FROM ubuntu:16.04

LABEL maintainer="Amazon AI"
LABEL dlc_major_version="2"
# Specify accept-bind-to-port LABEL for inference pipelines to use SAGEMAKER_BIND_TO_PORT
# https://docs.aws.amazon.com/sagemaker/latest/dg/inference-pipeline-real-time.html
LABEL com.amazonaws.sagemaker.capabilities.accept-bind-to-port=true
# Specify multi-models LABEL to indicate container is capable of loading and serving multiple models concurrently
# https://docs.aws.amazon.com/sagemaker/latest/dg/build-multi-model-build-container.html
LABEL com.amazonaws.sagemaker.capabilities.multi-models=true

ARG PYTHON=python3
ARG PYTHON_VERSION=3.6.13
ARG MMS_VERSION=1.1.2

# See http://bugs.python.org/issue19846
ENV LANG C.UTF-8
ENV LD_LIBRARY_PATH /opt/conda/lib/:$LD_LIBRARY_PATH
ENV PATH /opt/conda/bin:$PATH
ENV SAGEMAKER_SERVING_MODULE sagemaker_pytorch_serving_container.serving:main
ENV TEMP=/home/model-server/tmp

RUN apt-get update && apt-get install -y --no-install-recommends \
    build-essential \
    ca-certificates \
    cmake \
    curl \
    emacs \
    git \
    jq \
    libgl1-mesa-glx \
    libglib2.0-0 \
    libsm6 \
    libxext6 \
    libxrender-dev \
    openjdk-8-jdk-headless \
    vim \
    wget \
    unzip \
    zlib1g-dev

RUN curl -L -o ~/miniconda.sh https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh \
 && chmod +x ~/miniconda.sh \
 && ~/miniconda.sh -b -p /opt/conda \
 && rm ~/miniconda.sh \
 && /opt/conda/bin/conda update conda \
 && /opt/conda/bin/conda install -c conda-forge \
    python=$PYTHON_VERSION \
 && /opt/conda/bin/conda install -y \
    # conda 4.9.2 requires ruamel_yaml to be installed. Currently pinned at latest.
    ruamel_yaml==0.15.100 \
    cython==0.29.12 \
    ipython==7.7.0 \
    mkl-include==2019.4 \
    mkl==2019.4 \
    numpy==1.16.4 \
    scipy==1.3.0 \
    typing==3.6.4 \
 && /opt/conda/bin/conda clean -ya

RUN conda install -c \
    conda-forge \
    opencv==4.0.1 \
 && conda install -y \
    scikit-learn==0.21.2 \
    pandas==0.25.0 \
    h5py==2.9.0 \
    requests==2.22.0 \
 && conda clean -ya \
 && pip install --upgrade pip --trusted-host pypi.org --trusted-host files.pythonhosted.org \
 && ln -s /opt/conda/bin/pip /usr/local/bin/pip3 \
 && pip install multi-model-server==$MMS_VERSION

 # Uninstall and re-install torch and torchvision from the PyTorch website
RUN pip uninstall -y torch \
 && pip install --no-cache-dir -U https://pytorch-aws.s3-us-west-2.amazonaws.com/pytorch-1.5.1/Inference/cpu/torch-1.5.1-cp36-cp36m-manylinux1_x86_64.whl \
 && pip uninstall -y torchvision \
 && pip install --no-deps --no-cache-dir -U \
    https://torchvision-build.s3.amazonaws.com/1.5.1/cpu/torchvision-0.6.1-cp36-cp36m-linux_x86_64.whl

RUN useradd -m model-server \
 && mkdir -p /home/model-server/tmp \
 && chown -R model-server /home/model-server

COPY mms-entrypoint.py /usr/local/bin/dockerd-entrypoint.py
COPY config.properties /home/model-server

RUN chmod +x /usr/local/bin/dockerd-entrypoint.py

ADD https://raw.githubusercontent.com/aws/deep-learning-containers/master/src/deep_learning_container.py /usr/local/bin/deep_learning_container.py

RUN chmod +x /usr/local/bin/deep_learning_container.py

RUN pip install --no-cache-dir "sagemaker-pytorch-inference<2"

RUN curl https://aws-dlc-licenses.s3.amazonaws.com/pytorch-1.5.1/license.txt -o /license.txt

# install PyYAML>=5.4,<5.5 to avoid conflict with latest awscli
RUN conda install -y -c conda-forge "PyYAML>=5.4,<5.5"

RUN pip install \
    "Pillow>=8.3.2,<8.4" \
    "awscli<2" \
    # cryptography required by pyopenssl and paramiko, <3.3.2 has safety vulnerabilities
    "cryptography>=3.3.2"

RUN HOME_DIR=/root \
 && curl -o ${HOME_DIR}/oss_compliance.zip https://aws-dlinfra-utilities.s3.amazonaws.com/oss_compliance.zip \
 && unzip ${HOME_DIR}/oss_compliance.zip -d ${HOME_DIR}/ \
 && cp ${HOME_DIR}/oss_compliance/test/testOSSCompliance /usr/local/bin/testOSSCompliance \
 && chmod +x /usr/local/bin/testOSSCompliance \
 && chmod +x ${HOME_DIR}/oss_compliance/generate_oss_compliance.sh \
 && ${HOME_DIR}/oss_compliance/generate_oss_compliance.sh ${HOME_DIR} ${PYTHON} \
 && rm -rf ${HOME_DIR}/oss_compliance*

EXPOSE 8080 8081
ENTRYPOINT ["python", "/usr/local/bin/dockerd-entrypoint.py"]
CMD ["multi-model-server", "--start", "--mms-config", "/home/model-server/config.properties"]