98 lines
3.3 KiB
Docker
98 lines
3.3 KiB
Docker
{#
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# SPDX-FileCopyrightText: Copyright (c) 2024-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: Apache-2.0
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#}
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# === BEGIN templates/vllm_framework.Dockerfile ===
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########################################################
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########## Framework Development Image ################
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########################################################
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#
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# PURPOSE: Framework development and vLLM compilation
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#
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# This stage builds and compiles framework dependencies including:
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# - vLLM inference engine with CUDA support
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# - DeepGEMM and FlashInfer optimizations
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# - All necessary build tools and compilation dependencies
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# - Framework-level Python packages and extensions
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#
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# Use this stage when you need to:
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# - Build vLLM from source with custom modifications
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# - Develop or debug framework-level components
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# - Create custom builds with specific optimization flags
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#
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# Use dynamo base image (see /container/Dockerfile for more details)
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FROM ${BASE_IMAGE}:${BASE_IMAGE_TAG} AS framework
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COPY --from=dynamo_base /bin/uv /bin/uvx /bin/
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ARG PYTHON_VERSION
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# Cache apt downloads; sharing=locked avoids apt/dpkg races with concurrent builds.
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RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
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apt-get update -y \
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&& DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
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# Python runtime - CRITICAL for virtual environment to work
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python${PYTHON_VERSION}-dev \
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build-essential \
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# vLLM build dependencies
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cmake \
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ibverbs-providers \
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ibverbs-utils \
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libibumad-dev \
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libibverbs-dev \
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libnuma-dev \
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librdmacm-dev \
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rdma-core \
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&& apt-get clean \
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&& rm -rf /var/lib/apt/lists/*
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# if libmlx5.so not shipped with 24.04 rdma-core packaging, CMAKE will fail when looking for
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# generic dev name .so so we symlink .s0.1 -> .so
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RUN ln -sf /usr/lib/aarch64-linux-gnu/libmlx5.so.1 /usr/lib/aarch64-linux-gnu/libmlx5.so || true
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# Create virtual environment
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RUN mkdir -p /opt/dynamo/venv && \
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export UV_CACHE_DIR=/root/.cache/uv && \
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uv venv /opt/dynamo/venv --python $PYTHON_VERSION
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# Activate virtual environment
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ENV VIRTUAL_ENV=/opt/dynamo/venv \
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PATH="/opt/dynamo/venv/bin:${PATH}"
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ARG ARCH
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# Install vllm - keep this early in Dockerfile to avoid
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# rebuilds from unrelated source code changes
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ARG VLLM_REF
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ARG VLLM_GIT_URL
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ARG DEEPGEMM_REF
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ARG FLASHINF_REF
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ARG LMCACHE_REF
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ARG VLLM_OMNI_REF
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ARG CUDA_VERSION
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ARG MAX_JOBS
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ENV MAX_JOBS=$MAX_JOBS
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ENV CUDA_HOME=/usr/local/cuda
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# Install VLLM and related dependencies
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RUN --mount=type=bind,source=./container/deps/,target=/tmp/deps \
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--mount=type=cache,target=/root/.cache/uv \
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export UV_CACHE_DIR=/root/.cache/uv UV_HTTP_TIMEOUT=300 UV_HTTP_RETRIES=5 && \
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cp /tmp/deps/vllm/install_vllm.sh /tmp/install_vllm.sh && \
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chmod +x /tmp/install_vllm.sh && \
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/tmp/install_vllm.sh \
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--vllm-ref $VLLM_REF \
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--max-jobs $MAX_JOBS \
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--arch $ARCH \
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--installation-dir /opt \
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${DEEPGEMM_REF:+--deepgemm-ref "$DEEPGEMM_REF"} \
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${FLASHINF_REF:+--flashinf-ref "$FLASHINF_REF"} \
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${LMCACHE_REF:+--lmcache-ref "$LMCACHE_REF"} \
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${VLLM_OMNI_REF:+--vllm-omni-ref "$VLLM_OMNI_REF"} \
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--cuda-version $CUDA_VERSION
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ENV LD_LIBRARY_PATH=\
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/opt/vllm/tools/ep_kernels/ep_kernels_workspace/nvshmem_install/lib:\
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$LD_LIBRARY_PATH
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