version: v0.13.0
- vLLM main:
11b6af5280
---------
Signed-off-by: MrZ20 <2609716663@qq.com>
### What this PR does / why we need it?
Description
This PR fixes linting issues in the root directory, benchmarks/, tools/
and docs/ to align with the project's Ruff configuration.
This is part of a gradual effort to enable full linting coverage across
the repository. The corresponding paths have been removed from the
exclude list in pyproject.toml.
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.13.0
- vLLM main:
2f4e6548ef
---------
Signed-off-by: root <root@LAPTOP-VQKDDVMG.localdomain>
Co-authored-by: root <root@LAPTOP-VQKDDVMG.localdomain>
### Does this PR introduce _any_ user-facing change?
suffix spec decode method rely on `arctic-inference` library. This PR
add it into requirements to make sure the function works by default
### How was this patch tested?
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: frankie-ys <yongshengwang@cmbchina.com>
Signed-off-by: frankie <wangyongsheng686@gmail.com>
### What this PR does / why we need it?
fix fastapi version == 0.123.10(<0.124.0)
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
Signed-off-by: hfadzxy <starmoon_zhang@163.com>
### What this PR does / why we need it?
This PR introduces support for adding custom CANN `aclnn` ops to
`vllm-ascend`, allowing users to define and use their own custom
operators.
Key changes include:
- Building and installing custom ops into the `vllm-ascend`-specified
directory
- Binding the `aclnn` op interface to the `torch.ops._C_ascend` module
- Enabling invocation of these ops within `vllm-ascend`
This PR includes a sample custom op:
`aclnnGroupedMatmulSwigluQuantWeightNzTensorList`, which is adapted from
the CANN operator
[`aclnnGroupedMatmulSwigluQuantWeightNZ`](https://www.hiascend.com/document/detail/zh/canncommercial/83RC1/API/aolapi/context/aclnnGroupedMatmulSwigluQuantWeightNZ.md).
Its input parameters `weight` and `weight_scale` now accept
`list[torch.Tensor]` (i.e., `at::TensorList`).
### Does this PR introduce _any_ user-facing change?
No.
- vLLM version: v0.11.2
---------
Signed-off-by: QianChenxi <chenxi.qian.cq@outlook.com>
### What this PR does / why we need it?
While using the LLM Compressor quantization tool from the VLLM community
to generate quantized weights, the VLLM Ascend engine needs to be
adapted to support the compressed tensors quantization format.
1. Add AscendCompressedTensorsConfig to replace CompressedTensorsConfig
in vllm.
2. Support CompressedTensorsW8A8 static weight.
- weight: per-channel, int8, symmetric; activation: per-tensor, int8,
symmetric.
4. Support CompressedTensorsW8A8Dynamic weight.
- weight: per-channel, int8, symmetric; activation: per-token, int8,
symmetric, dynamic.
5. Modify the override_quantization_method in AscendQuantConfig.
Co-authored-by: taoqun110 taoqun@huawei.com
Co-authored-by: chenxi-hh chen464822955@163.com
- vLLM version: v0.11.2
---------
Signed-off-by: LHXuuu <scut_xlh@163.com>
Signed-off-by: chenxi-hh <chen464822955@163.com>
Signed-off-by: chenxi-hh <32731611+chenxi-hh@users.noreply.github.com>
Co-authored-by: chenxi-hh <chen464822955@163.com>
Co-authored-by: chenxi-hh <32731611+chenxi-hh@users.noreply.github.com>
### What this PR does / why we need it?
This PR pins the transformers dependency to 4.57.1.
Reason: CI tests (specifically test_completion_with_prompt_embeds.py)
are failing with an AttributeError: 'dict' object has no attribute
'model_type' when using newer versions of transformers.
The issue stems from a bug in tokenization_utils_base.py where the code
attempts to access the model_type field of a configuration dictionary
(_config) using dot notation (_config.model_type) instead of dictionary
key lookup (_config["model_type"] or _config.get("model_type")). This
occurs in the logic block checking for transformers_version <= 4.57.2.
Pinning the version to 4.57.1 bypasses this buggy code path and restores
CI stability.
Error Traceback:
``` shell
/usr/local/python3.11.13/lib/python3.11/site-packages/transformers/tokenization_utils_base.py:2419:
if _is_local and _config.model_type not in [
E AttributeError: 'dict' object has no attribute 'model_type'
```
- vLLM main:
2918c1b49c
Signed-off-by: MrZ20 <2609716663@qq.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>
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?
vllm requires opencv-python-headless >= 4.11.0 which requires
(numpy<2.3.0,>=2), but vllm-ascend numpy version must be less than
2.0.0, so limit opencv-python-headless less than 4.11.0.86 will fix this
conflict.
