[Build] Force torch version (#3791)

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>
This commit is contained in:
wangxiyuan
2025-10-30 15:53:15 +08:00
committed by GitHub
parent ff47524b88
commit 10772d94e3
8 changed files with 15 additions and 8 deletions

View File

@@ -20,6 +20,13 @@ set(VLLM_ASCEND_INSTALL_PATH "${CMAKE_INSTALL_PREFIX}")
find_package(Torch REQUIRED)
run_python(TORCH_VERSION
"import torch; print(torch.__version__)" "Failed to locate torch path")
# check torch version is 2.7.1
if(NOT ${TORCH_VERSION} VERSION_EQUAL "2.7.1")
message(FATAL_ERROR "Expected PyTorch version 2.7.1, but found ${TORCH_VERSION}")
endif()
set(RUN_MODE "npu" CACHE STRING "cpu/sim/npu")
set(SOC_VERSION ${SOC_VERSION})
message(STATUS "Detected SOC version: ${SOC_VERSION}")

View File

@@ -43,7 +43,7 @@ By using vLLM Ascend plugin, popular open-source models, including Transformer-l
- Software:
* Python >= 3.9, < 3.12
* CANN >= 8.2.rc1 (Ascend HDK version refers to [here](https://www.hiascend.com/document/detail/zh/canncommercial/82RC1/releasenote/releasenote_0000.html))
* PyTorch >= 2.7.1, torch-npu >= 2.7.1.dev20250724
* PyTorch == 2.7.1, torch-npu == 2.7.1.dev20250724
* vLLM (the same version as vllm-ascend)
## Getting Started

View File

@@ -44,7 +44,7 @@ vLLM 昇腾插件 (`vllm-ascend`) 是一个由社区维护的让vLLM在Ascend NP
- 软件:
* Python >= 3.9, < 3.12
* CANN >= 8.2.rc1 (Ascend HDK 版本参考[这里](https://www.hiascend.com/document/detail/zh/canncommercial/82RC1/releasenote/releasenote_0000.html))
* PyTorch >= 2.7.1, torch-npu >= 2.7.1.dev20250724
* PyTorch == 2.7.1, torch-npu == 2.7.1.dev20250724
* vLLM (与vllm-ascend版本一致)
## 开始使用

View File

@@ -13,8 +13,8 @@ This document describes how to install vllm-ascend manually.
|---------------|----------------------------------|-------------------------------------------|
| Ascend HDK | Refer to [here](https://www.hiascend.com/document/detail/zh/canncommercial/82RC1/releasenote/releasenote_0000.html) | Required for CANN |
| CANN | >= 8.2.RC1 | Required for vllm-ascend and torch-npu |
| torch-npu | >= 2.7.1.dev20250724 | Required for vllm-ascend, No need to install manually, it will be auto installed in below steps |
| torch | >= 2.7.1 | Required for torch-npu and vllm |
| torch-npu | == 2.7.1.dev20250724 | Required for vllm-ascend, No need to install manually, it will be auto installed in below steps |
| torch | == 2.7.1 | Required for torch-npu and vllm |
There are two installation methods:
- **Using pip**: first prepare env manually or via CANN image, then install `vllm-ascend` using pip.

View File

@@ -5,7 +5,7 @@
* Software:
* Python >= 3.9, < 3.12
* CANN >= 8.2.rc1
* PyTorch >= 2.7.1, torch-npu >= 2.7.1.dev20250724
* PyTorch == 2.7.1, torch-npu == 2.7.1.dev20250724
* vLLM (same version as vllm-ascend)
* mooncake-transfer-engine reference documentation: https://github.com/kvcache-ai/Mooncake/blob/main/doc/zh/ascend_transport.md

View File

@@ -5,7 +5,7 @@
* Software:
* Python >= 3.9, < 3.12
* CANN >= 8.2.rc1
* PyTorch >= 2.7.1, torch-npu >= 2.7.1.dev20250724
* PyTorch == 2.7.1, torch-npu == 2.7.1.dev20250724
* vLLMmain branch
* vLLM-Ascendmain branch
* Mooncake[AscendTransport/Mooncake at pooling-async-memcpy](https://github.com/AscendTransport/Mooncake/tree/pooling-async-memcpy)(Currently available branch code, continuously updated.)

View File

@@ -15,7 +15,7 @@ requires = [
"setuptools>=64",
"setuptools-scm>=8",
"torch-npu==2.7.1.dev20250724",
"torch>=2.7.1",
"torch==2.7.1",
"torchvision",
"wheel",
"msgpack",

View File

@@ -11,7 +11,7 @@ scipy
pandas
setuptools>=64
setuptools-scm>=8
torch>=2.7.1
torch==2.7.1
torchvision
wheel
pandas-stubs