[Build] Update doc (#509)
1. install torch-npu before vllm-ascend to ensure custom ops build success. 2. set `COMPILE_CUSTOM_KERNELS=0` if users want to disable custom ops build. Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
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@@ -28,6 +28,9 @@ cd ..
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# Clone vllm-ascend and install
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# Clone vllm-ascend and install
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git clone https://github.com/vllm-project/vllm-ascend.git
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git clone https://github.com/vllm-project/vllm-ascend.git
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cd vllm-ascend
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cd vllm-ascend
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# install system requirement
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apt install -y gcc g++ cmake libnuma-dev
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# install project requirement
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pip install -r requirements-dev.txt
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pip install -r requirements-dev.txt
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# Then you can run lint and mypy test
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# Then you can run lint and mypy test
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@@ -38,6 +41,8 @@ bash format.sh
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# pip install -e .
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# pip install -e .
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# - build without deps for debugging in other OS
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# - build without deps for debugging in other OS
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# pip install -e . --no-deps
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# pip install -e . --no-deps
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# - build without custom ops
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# COMPILE_CUSTOM_KERNELS=0 pip install -e .
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# Commit changed files using `-s`
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# Commit changed files using `-s`
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git commit -sm "your commit info"
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git commit -sm "your commit info"
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@@ -123,10 +123,30 @@ First install system dependencies:
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```bash
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```bash
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apt update -y
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apt update -y
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apt install -y gcc g++ libnuma-dev
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apt install -y gcc g++ cmake libnuma-dev
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```
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```
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You can install `vllm` and `vllm-ascend` from **pre-built wheel**:
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Current version depends on a unreleased `torch-npu`, you need to install manually:
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```
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# Once the packages are installed, you need to install `torch-npu` manually,
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# because that vllm-ascend relies on an unreleased version of torch-npu.
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# This step will be removed in the next vllm-ascend release.
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#
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# Here we take python 3.10 on aarch64 as an example. Feel free to install the correct version for your environment. See:
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#
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# https://pytorch-package.obs.cn-north-4.myhuaweicloud.com/pta/Daily/v2.5.1/20250320.3/pytorch_v2.5.1_py39.tar.gz
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# https://pytorch-package.obs.cn-north-4.myhuaweicloud.com/pta/Daily/v2.5.1/20250320.3/pytorch_v2.5.1_py310.tar.gz
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# https://pytorch-package.obs.cn-north-4.myhuaweicloud.com/pta/Daily/v2.5.1/20250320.3/pytorch_v2.5.1_py311.tar.gz
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#
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mkdir pta
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cd pta
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wget https://pytorch-package.obs.cn-north-4.myhuaweicloud.com/pta/Daily/v2.5.1/20250320.3/pytorch_v2.5.1_py310.tar.gz
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tar -xvf pytorch_v2.5.1_py310.tar.gz
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pip install ./torch_npu-2.5.1.dev20250320-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
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```
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Then you can install `vllm` and `vllm-ascend` from **pre-built wheel**:
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```{code-block} bash
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```{code-block} bash
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:substitutions:
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:substitutions:
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@@ -156,25 +176,10 @@ pip install -e . --extra-index https://download.pytorch.org/whl/cpu/
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```
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```
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:::
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:::
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Current version depends on a unreleased `torch-npu`, you need to install manually:
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```{note}
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vllm-ascend will build custom ops by default. If you don't want to build it, set `COMPILE_CUSTOM_KERNELS=0` environment to disable it.
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```
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```
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# Once the packages are installed, you need to install `torch-npu` manually,
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# because that vllm-ascend relies on an unreleased version of torch-npu.
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# This step will be removed in the next vllm-ascend release.
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#
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# Here we take python 3.10 on aarch64 as an example. Feel free to install the correct version for your environment. See:
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#
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# https://pytorch-package.obs.cn-north-4.myhuaweicloud.com/pta/Daily/v2.5.1/20250320.3/pytorch_v2.5.1_py39.tar.gz
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# https://pytorch-package.obs.cn-north-4.myhuaweicloud.com/pta/Daily/v2.5.1/20250320.3/pytorch_v2.5.1_py310.tar.gz
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# https://pytorch-package.obs.cn-north-4.myhuaweicloud.com/pta/Daily/v2.5.1/20250320.3/pytorch_v2.5.1_py311.tar.gz
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#
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mkdir pta
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cd pta
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wget https://pytorch-package.obs.cn-north-4.myhuaweicloud.com/pta/Daily/v2.5.1/20250320.3/pytorch_v2.5.1_py310.tar.gz
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tar -xvf pytorch_v2.5.1_py310.tar.gz
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pip install ./torch_npu-2.5.1.dev20250320-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
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```
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::::
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::::
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::::{tab-item} Using docker
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::::{tab-item} Using docker
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