FROM ubuntu:18.04 LABEL maintainer="Amazon AI" LABEL dlc_major_version="4" # Specify 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 LABEL com.amazonaws.sagemaker.capabilities.multi-models=true # Add arguments to achieve the version, python and url ARG PYTHON=python3 ARG PYTHON_PIP=python3-pip ARG PIP=pip3 ARG PYTHON_VERSION=3.6.13 ARG TFS_SHORT_VERSION=1.15 ARG TF_S3_URL=https://tensorflow-aws.s3-us-west-2.amazonaws.com ARG TF_MODEL_SERVER_SOURCE=${TF_S3_URL}/1.15.3/Serving/CPU-WITH-MKL/tensorflow_model_server # See http://bugs.python.org/issue19846 ENV LANG=C.UTF-8 # Python won’t try to write .pyc or .pyo files on the import of source modules ENV PYTHONDONTWRITEBYTECODE=1 ENV PYTHONUNBUFFERED=1 ENV SAGEMAKER_TFS_VERSION="${TFS_SHORT_VERSION}" ENV PATH="$PATH:/sagemaker" ENV LD_LIBRARY_PATH='/usr/local/lib:$LD_LIBRARY_PATH' ENV MODEL_BASE_PATH=/models # The only required piece is the model name in order to differentiate endpoints ENV MODEL_NAME=model # To prevent user interaction when installing time zone data package ENV DEBIAN_FRONTEND=noninteractive # nginx + njs RUN apt-get update \ && apt-get -y install --no-install-recommends \ curl \ gnupg2 \ ca-certificates \ emacs \ git \ unzip \ wget \ build-essential \ vim \ libssl1.1 \ openssl \ && curl -s http://nginx.org/keys/nginx_signing.key | apt-key add - \ && echo 'deb http://nginx.org/packages/ubuntu/ bionic nginx' >> /etc/apt/sources.list \ && apt-get update \ && apt-get -y install --no-install-recommends \ nginx \ nginx-module-njs \ && apt-get clean \ && rm -rf /var/lib/apt/lists/* RUN apt-get update \ && apt-get install -y --no-install-recommends \ libbz2-dev \ libc6-dev \ libffi-dev \ libgdbm-dev \ libncursesw5-dev \ libreadline-gplv2-dev \ libsqlite3-dev \ libssl-dev \ tk-dev \ && rm -rf /var/lib/apt/lists/* \ && apt-get clean RUN wget https://www.python.org/ftp/python/$PYTHON_VERSION/Python-$PYTHON_VERSION.tgz \ && tar -xvf Python-$PYTHON_VERSION.tgz \ && cd Python-$PYTHON_VERSION \ && ./configure && make && make install \ && rm -rf ../Python-$PYTHON_VERSION* RUN ${PIP} --no-cache-dir install --upgrade \ pip \ setuptools # Some TF tools expect a "python" binary RUN ln -s $(which python3) /usr/local/bin/python \ && ln -s $(which pip3) /usr/bin/pip # cython, falcon, gunicorn, grpc RUN ${PIP} install --no-cache-dir \ "awscli<2" \ "pyYAML>=5.4,<5.5" \ boto3 \ cython==0.29.12 \ falcon==2.0.0 \ gunicorn==20.0.4 \ gevent==1.4.0 \ requests==2.22.0 \ grpcio==1.24.1 \ protobuf==3.10.0 \ # using --no-dependencies to avoid installing tensorflow binary && ${PIP} install --no-dependencies --no-cache-dir \ tensorflow-serving-api==1.15.0 COPY sagemaker /sagemaker RUN curl ${TF_S3_URL}/MKL-Libraries/libiomp5.so -o /usr/local/lib/libiomp5.so \ && curl ${TF_S3_URL}/MKL-Libraries/libmklml_intel.so -o /usr/local/lib/libmklml_intel.so RUN curl ${TF_MODEL_SERVER_SOURCE} -o /usr/bin/tensorflow_model_server \ && chmod 555 /usr/bin/tensorflow_model_server # Expose ports # gRPC and REST EXPOSE 8500 8501 # Set where models should be stored in the container RUN mkdir -p ${MODEL_BASE_PATH} # Create a script that runs the model server so we can use environment variables # while also passing in arguments from the docker command line RUN echo '#!/bin/bash \n\n' > /usr/bin/tf_serving_entrypoint.sh \ && echo '/usr/bin/tensorflow_model_server --port=8500 --rest_api_port=8501 --model_name=${MODEL_NAME} --model_base_path=${MODEL_BASE_PATH}/${MODEL_NAME} "$@"' >> /usr/bin/tf_serving_entrypoint.sh \ && chmod +x /usr/bin/tf_serving_entrypoint.sh 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* RUN curl https://aws-dlc-licenses.s3.amazonaws.com/tensorflow/license.txt -o /license.txt CMD ["/usr/bin/tf_serving_entrypoint.sh"]