########################################################
#  _____ ____ ____    ___
# | ____/ ___|___ \  |_ _|_ __ ___   __ _  __ _  ___
# |  _|| |     __) |  | || '_ ` _ \ / _` |/ _` |/ _ \
# | |__| |___ / __/   | || | | | | | (_| | (_| |  __/
# |_____\____|_____| |___|_| |_| |_|\__,_|\__, |\___|
#                                         |___/
#  ____           _
# |  _ \ ___  ___(_)_ __   ___
# | |_) / _ \/ __| | '_ \ / _ \
# |  _ <  __/ (__| | |_) |  __/
# |_| \_\___|\___|_| .__/ \___|
#                  |_|
########################################################

FROM ubuntu:20.04 AS base_image

ENV DEBIAN_FRONTEND=noninteractive \
    LD_LIBRARY_PATH="${LD_LIBRARY_PATH}:/usr/local/lib:/opt/conda/lib" \
    PATH="${PATH}:/opt/conda/bin"

RUN apt-get update \
 && apt-get upgrade -y \
 && apt-get autoremove -y \
 && apt-get clean \
 && rm -rf /var/lib/apt/lists/*

FROM base_image AS ec2

LABEL maintainer="Amazon AI"
LABEL dlc_major_version="1"

ARG PYTHON_VERSION=3.8.10
ARG MAMBA_VERSION=4.12.0-2
ARG MMS_VERSION=1.1.8
ARG MX_URL=https://framework-binaries.s3.us-west-2.amazonaws.com/mxnet/v1.9.0_mkl_blas/aws_mx-1.9.0b20221209-py3-none-manylinux2014_x86_64.whl

ENV PYTHONDONTWRITEBYTECODE=1 \
    PYTHONUNBUFFERED=1 \
    LD_LIBRARY_PATH="${LD_LIBRARY_PATH}:/usr/local/lib" \
    PYTHONIOENCODING=UTF-8 \
    LANG=C.UTF-8 \
    LC_ALL=C.UTF-8 \
    TEMP=/home/model-server/tmp \
    DEBIAN_FRONTEND=noninteractive \
    DLC_CONTAINER_TYPE=inference

# Set MKL_THREADING_LAYER=GNU to prevent issues between torch and numpy/mkl
ENV MKL_THREADING_LAYER=GNU

RUN apt-get update \
 && apt-get -y upgrade --only-upgrade systemd \
 && apt-get install -y --no-install-recommends \
    build-essential \
    ca-certificates \
    curl \
    emacs \
    git \
    libopencv-dev \
    openjdk-8-jdk-headless \
    openjdk-8-jdk \
    openjdk-8-jre \
    vim \
    wget \
    unzip \
    zlib1g-dev \
    libreadline-gplv2-dev \
    libncursesw5-dev \
    libssl-dev \
    libsqlite3-dev \
    libgdbm-dev \
    libc6-dev \
    libbz2-dev \
    tk-dev \
    libffi-dev \
 && apt-get clean \
 && rm -rf /var/lib/apt/lists/*

# install Python
RUN apt-get update \
 && apt-get install -y python3 python3-pip \
 && rm -rf /usr/bin/python /usr/bin/pip \
 && ln -s /usr/bin/python3 /usr/bin/python \
 && ln -s /usr/bin/pip3 /usr/bin/pip

WORKDIR /

RUN curl -L -o ~/mambaforge.sh https://github.com/conda-forge/miniforge/releases/download/${MAMBA_VERSION}/Mambaforge-${MAMBA_VERSION}-Linux-x86_64.sh \
 && chmod +x ~/mambaforge.sh \
 && ~/mambaforge.sh -b -p /opt/conda \
 && rm ~/mambaforge.sh \
 && /opt/conda/bin/conda install -c conda-forge \
    mkl \
    mkl-include \
 # Upstream conda looks to have moved to 4.13 which is incompatible with mamba 0.22.1 and will fail the conda-forge installs.
 # having "conda update conda" before the "conda -c conda-forge" commands will automatically update conda to 4.13.
 # Moving conda update conda" after the "conda -c conda-forge" commands keep conda at 4.12 but will update other packages using
 # the current conda 4.12
 && /opt/conda/bin/conda update -y conda \
 && /opt/conda/bin/conda clean -ya

RUN pip install --upgrade pip --trusted-host pypi.org --trusted-host files.pythonhosted.org \
 && pip install --no-cache-dir \
    "awscli<2" \
    boto3 \
    ${MX_URL} \
    gluonnlp==0.10.0 \
    gluoncv==0.8.0 \
    multi-model-server==$MMS_VERSION \
    "numpy<1.20" \
    onnx>=1.13.0 \
    # Protobuf >=3.21 results in protobuf errors version mismatch errors with framework and other packages.
    "protobuf>=3.20.2,<3.21" \
    "wheel>=0.38.0" \
    # setuptools is installed while the installation of python
    "setuptools>=66.0.0" \
    # Upper bound pin matplotlib, as it creates dependency conflict with numpy
    "matplotlib<3.7"

# This is here to make our installed version of OpenCV work.
# https://stackoverflow.com/questions/29274638/opencv-libdc1394-error-failed-to-initialize-libdc1394
# TODO: Should we be installing OpenCV in our image like this? Is there another way we can fix this?
RUN ln -s /dev/null /dev/raw1394

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

COPY mms-ec2-entrypoint.py /usr/local/bin/dockerd-entrypoint.py
COPY config.properties /home/model-server

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

COPY deep_learning_container.py /usr/local/bin/deep_learning_container.py

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

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* \
 && rm -iRf ${HOME_DIR}/.cache

RUN curl https://aws-dlc-licenses.s3.amazonaws.com/aws-mx-1.9.0/license.txt -o /license.txt

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

#################################################################
#  ____                   __  __       _
# / ___|  __ _  __ _  ___|  \/  | __ _| | _____ _ __
# \___ \ / _` |/ _` |/ _ \ |\/| |/ _` | |/ / _ \ '__|
#  ___) | (_| | (_| |  __/ |  | | (_| |   <  __/ |
# |____/ \__,_|\__, |\___|_|  |_|\__,_|_|\_\___|_|
#              |___/
#  ___                              ____           _
# |_ _|_ __ ___   __ _  __ _  ___  |  _ \ ___  ___(_)_ __   ___
#  | || '_ ` _ \ / _` |/ _` |/ _ \ | |_) / _ \/ __| | '_ \ / _ \
#  | || | | | | | (_| | (_| |  __/ |  _ <  __/ (__| | |_) |  __/
# |___|_| |_| |_|\__,_|\__, |\___| |_| \_\___|\___|_| .__/ \___|
#                      |___/                        |_|
#################################################################

FROM ec2 AS sagemaker

LABEL maintainer="Amazon AI"
LABEL dlc_major_version="1"

# 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_VERSION=3.8.10

WORKDIR /

RUN pip install --no-cache-dir \
    sagemaker-mxnet-inference

RUN pip install --no-cache-dir \
    "sagemaker-inference==1.6.1"

COPY mms-entrypoint.py /usr/local/bin/dockerd-entrypoint.py

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

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* \
 && rm -iRf ${HOME_DIR}/.cache

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