MastersThesis/src/paddle_ocr/Dockerfile.build-paddle

# Dockerfile.build-paddle - Build PaddlePaddle GPU wheel for ARM64
#
# This Dockerfile compiles PaddlePaddle from source with CUDA support for ARM64.
# The resulting wheel can be used in Dockerfile.gpu for ARM64 GPU acceleration.
#
# Build time: 2-4 hours depending on hardware
# Output: /output/paddlepaddle_gpu-*.whl
#
# Usage:
#   docker compose run build-paddle
#   # or
#   docker build -f Dockerfile.build-paddle -t paddle-builder .
#   docker run -v ./wheels:/output paddle-builder

FROM nvidia/cuda:12.4.1-cudnn-devel-ubuntu22.04

LABEL maintainer="Sergio Jimenez"
LABEL description="PaddlePaddle GPU wheel builder for ARM64"

# Build arguments
ARG PADDLE_VERSION=v3.0.0
ARG PYTHON_VERSION=3.11

# Environment setup
ENV DEBIAN_FRONTEND=noninteractive
ENV PYTHONUNBUFFERED=1

# Install build dependencies
RUN apt-get update && apt-get install -y --no-install-recommends \
    # Python
    python${PYTHON_VERSION} \
    python${PYTHON_VERSION}-dev \
    python${PYTHON_VERSION}-venv \
    python3-pip \
    # Build tools
    build-essential \
    cmake \
    ninja-build \
    git \
    wget \
    curl \
    pkg-config \
    # Libraries
    libssl-dev \
    libffi-dev \
    zlib1g-dev \
    libbz2-dev \
    libreadline-dev \
    libsqlite3-dev \
    liblzma-dev \
    libncurses5-dev \
    libncursesw5-dev \
    libgflags-dev \
    libgoogle-glog-dev \
    libprotobuf-dev \
    protobuf-compiler \
    patchelf \
    # Additional dependencies for Paddle
    libopenblas-dev \
    liblapack-dev \
    swig \
    && rm -rf /var/lib/apt/lists/* \
    && ln -sf /usr/bin/python${PYTHON_VERSION} /usr/bin/python \
    && ln -sf /usr/bin/python${PYTHON_VERSION} /usr/bin/python3

# Upgrade pip and install Python build dependencies
RUN python -m pip install --upgrade pip setuptools wheel \
    && python -m pip install \
    numpy \
    protobuf \
    pyyaml \
    requests \
    packaging \
    astor \
    decorator \
    paddle-bfloat \
    opt-einsum

WORKDIR /build

# Clone PaddlePaddle repository
RUN git clone --depth 1 --branch ${PADDLE_VERSION} \
    https://github.com/PaddlePaddle/Paddle.git

WORKDIR /build/Paddle

# Install additional Python requirements for building
RUN pip install -r python/requirements.txt || true

# Create build directory
RUN mkdir -p build
WORKDIR /build/Paddle/build

# Configure CMake for ARM64 + CUDA build
#
# CUDA_ARCH is auto-detected from host GPU and passed via docker-compose.
# To detect: nvidia-smi --query-gpu=compute_cap --format=csv,noheader
# Example: 12.1 -> use "90" (Hopper, closest supported), 9.0 -> use "90"
#
# Build time: ~30-60 min with single arch vs 2-4 hours with all archs

ARG CUDA_ARCH=90
RUN echo "Building for CUDA architecture: sm_${CUDA_ARCH}"

RUN cmake .. \
    -GNinja \
    -DCMAKE_BUILD_TYPE=Release \
    -DPY_VERSION=${PYTHON_VERSION} \
    -DWITH_GPU=ON \
    -DWITH_TESTING=OFF \
    -DWITH_DISTRIBUTE=OFF \
    -DWITH_NCCL=OFF \
    -DWITH_MKL=OFF \
    -DWITH_MKLDNN=OFF \
    -DON_INFER=OFF \
    -DWITH_PYTHON=ON \
    -DWITH_AVX=OFF \
    -DCUDA_ARCH_NAME=Manual \
    -DCUDA_ARCH_BIN="${CUDA_ARCH}" \
    -DCMAKE_CUDA_ARCHITECTURES="${CUDA_ARCH}" \
    -DCMAKE_EXPORT_COMPILE_COMMANDS=ON

# Build PaddlePaddle (this takes 2-4 hours)
RUN ninja -j$(nproc) || ninja -j$(($(nproc)/2)) || ninja -j4

# Build the Python wheel
WORKDIR /build/Paddle/build
RUN ninja paddle_python

# Create output directory and copy wheel
RUN mkdir -p /output

# The wheel should be in python/dist/
WORKDIR /build/Paddle

# Build wheel package
RUN cd python && python setup.py bdist_wheel

# Copy wheel to output
RUN cp python/dist/*.whl /output/ 2>/dev/null || \
    cp build/python/dist/*.whl /output/ 2>/dev/null || \
    echo "Wheel location may vary, checking build artifacts..."

# List what was built
RUN ls -la /output/ && \
    echo "=== Build complete ===" && \
    echo "Wheel files:" && \
    find /build -name "*.whl" -type f 2>/dev/null

# Default command: copy wheel to mounted volume
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/"]