### How was this patch tested?
tested by CI
- vLLM version: v0.11.0rc3
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0
Signed-off-by: 22dimensions <waitingwind@foxmail.com>
we notice that torch npu 0919 doesn't work. This PR revert related
change which rely on 0919 version.
Revert PR: #3295#3205#3102
Related: #3353
- vLLM version: v0.11.0
### What this PR does / why we need it?
Upgrade torch-npu to the newest POC version
### Does this PR introduce _any_ user-facing change?
yes, user need upgrade the pta version as well.
### How was this patch tested?
- vLLM version: v0.11.0rc3
- vLLM main:
https://github.com/vllm-project/vllm/commit/releases/v0.11.0
---------
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.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?
1. Enable pymarkdown check
2. Enable python `__init__.py` check for vllm and vllm-ascend
3. Make clean code
### How was this patch tested?
- vLLM version: v0.9.2
- vLLM main:
29c6fbe58c
---------
Signed-off-by: wangli <wangli858794774@gmail.com>
1. vLLM commit
45badd05d0
changed the pooling check logic which broken vLLM Ascend.
2. vLLM commit
3e04107d97
requires higher version of transformers. The transformers version bug
has been fixed by
e936e401de.
We can safe to remove the version limit now.
3. vLLM commit
217937221b
added a new input `enable_eplb` for FusedMoe Ops
This PR fix the broken CI.
- vLLM version: v0.9.2
- vLLM main:
6a971ed692
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
### What this PR does / why we need it?
Fix version conflict on transformers:
`pip._vendor.pkg_resources.ContextualVersionConflict: (transformers
4.53.0 (/usr/local/python3.10.17/lib/python3.10/site-packages),
Requirement.parse('transformers<4.53.0'), {'vllm-ascend'})`
Fix
https://github.com/vllm-project/vllm-ascend/actions/runs/15933263325/job/44947231642
### Does this PR introduce _any_ user-facing change?
Fix broken build
### How was this patch tested?
CI passed with new existing test.
Signed-off-by: MengqingCao <cmq0113@163.com>
### What this PR does / why we need it?
- Fix vLLM EPLB break
e9fd658a73
by recovering load_weights back to [v0.9.1
version](07b8fae219)
temporarily.
- Fix transformers>=4.53.0 image processor break
Related: https://github.com/vllm-project/vllm-ascend/issues/1470
- Mirror torch_npu requirements to pyproject.toml
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
CI passed
---------
Signed-off-by: MengqingCao <cmq0113@163.com>
Signed-off-by: Yikun Jiang <yikunkero@gmail.com>
Co-authored-by: Yikun Jiang <yikunkero@gmail.com>
1. Fix format check error to make format.sh work
2. Add codespell check CI
3. Add the missing required package for vllm-ascend.
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
### What this PR does / why we need it?
The torch-npu 2.5.1 are published:
https://pypi.org/project/torch-npu/2.5.1/
It's time to remove all torch-npu dev version from vllm-ascend code base
### Does this PR introduce _any_ user-facing change?
Yes, using torch-npu 2.5.1
### How was this patch tested?
- [ ] CI passed
- [ ] Manually test
- [ ] Grep all `dev2025`
---------
Signed-off-by: Yikun Jiang <yikunkero@gmail.com>
<!-- 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.
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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.
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clarify how you tested step by step, ideally copy and paste-able, so
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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>
This PR added patch module for vllm
1. platform patch: the patch will be registered when load the platform
2. worker patch: the patch will be registered when worker is started.
The detail is:
1. patch_common: patch for main and 0.8.4 version
4. patch_main: patch for main verison
5. patch_0_8_4: patch for 0.8.4 version
### What this PR does / why we need it?
This PR enable custom ops build by default.
### Does this PR introduce _any_ user-facing change?
Yes, users now install vllm-ascend from source will trigger custom ops
build step.
### How was this patch tested?
By image build and e2e CI
---------
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
### What this PR does / why we need it?
Set torchvision<0.21.0 to match torch/torch_npu version to resolve
`RuntimeError: operator torchvision::nms does not exist`.
Closes: https://github.com/vllm-project/vllm-ascend/issues/477
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
CI passed
Signed-off-by: Yikun Jiang <yikunkero@gmail.com>
### What this PR does / why we need it?
vLLM bumps numpy version to 2.x:
8427f70493
, this will cause a
`pip._vendor.pkg_resources.ContextualVersionConflict: (numpy 2.2.4
(/usr/local/python3.10/lib/python3.10/site-packages),
Requirement.parse('numpy==1.26.4'), {'vllm-ascend'})` failure when vllm
ascend install. This PR resolved the issue by:
- Set numpy < 2.0.0 to resolve numpy VersionConflict
- Sync requirements and toml
- Reorder
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
CI passed
Closes: https://github.com/vllm-project/vllm-ascend/issues/473
Signed-off-by: Yikun Jiang <yikunkero@gmail.com>
