DockerFile for creating a tensorflow server container by adding models in the path and running it on specified ports.

models.conf

model_config_list: {

  config: {
    name: "resnet_101",
    base_path: "/models/res2",
    model_platform: "tensorflow",
    model_version_policy: {
      specific: {
        versions: 1
      }
    }
  }
}

tf-server_DockerFile

ARG TF_SERVING_VERSION=latest
ARG TF_SERVING_BUILD_IMAGE=tensorflow/serving:${TF_SERVING_VERSION}-devel

FROM ${TF_SERVING_BUILD_IMAGE} as build_image
FROM ubuntu:16.04

ARG TF_SERVING_VERSION_GIT_BRANCH=master
ARG TF_SERVING_VERSION_GIT_COMMIT=head

LABEL maintainer="[email protected]"
LABEL tensorflow_serving_github_branchtag=${TF_SERVING_VERSION_GIT_BRANCH}
LABEL tensorflow_serving_github_commit=${TF_SERVING_VERSION_GIT_COMMIT}

RUN apt-get update && apt-get install -y --no-install-recommends \
        ca-certificates \
        && \
    apt-get clean && \
    rm -rf /var/lib/apt/lists/*

# Install TF Serving pkg
COPY --from=build_image /usr/local/bin/tensorflow_model_server /usr/bin/tensorflow_model_server

# 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}

COPY ./models/inception ${MODEL_BASE_PATH}/inception
COPY ./models/res2 ${MODEL_BASE_PATH}/res2
COPY ./models/ssd ${MODEL_BASE_PATH}/ssd

COPY ./models.conf /models/models.conf

# The only required piece is the model name in order to differentiate endpoints
ENTRYPOINT tensorflow_model_server --port=8500 --rest_api_port=8501 --model_config_file=/models/models.conf