@@ -139,21 +139,6 @@ RUN ldconfig /usr/local/cuda-$(echo $CUDA_VERSION | cut -d. -f1,2)/compat/
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WORKDIR /workspace
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# install build and runtime dependencies
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-
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- # arm64 (GH200) build follows the practice of "use existing pytorch" build,
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- # we need to install torch and torchvision from the nightly builds first,
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- # pytorch will not appear as a vLLM dependency in all of the following steps
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- # after this step
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- RUN --mount=type=cache,target=/root/.cache/uv \
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- if [ "$TARGETPLATFORM" = "linux/arm64" ]; then \
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- uv pip install --system \
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- --index-url ${PYTORCH_CUDA_NIGHTLY_INDEX_BASE_URL}/cu$(echo $CUDA_VERSION | cut -d. -f1,2 | tr -d '.' ) \
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- "torch==2.8.0.dev20250318+cu128" "torchvision==0.22.0.dev20250319" ; \
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- uv pip install --system \
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- --index-url ${PYTORCH_CUDA_NIGHTLY_INDEX_BASE_URL}/cu$(echo $CUDA_VERSION | cut -d. -f1,2 | tr -d '.' ) \
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- --pre pytorch_triton==3.3.0+gitab727c40; \
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- fi
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-
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COPY requirements/common.txt requirements/common.txt
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COPY requirements/cuda.txt requirements/cuda.txt
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RUN --mount=type=cache,target=/root/.cache/uv \
@@ -234,6 +219,8 @@ RUN --mount=type=cache,target=/root/.cache/uv \
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&& sccache --show-stats; \
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fi
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+ ARG vllm_target_device="cuda"
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+ ENV VLLM_TARGET_DEVICE=${vllm_target_device}
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ENV CCACHE_DIR=/root/.cache/ccache
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RUN --mount=type=cache,target=/root/.cache/ccache \
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--mount=type=cache,target=/root/.cache/uv \
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