ARG PYTHON=python3
ARG PYTHON_VERSION=3.8.13
ARG MAMBA_VERSION=4.12.0-2

# PyTorch Binaries
ARG PT_INFERENCE_URL=https://aws-pytorch-unified-cicd-binaries.s3.us-west-2.amazonaws.com/r1.11.0_ec2/20221206-192811/6ead7f1c1f99d7cc5d15574e6698a855ddd7c823/torch-1.11.0%2Bcpu-cp38-cp38-linux_x86_64.whl
ARG PT_TORCHVISION_URL=https://download.pytorch.org/whl/cpu/torchvision-0.12.0%2Bcpu-cp38-cp38-linux_x86_64.whl
ARG PT_TORCHAUDIO_URL=https://download.pytorch.org/whl/cpu/torchaudio-0.11.0%2Bcpu-cp38-cp38-linux_x86_64.whl
ARG PT_TORCHDATA_URL=https://aws-pytorch-cicd-v3-binaries.s3.us-west-2.amazonaws.com/r1.11.0_v3_e3/aws-torchdata/torchdata-0.4.0-cp38-cp38-linux_x86_64.whl

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

FROM ubuntu:20.04 AS base_image

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

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
ARG PYTHON_VERSION
ARG OPEN_MPI_VERSION=4.0.1
ARG MAMBA_VERSION

# PyTorch Binaries
ARG PT_INFERENCE_URL
ARG PT_TORCHVISION_URL
ARG PT_TORCHAUDIO_URL
ARG PT_TORCHDATA_URL

ARG TS_VERSION=0.6.0

ENV LANG=C.UTF-8
ENV LD_LIBRARY_PATH="${LD_LIBRARY_PATH}:/opt/conda/lib"
ENV PATH=/opt/conda/bin:$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 \
# TODO: Remove systemd upgrade once it is updated in base image
 && apt-get -y upgrade --only-upgrade systemd \
 && 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://www.open-mpi.org/software/ompi/v4.0/downloads/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


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 \
    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 \
# 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

# Conda installs links for libtinfo.so.6 and libtinfo.so.6.2 both
# Which causes "/opt/conda/lib/libtinfo.so.6: no version information available" warning
# Removing link for libtinfo.so.6. This change is needed only for ubuntu 20.04-conda, and can be reverted
# once conda fixes the issue: https://github.com/conda/conda/issues/9680
RUN rm -rf /opt/conda/lib/libtinfo.so.6

# Install aws-sdk-cpp s3;transfer modules for torchdata
# pin aws-sdk-cpp modules
COPY pin_git_modules.py .
RUN git clone https://github.com/aws/aws-sdk-cpp --branch main
RUN python pin_git_modules.py --src $(pwd)/aws-sdk-cpp --date 2022-03-17
RUN rm pin_git_modules.py
# add necessary flags
RUN cd aws-sdk-cpp/ \
 && export LD_LIBRARY_PATH="/usr/lib/x86_64-linux-gnu/:${LD_LIBRARY_PATH}" \
 && mkdir sdk-build \
 && cd sdk-build \
 && cmake .. -DCMAKE_CXX_FLAGS="-lcurl" -DCMAKE_BUILD_TYPE=Release -DBUILD_ONLY="s3;transfer" -DAUTORUN_UNIT_TESTS=OFF \
 && make \
 && make install \
 && cd ../.. \
 && rm -rf aws-sdk-cpp

# Install AWS-PyTorch, and other torch packages
RUN 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 --no-cache-dir -U \
    "awscli<2" \
    boto3 \
    "cryptography>3.2" \
    enum-compat==0.0.3 \
    "ipython>=8.10,<9" \
    numpy==1.22.2 \
    "opencv-python>=4.6,<5" \
    packaging \
    "Pillow>=9.3.0" \
    "pyyaml>=5.4,<5.5" \
    scipy \
 && pip uninstall -y torch torchvision torchaudio torchdata \
 && pip install --no-cache-dir -U ${PT_INFERENCE_URL} ${PT_TORCHVISION_URL} ${PT_TORCHAUDIO_URL} ${PT_TORCHDATA_URL}

RUN pip uninstall -y model-archiver multi-model-server \
 && pip install torchserve==${TS_VERSION} \
 && pip install torch-model-archiver==${TS_VERSION}

# Install TorchServe pypi dependencies directly from their requirements.txt file
# NOTE: This also brings in unnecessary cpu dependencies like nvgpu
RUN pip install --no-cache-dir -U -r https://raw.githubusercontent.com/pytorch/serve/v${TS_VERSION}/requirements/common.txt
# Pillow is pinned in TS 0.6.0 to an obsolete version. To work around this, re-install in a separate line
RUN pip install --no-cache-dir -U "Pillow>=9.3.0,<10"

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-1.11/license.txt

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

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==2.0.10"

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*

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/"]