Dockerfile.fedora29

FROM fedora:29

ARG TF_SERVING_VERSION_GIT_BRANCH=master
ARG TF_SERVING_VERSION_GIT_COMMIT=head

LABEL maintainer="smodeel@redhat.com"
LABEL tensorflow_serving_github_branchtag=${TF_SERVING_VERSION_GIT_BRANCH}
LABEL tensorflow_serving_github_commit=${TF_SERVING_VERSION_GIT_COMMIT}

# provide different URL here for different versions
ARG TF_URL=https://github.com/AICoE/tensorflow-wheels/releases/download/tensorflow_serving_api-r1.14-cpu-2019-08-14_132212/tensorflow-model-serving-r1.14-1.0-1.x86_64.rpm

# Install TF Serving pkg
RUN dnf install -y gcc gcc-c++ glibc-devel openssl-devel \
    && dnf install -y wget tree which findutils x86info cpuid dmidecode procps \
    && dnf install -y kernel-devel make automake autoconf swig zip unzip libtool binutils \
    && dnf clean all -y \
    && mkdir -p /usr/local/bin \
    && wget -q ${TF_URL} \
    && rpm -ivh tensorflow-model-serving-*.rpm


# Expose ports
# gRPC
EXPOSE 8500

# REST
EXPOSE 8501

# Set where models should be stored in the container
ENV MODEL_BASE_PATH=/models
RUN mkdir -p ${MODEL_BASE_PATH}

# The only required piece is the model name in order to differentiate endpoints
ENV MODEL_NAME=model

# 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 -e '#!/bin/bash \n\n \
ls -l ${MODEL_BASE_PATH} \n\n\
/usr/local/bin/tensorflow_model_server --port=8500 --rest_api_port=8501 \
--model_name=${MODEL_NAME} --model_base_path=${MODEL_BASE_PATH}/${MODEL_NAME} \
"$@"' > /usr/bin/tf_serving_entrypoint.sh \
&& chmod +x /usr/bin/tf_serving_entrypoint.sh

ENTRYPOINT ["/usr/bin/tf_serving_entrypoint.sh"]