90 lines
3.9 KiB
Docker
Executable File
90 lines
3.9 KiB
Docker
Executable File
# 开发镜像（GPU）：Ubuntu 22.04 + CUDA 12.1 runtime + Node 22 + cadquery + PyTorch(cu121) + PyTorch3D
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# 用于装配检测「最近零件」服务端 GPU（scripts/assembly_nearest_gpu.py）
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# 宿主机需：NVIDIA 驱动 + nvidia-container-toolkit；构建不要求 GPU，运行需 --gpus
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#
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# 构建：docker build -t massive-point-cloud-app-dev:local -f docker/Dockerfile.dev.gpu .
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#
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# 无 NVIDIA 的机器请改用 docker/Dockerfile.dev（仅 CPU），compose 中去掉 gpus 与 ASSEMBLY_USE_GPU
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FROM nvidia/cuda:12.1.1-cudnn8-runtime-ubuntu22.04
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ENV DEBIAN_FRONTEND=noninteractive \
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PYTHON3_PATH=/usr/bin/python3 \
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ASSEMBLY_USE_GPU=1 \
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NVIDIA_VISIBLE_DEVICES=all \
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NVIDIA_DRIVER_CAPABILITIES=compute,utility
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# apt 换阿里云（国内构建加速）；需官方源时可在下方注释掉本段
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RUN set -eux; \
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if [ -f /etc/apt/sources.list ]; then \
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sed -i 's|http://archive.ubuntu.com/ubuntu|http://mirrors.aliyun.com/ubuntu|g' /etc/apt/sources.list; \
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sed -i 's|http://security.ubuntu.com/ubuntu|http://mirrors.aliyun.com/ubuntu|g' /etc/apt/sources.list; \
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fi
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RUN apt-get update && apt-get install -y --no-install-recommends \
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python3 \
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python3-pip \
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python3-dev \
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ca-certificates \
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curl \
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gnupg \
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libgl1 \
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libglib2.0-0 \
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libxrender1 \
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libxext6 \
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libsm6 \
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libice6 \
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libx11-6 \
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&& rm -rf /var/lib/apt/lists/*
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# CUDA runtime 镜像默认不带 nvidia-smi；装 Ubuntu 的 nvidia-utils（主版本与宿主机驱动大版本一致，如 535/550）
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# 构建失败时改：--build-arg NVIDIA_UTILS_MAJOR=550
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ARG NVIDIA_UTILS_MAJOR=535
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RUN apt-get update && apt-get install -y --no-install-recommends \
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"nvidia-utils-${NVIDIA_UTILS_MAJOR}" \
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&& rm -rf /var/lib/apt/lists/*
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RUN mkdir -p /etc/apt/keyrings \
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&& curl -fsSL https://deb.nodesource.com/gpgkey/nodesource-repo.gpg.key | gpg --dearmor -o /etc/apt/keyrings/nodesource.gpg \
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&& echo "deb [signed-by=/etc/apt/keyrings/nodesource.gpg] https://deb.nodesource.com/node_22.x nodistro main" > /etc/apt/sources.list.d/nodesource.list \
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&& apt-get update && apt-get install -y --no-install-recommends nodejs \
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&& rm -rf /var/lib/apt/lists/*
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RUN python3 -m pip install --no-cache-dir --upgrade pip setuptools wheel
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# cadquery（与 Dockerfile.dev 一致）
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ARG PIP_INDEX_URL=https://pypi.tuna.tsinghua.edu.cn/simple
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ARG PIP_DEFAULT_TIMEOUT=300
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COPY requirements-geometry.txt /tmp/requirements-geometry.txt
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RUN python3 -m pip install --no-cache-dir --break-system-packages \
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--default-timeout="${PIP_DEFAULT_TIMEOUT}" \
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--retries 10 \
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-i "${PIP_INDEX_URL}" \
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-r /tmp/requirements-geometry.txt \
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&& rm /tmp/requirements-geometry.txt \
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&& python3 -c "import cadquery; print('cadquery OK')"
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# PyTorch CUDA 12.1：默认清华镜像；覆盖示例：--build-arg TORCH_INDEX_URL=https://download.pytorch.org/whl/cu121
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ARG TORCH_INDEX_URL=https://mirrors.tuna.tsinghua.edu.cn/pytorch/whl/cu121
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RUN python3 -m pip install --no-cache-dir --break-system-packages \
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--default-timeout=300 --retries 10 \
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torch==2.3.1 torchvision==0.18.1 \
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--index-url "${TORCH_INDEX_URL}"
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# PyTorch3D 预编译轮仅 Meta 官方 CDN，无稳定国内镜像；加大超时。可本地下载 wheel 后 COPY + pip install。
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RUN python3 -m pip install --no-cache-dir --break-system-packages \
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--default-timeout=300 --retries 10 \
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-i https://pypi.tuna.tsinghua.edu.cn/simple \
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trimesh \
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&& python3 -m pip install --no-cache-dir --break-system-packages \
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--default-timeout=600 --retries 15 \
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pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/py310_cu121_pyt231/download.html
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RUN python3 -c "import torch; import pytorch3d; import trimesh; print('pytorch', torch.__version__, 'pytorch3d', pytorch3d.__version__)"
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WORKDIR /app
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RUN corepack enable && corepack prepare pnpm@latest --activate
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CMD ["node", "-e", "console.log('use docker-compose command')"]
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