ARG PYTHON=python3
ARG PYTHON_VERSION=3.9.13
ARG MAMBA_VERSION=22.9.0-1
ARG OPEN_MPI_VERSION=4.1.4

# PyTorch Binaries
ARG TORCH_URL=https://aws-pytorch-unified-cicd-binaries.s3.us-west-2.amazonaws.com/r1.13.1_ec2/20221217-194030/54406b8eed7fbd61be629cb06229dfb7b6b2954e/torch-1.13.1%2Bcpu-cp39-cp39-linux_x86_64.whl
ARG TORCHVISION_VERSION=0.14.1+cpu
ARG TORCHAUDIO_VERSION=0.13.1+cpu
ARG TORCHDATA_VERSION=0.5.1
ARG TORCHSERVE_VERSION
ARG SM_TOOLKIT_VERSION

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

FROM ubuntu:20.04 AS base_image

ENV DEBIAN_FRONTEND=noninteractive \
    LD_LIBRARY_PATH="${LD_LIBRARY_PATH}:/usr/local/lib"

FROM base_image AS ec2

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

ARG PYTHON
ARG PYTHON_VERSION
ARG MAMBA_VERSION
ARG OPEN_MPI_VERSION

# PyTorch Passed arguments (URLs and Versions)
ARG TORCH_URL
ARG TORCHVISION_VERSION
ARG TORCHAUDIO_VERSION
ARG TORCHDATA_VERSION
ARG TORCHSERVE_VERSION

# Set Debian interaction
ARG DEBIAN_FRONTEND=noninteractive

# 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 TEMP=/home/model-server/tmp
# Set MKL_THREADING_LAYER=GNU to prevent issues between torch and numpy/mkl
ENV MKL_THREADING_LAYER=GNU
ENV DLC_CONTAINER_TYPE=inference

RUN apt-get update \
 && apt-get -y upgrade \
 && apt-get install -y --no-install-recommends software-properties-common \
 # && add-apt-repository ppa:openjdk-r/ppa \
 && apt-get update \
 && apt-get install -y --no-install-recommends \
    build-essential \
    ca-certificates \
    cmake \
    curl \
    emacs \
    git \
    jq \
    libcurl4-openssl-dev \
    libgl1-mesa-glx \
    libglib2.0-0 \
    libsm6 \
    libssl-dev \
    libxext6 \
    libxrender-dev \
    openjdk-11-jdk \
    openssl \
    unzip \
    vim \
    wget \
    zlib1g-dev \
 && rm -rf /var/lib/apt/lists/* \
 && apt-get clean

# https://github.com/docker-library/openjdk/issues/261 https://github.com/docker-library/openjdk/pull/263/files
RUN keytool -importkeystore -srckeystore /etc/ssl/certs/java/cacerts -destkeystore /etc/ssl/certs/java/cacerts.jks -deststoretype JKS -srcstorepass changeit -deststorepass changeit -noprompt; \
    mv /etc/ssl/certs/java/cacerts.jks /etc/ssl/certs/java/cacerts; \
    /var/lib/dpkg/info/ca-certificates-java.postinst configure;

RUN wget https://download.open-mpi.org/release/open-mpi/v4.1/openmpi-${OPEN_MPI_VERSION}.tar.gz \
 && gunzip -c openmpi-$OPEN_MPI_VERSION.tar.gz | tar xf - \
 && cd openmpi-$OPEN_MPI_VERSION \
 && ./configure --prefix=/home/.openmpi \
 && make all install \
 && cd .. \
 && rm openmpi-$OPEN_MPI_VERSION.tar.gz \
 && rm -rf openmpi-$OPEN_MPI_VERSION

# The ENV variables declared below are changed in the previous section
# Grouping these ENV variables in the first section causes
# ompi_info to fail. This is only observed in CPU containers
ENV PATH="$PATH:/home/.openmpi/bin"
ENV LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/home/.openmpi/lib/"
RUN ompi_info --parsable --all | grep mpi_built_with_cuda_support:value

# Install CondaForge miniconda
# Note: SSD Verification disabled as it breaks installs due to downgrading from py3.10 to py3.9
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 config --set ssl_verify False \
 && /opt/conda/bin/conda update -y conda \
 && /opt/conda/bin/conda install -c conda-forge \
    python=${PYTHON_VERSION} \
    cython \
    mkl \
    mkl-include \
    parso \
    typing \
    h5py \
    requests \
    # Below 2 are included in miniconda base, but not mamba so need to install
    conda-content-trust \
    charset-normalizer \
 && /opt/conda/bin/conda clean -ya

# symlink pip for OS use
RUN pip install --upgrade pip --trusted-host pypi.org --trusted-host files.pythonhosted.org \
 && ln -s /opt/conda/bin/pip /usr/local/bin/pip3

# Ensure PyTorch did not get installed from Conda
RUN pip uninstall -y torch torchvision torchaudio torchdata model-archiver multi-model-server

# Install AWS-PyTorch, and other torch packages
RUN pip install --no-cache-dir --extra-index-url https://download.pytorch.org/whl/cpu -U \
    boto3 \
    enum-compat==0.0.3 \
    opencv-python \
    scipy \
    "cryptography>3.2" \
    "ipython>=8.10.0,<9.0" \
    "awscli<2" \
    ${TORCH_URL} \
    torchaudio==${TORCHAUDIO_VERSION} \
    torchvision==${TORCHVISION_VERSION} \
    torchdata==${TORCHDATA_VERSION}

# Install TorchServe pypi dependencies directly from their requirements.txt file
# NOTE: This also brings in unnecessary cpu dependencies like nvgpu
# -> Numpy is higer version as required by torch
# -> PyYaml needs to be high pinned for awscli v1 (current v1 = 1.27.99)
RUN pip install --no-cache-dir -U -r https://raw.githubusercontent.com/pytorch/serve/v${TORCHSERVE_VERSION}/requirements/common.txt \
    "numpy>=1.22.2,<1.23" \
    "pyyaml>=5.4,<5.5" \
    torchserve==${TORCHSERVE_VERSION} \
    torch-model-archiver==${TORCHSERVE_VERSION}

# add necessary certificate for aws sdk cpp download
RUN mkdir -p /etc/pki/tls/certs && cp /etc/ssl/certs/ca-certificates.crt /etc/pki/tls/certs/ca-bundle.crt

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

COPY torchserve-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 -rf /tmp/tmp*

RUN curl -o /license.txt  https://aws-dlc-licenses.s3.amazonaws.com/pytorch-1.13/license.txt

# Removing the cache as it is needed for security verification
RUN rm -iRf /root/.cache

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

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

FROM ec2 AS sagemaker

LABEL maintainer="Amazon AI"
LABEL dlc_major_version="1"
LABEL com.amazonaws.sagemaker.capabilities.accept-bind-to-port=true
LABEL com.amazonaws.sagemaker.capabilities.multi-models=true

ARG PYTHON
ARG SM_TOOLKIT_VERSION
ARG TORCHSERVE_VERSION

ENV SAGEMAKER_SERVING_MODULE sagemaker_pytorch_serving_container.serving:main

# Install scikit-learn and pandas
RUN conda install -y -c conda-forge \
    scikit-learn \
    pandas

RUN pip install --no-cache-dir sagemaker-pytorch-inference==${SM_TOOLKIT_VERSION}

COPY torchserve-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*

# Removing the cache as it is needed for security verification
RUN rm -iRf /root/.cache

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