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Building XGBoost Serving from source

Prerequisites

To build and use XGBoost Serving, you need to set up some prerequisites.

Packages

We develop XGBoost Serving under Ubuntu 16.04, so execute the following command to install the required packages:

apt-get update && apt-get install -y --no-install-recommends \
        automake \
        build-essential \
        ca-certificates \
        curl \
        git \
        libcurl3-dev \
        libfreetype6-dev \
        libpng-dev \
        libtool \
        libzmq3-dev \
        mlocate \
        openjdk-8-jdk\
        openjdk-8-jre-headless \
        pkg-config \
        python-dev \
        software-properties-common \
        swig \
        unzip \
        wget \
        zip \
        zlib1g-dev \
        iproute2 \
        linux-tools-generic \
        xdot \
        ghostscript \
        libc-dbg \
        ssh \
        openssl \
        libssl-dev

Bazel

XGBoost Serving requires Bazel 0.24.1 or higher. You can find the Bazel installation instructions here.

If you have prerequisites for Bazel, those instructions consist of the steps:

  1. Download the relevant binary from here. Let's say you download bazel-0.24.1-installer-linux-x86_64.sh. You would execute:
chmod +x bazel-0.24.1-installer-linux-x86_64.sh
./bazel-0.24.1-installer-linux-x86_64.sh --user
  1. Set up your environment. Put this in your ~/.bashrc.
export PATH="$PATH:$HOME/bin"

CMake

XGBoost Serving requires CMake 3.14 or higher to build XGBoost. You can find the CMake binary from here. Suppose you download cmake-3.18.0-Linux-x86_64.sh, run the following command to install CMake:

chmod +x cmake-3.18.0-Linux-x86_64.sh
./cmake-3.18.0-Linux-x86_64.sh --skip-license --prefix=/usr

Building

Clone the XGBoost Serving repository

git clone https://github.com/hzy001/xgboost-serving.git
cd xgboost-serving

Note that these instructions will install the latest xgboost branch of XGBoost Serving. If you want to install a specific branch(such as a release branch), just checkout the relevant branch.

Building the model server

To build the tensorflow_model_server, run the following command:

bazel build -c opt //tensorflow_serving/model_servers:tensorflow_model_server

Binaries are placed in the bazel-bin directory, and can be run using a command like:

./bazel-bin/tensorflow_serving/model_servers/tensorflow_model_server

Building the Python API PIP package

Run the following command to generate the build_pip_package executable:

bazel build -c opt //tensorflow_serving/tools/pip_package:build_pip_package

Binaries are placed in the bazel-bin directory, and you can run the following command to generate the Python API PIP package:

./bazel-bin/tensorflow_serving/tools/pip_package/build_pip_package $(pwd)

If the command finishes successfully, you will see the tensorflow_serving_api-2.0.0-py2.py3-none-any.whl package in the current directory and you can install this package to use the tensorflow serving apis.