ModelScope/docker/Dockerfile.ubuntu

ARG BASE_IMAGE=reg.docker.alibaba-inc.com/modelscope/ubuntu:20.04-cuda11.3.0-cudnn8-devel
FROM $BASE_IMAGE
ARG DEBIAN_FRONTEND=noninteractive
ENV TZ=Asia/Shanghai
ENV CONDA_DIR /opt/conda
ENV PATH="${CONDA_DIR}/bin:${PATH}"
ENV arch=x86_64
SHELL ["/bin/bash", "-c"]
COPY docker/rcfiles /tmp/resources
RUN apt-get update && apt-get install -y --reinstall ca-certificates && \
    cp /tmp/resources/ubuntu20.04_sources.tuna /etc/apt/sources.list && \
    apt-get update && \
    apt-get install -y locales wget git  vim ffmpeg libsm6 tzdata language-pack-zh-hans ttf-wqy-microhei ttf-wqy-zenhei xfonts-wqy libxext6 build-essential ninja-build && \
    wget https://packagecloud.io/github/git-lfs/packages/debian/bullseye/git-lfs_3.2.0_amd64.deb/download -O ./git-lfs_3.2.0_amd64.deb && \
    dpkg -i ./git-lfs_3.2.0_amd64.deb && \
    rm -f ./git-lfs_3.2.0_amd64.deb && \
    locale-gen zh_CN && \
    locale-gen zh_CN.utf8 && \
    update-locale LANG=zh_CN.UTF-8 LC_ALL=zh_CN.UTF-8 LANGUAGE=zh_CN.UTF-8 && \
    ln -fs /usr/share/zoneinfo/Asia/Shanghai /etc/localtime && \
    dpkg-reconfigure --frontend noninteractive tzdata && \
    apt-get clean && \
    rm -rf /var/lib/apt/lists/*

ENV LANG=zh_CN.UTF-8 LANGUAGE=zh_CN.UTF-8 LC_ALL=zh_CN.UTF-8

#install and config python
ARG PYTHON_VERSION=3.7.13
RUN wget --quiet https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-${arch}.sh -O ./miniconda.sh && \
    /bin/bash  miniconda.sh -b -p /opt/conda && \
    rm  -f miniconda.sh && \
    ln  -s /opt/conda/etc/profile.d/conda.sh /etc/profile.d/conda.sh && \
    echo ". /opt/conda/etc/profile.d/conda.sh" >> ~/.bashrc && \
    cp /tmp/resources/conda.tuna  ~/.condarc && \
    source /root/.bashrc && \
    conda install --yes python==${PYTHON_VERSION} && \
    pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple

ARG USE_GPU=True

# install pytorch
ARG TORCH_VERSION=1.12.0
ARG CUDATOOLKIT_VERSION=11.3
RUN if [ "$USE_GPU" = "True" ] ; then \
        conda install --yes pytorch==$TORCH_VERSION torchvision torchaudio cudatoolkit=$CUDATOOLKIT_VERSION -c pytorch && conda clean --yes --all; \
    else \
        conda install pytorch==$TORCH_VERSION torchvision torchaudio cpuonly -c pytorch; \
    fi

# install tensorflow
ARG TENSORFLOW_VERSION=1.15.5
RUN if [ "$USE_GPU" = "True" ] ; then \
        pip install --no-cache-dir --use-deprecated=legacy-resolver tensorflow==$TENSORFLOW_VERSION -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html; \
    else \
        pip install --no-cache-dir tensorflow==$TENSORFLOW_VERSION; \
    fi

RUN if [ "$USE_GPU" = "True" ] ; then \
        CUDA_HOME=/usr/local/cuda TORCH_CUDA_ARCH_LIST="5.0 5.2 6.0 6.1 7.0 7.5 8.0 8.6" MMCV_WITH_OPS=1 MAX_JOBS=8 FORCE_CUDA=1 pip install --no-cache-dir mmcv-full && pip cache purge; \
    else \
        MMCV_WITH_OPS=1 MAX_JOBS=8 pip install --no-cache-dir mmcv-full && pip cache purge; \
    fi

# install modelscope
COPY requirements /var/modelscope
RUN pip install --no-cache-dir --upgrade pip && \
    pip install --no-cache-dir -r /var/modelscope/framework.txt -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html && \
    pip install --no-cache-dir -r /var/modelscope/audio.txt -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html && \
    pip install --no-cache-dir -r /var/modelscope/cv.txt -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html && \
    pip install --no-cache-dir -r /var/modelscope/multi-modal.txt -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html && \
    pip install --no-cache-dir -r /var/modelscope/nlp.txt -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html && \
    pip cache purge

# default shell bash
ENV SHELL=/bin/bash

# install special package
RUN pip install --no-cache-dir mmcls>=0.21.0 mmdet>=2.25.0 decord>=0.6.0 numpy==1.18.5 datasets==2.1.0

RUN if [ "$USE_GPU" = "True" ] ; then \
        pip install --no-cache-dir dgl-cu113 dglgo -f https://data.dgl.ai/wheels/repo.html; \
    else \
        pip install --no-cache-dir dgl dglgo -f https://data.dgl.ai/wheels/repo.html; \
    fi