[Build][Bugfix] Fix source code path to avoid reference error (#726)
### What this PR does / why we need it? Fix source code path to avoid reference error in docker image fix https://github.com/vllm-project/vllm-ascend/issues/725 Signed-off-by: MengqingCao <cmq0113@163.com>
This commit is contained in:
2
.github/workflows/image_openeuler.yml
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2
.github/workflows/image_openeuler.yml
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@@ -88,6 +88,8 @@ jobs:
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uses: docker/build-push-action@v6
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with:
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platforms: linux/amd64,linux/arm64
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# use the current repo path as the build context, ensure .git is contained
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context: .
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# only trigger when tag, branch/main push
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push: ${{ github.event_name == 'push' && github.repository_owner == 'vllm-project' }}
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labels: ${{ steps.meta.outputs.labels }}
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2
.github/workflows/image_ubuntu.yml
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2
.github/workflows/image_ubuntu.yml
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@@ -88,6 +88,8 @@ jobs:
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uses: docker/build-push-action@v6
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with:
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platforms: linux/amd64,linux/arm64
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# use the current repo path as the build context, ensure .git is contained
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context: .
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# only trigger when tag, branch/main push
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push: ${{ github.event_name == 'push' && github.repository_owner == 'vllm-project' }}
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labels: ${{ steps.meta.outputs.labels }}
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@@ -31,16 +31,16 @@ RUN apt-get update -y && \
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WORKDIR /workspace
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COPY . /workspace/vllm-ascend/
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COPY . /vllm-workspace/vllm-ascend/
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RUN pip config set global.index-url ${PIP_INDEX_URL}
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# Install vLLM
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ARG VLLM_REPO=https://github.com/vllm-project/vllm.git
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ARG VLLM_TAG=v0.8.5
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RUN git clone --depth 1 $VLLM_REPO --branch $VLLM_TAG /workspace/vllm
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RUN git clone --depth 1 $VLLM_REPO --branch $VLLM_TAG /vllm-workspace/vllm
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# In x86, triton will be installed by vllm. But in Ascend, triton doesn't work correctly. we need to uninstall it.
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RUN VLLM_TARGET_DEVICE="empty" python3 -m pip install -v -e /workspace/vllm/ --extra-index https://download.pytorch.org/whl/cpu/ && \
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RUN VLLM_TARGET_DEVICE="empty" python3 -m pip install -v -e /vllm-workspace/vllm/ --extra-index https://download.pytorch.org/whl/cpu/ && \
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python3 -m pip uninstall -y triton && \
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python3 -m pip cache purge
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@@ -49,7 +49,7 @@ RUN VLLM_TARGET_DEVICE="empty" python3 -m pip install -v -e /workspace/vllm/ --e
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RUN source /usr/local/Ascend/ascend-toolkit/set_env.sh && \
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source /usr/local/Ascend/nnal/atb/set_env.sh && \
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export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/Ascend/ascend-toolkit/latest/`uname -i`-linux/devlib && \
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python3 -m pip install -v -e /workspace/vllm-ascend/ --extra-index https://download.pytorch.org/whl/cpu/ && \
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python3 -m pip install -v -e /vllm-workspace/vllm-ascend/ --extra-index https://download.pytorch.org/whl/cpu/ && \
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python3 -m pip cache purge
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# Install modelscope (for fast download) and ray (for multinode)
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@@ -30,15 +30,15 @@ RUN pip config set global.index-url ${PIP_INDEX_URL}
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WORKDIR /workspace
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COPY . /workspace/vllm-ascend/
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COPY . /vllm-workspace/vllm-ascend/
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# Install vLLM
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ARG VLLM_REPO=https://github.com/vllm-project/vllm.git
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ARG VLLM_TAG=v0.8.5
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RUN git clone --depth 1 $VLLM_REPO --branch $VLLM_TAG /workspace/vllm
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RUN git clone --depth 1 $VLLM_REPO --branch $VLLM_TAG /vllm-workspace/vllm
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# In x86, triton will be installed by vllm. But in Ascend, triton doesn't work correctly. we need to uninstall it.
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RUN VLLM_TARGET_DEVICE="empty" python3 -m pip install -e /workspace/vllm/ --extra-index https://download.pytorch.org/whl/cpu/ && \
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RUN VLLM_TARGET_DEVICE="empty" python3 -m pip install -e /vllm-workspace/vllm/ --extra-index https://download.pytorch.org/whl/cpu/ && \
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python3 -m pip uninstall -y triton && \
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python3 -m pip cache purge
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@@ -46,7 +46,7 @@ RUN VLLM_TARGET_DEVICE="empty" python3 -m pip install -e /workspace/vllm/ --extr
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RUN source /usr/local/Ascend/ascend-toolkit/set_env.sh && \
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source /usr/local/Ascend/nnal/atb/set_env.sh && \
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export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/Ascend/ascend-toolkit/latest/`uname -i`-linux/devlib && \
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python3 -m pip install -v -e /workspace/vllm-ascend/ --extra-index https://download.pytorch.org/whl/cpu/ && \
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python3 -m pip install -v -e /vllm-workspace/vllm-ascend/ --extra-index https://download.pytorch.org/whl/cpu/ && \
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python3 -m pip cache purge
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# Install modelscope (for fast download) and ray (for multinode)
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