142 lines
3.8 KiB
Docker
142 lines
3.8 KiB
Docker
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# Dockerfile.build-paddle - Build PaddlePaddle GPU wheel for ARM64
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#
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# This Dockerfile compiles PaddlePaddle from source with CUDA support for ARM64.
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# The resulting wheel can be used in Dockerfile.gpu for ARM64 GPU acceleration.
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#
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# Build time: 2-4 hours depending on hardware
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# Output: /output/paddlepaddle_gpu-*.whl
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#
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# Usage:
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# docker compose run build-paddle
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# # or
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# docker build -f Dockerfile.build-paddle -t paddle-builder .
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# docker run -v ./wheels:/output paddle-builder
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FROM nvidia/cuda:12.4.1-cudnn-devel-ubuntu22.04
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LABEL maintainer="Sergio Jimenez"
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LABEL description="PaddlePaddle GPU wheel builder for ARM64"
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# Build arguments
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ARG PADDLE_VERSION=v3.0.0
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ARG PYTHON_VERSION=3.11
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# Environment setup
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ENV DEBIAN_FRONTEND=noninteractive
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ENV PYTHONUNBUFFERED=1
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# Install build dependencies
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RUN apt-get update && apt-get install -y --no-install-recommends \
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# Python
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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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# Build tools
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build-essential \
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cmake \
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ninja-build \
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git \
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wget \
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curl \
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pkg-config \
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# Libraries
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libssl-dev \
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libffi-dev \
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zlib1g-dev \
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libbz2-dev \
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libreadline-dev \
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libsqlite3-dev \
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liblzma-dev \
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libncurses5-dev \
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libncursesw5-dev \
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libgflags-dev \
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libgoogle-glog-dev \
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libprotobuf-dev \
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protobuf-compiler \
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patchelf \
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# Additional dependencies for Paddle
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libopenblas-dev \
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liblapack-dev \
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swig \
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&& rm -rf /var/lib/apt/lists/* \
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&& ln -sf /usr/bin/python${PYTHON_VERSION} /usr/bin/python \
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&& ln -sf /usr/bin/python${PYTHON_VERSION} /usr/bin/python3
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# Upgrade pip and install Python build dependencies
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RUN python -m pip install --upgrade pip setuptools wheel \
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&& python -m pip install \
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numpy \
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protobuf \
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pyyaml \
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requests \
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packaging \
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astor \
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decorator \
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paddle-bfloat \
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opt-einsum
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WORKDIR /build
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# Clone PaddlePaddle repository
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RUN git clone --depth 1 --branch ${PADDLE_VERSION} \
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https://github.com/PaddlePaddle/Paddle.git
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WORKDIR /build/Paddle
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# Install additional Python requirements for building
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RUN pip install -r python/requirements.txt || true
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# Create build directory
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RUN mkdir -p build
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WORKDIR /build/Paddle/build
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# Configure CMake for ARM64 + CUDA build
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# Note: Adjust CUDA_ARCH_NAME based on your GPU architecture
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# Common values: Auto, Ampere, Ada, Hopper
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RUN cmake .. \
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-GNinja \
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-DCMAKE_BUILD_TYPE=Release \
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-DPY_VERSION=${PYTHON_VERSION} \
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-DWITH_GPU=ON \
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-DWITH_TESTING=OFF \
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-DWITH_DISTRIBUTE=OFF \
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-DWITH_NCCL=OFF \
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-DWITH_MKL=OFF \
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-DWITH_MKLDNN=OFF \
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-DON_INFER=OFF \
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-DWITH_PYTHON=ON \
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-DWITH_AVX=OFF \
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-DCUDA_ARCH_NAME=Auto \
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-DCMAKE_EXPORT_COMPILE_COMMANDS=ON
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# Build PaddlePaddle (this takes 2-4 hours)
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RUN ninja -j$(nproc) || ninja -j$(($(nproc)/2)) || ninja -j4
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# Build the Python wheel
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WORKDIR /build/Paddle/build
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RUN ninja paddle_python
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# Create output directory and copy wheel
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RUN mkdir -p /output
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# The wheel should be in python/dist/
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WORKDIR /build/Paddle
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# Build wheel package
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RUN cd python && python setup.py bdist_wheel
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# Copy wheel to output
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RUN cp python/dist/*.whl /output/ 2>/dev/null || \
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cp build/python/dist/*.whl /output/ 2>/dev/null || \
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echo "Wheel location may vary, checking build artifacts..."
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# List what was built
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RUN ls -la /output/ && \
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echo "=== Build complete ===" && \
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echo "Wheel files:" && \
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find /build -name "*.whl" -type f 2>/dev/null
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# Default command: copy wheel to mounted volume
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CMD ["sh", "-c", "cp /output/*.whl /wheels/ 2>/dev/null && echo 'Wheel copied to /wheels/' && ls -la /wheels/ || echo 'No wheel found in /output, checking other locations...' && find /build -name '*.whl' -exec cp {} /wheels/ \\; && ls -la /wheels/"]
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