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build 0.10.1 add upstream commands
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scripts/install_efa.sh

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@@ -72,7 +72,7 @@ function install_efa {
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apt-get autoremove -y
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rm -rf /var/lib/apt/lists/*
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ldconfig
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check_libnccl_net_so
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# check_libnccl_net_so
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}
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# idiomatic parameter and option handling in sh

vllm/arm64/gpu/Dockerfile.arm64.gpu

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FROM --platform=linux/arm64 docker.io/vllm/vllm-openai:v0.10.1 as final
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FROM nvidia/cuda:12.8.1-devel-ubuntu22.04 AS builder
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# build arguments
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ARG CUDA_VERSION=12.8.1
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ARG PYTHON_VERSION=3.12
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ARG TARGETPLATFORM=linux/arm64
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RUN apt-get update && apt-get install -y \
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git \
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python${PYTHON_VERSION} \
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python${PYTHON_VERSION}-dev \
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python${PYTHON_VERSION}-venv \
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python3-pip \
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wget \
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ninja-build \
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ccache \
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&& rm -rf /var/lib/apt/lists/*
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RUN pip install --upgrade pip && \
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pip install uv
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# Install PyTorch nightly for ARM64
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RUN uv pip install --system \
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--index-url https://download.pytorch.org/whl/nightly/cu$(echo $CUDA_VERSION | cut -d. -f1,2 | tr -d '.') \
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"torch==2.8.0.dev20250318+cu128" \
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"torchvision==0.22.0.dev20250319" \
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--pre pytorch_triton==3.3.0+gitab727c40
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WORKDIR /workspace
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RUN git clone https://github.com/vllm-project/vllm.git --branch v0.10.1
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WORKDIR /workspace/vllm
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ENV TORCH_CUDA_ARCH_LIST="7.5 8.9 9.0 10.0 12.0"
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RUN --mount=type=cache,target=/root/.cache/uv \
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uv pip install --system -r requirements/cuda.txt \
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--extra-index-url https://download.pytorch.org/whl/nightly/cu$(echo $CUDA_VERSION | cut -d. -f1,2 | tr -d '.') && \
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python setup.py bdist_wheel --dist-dir=/workspace/dist
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FROM nvidia/cuda:12.8.1-devel-ubuntu22.04 as final
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ARG PYTHON="python3"
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ARG EFA_VERSION="1.43.1"
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LABEL maintainer="Amazon AI"

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