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Haskell TensorFlow Library Setup Guide

Last update: 02/26/2019

Library Information

The Haskell Interface to TensorFlow C Library

https://github.com/tensorflow/haskell

Supported Running Environments

  • Stack (covered by this guide)
    • latest TensorFlow Haskell git version
    • TensorFlow C library 1.9.0
    • stack resolver: lts-12.26
    • GHC 8.4.4
  • Nix
    • latest TensorFlow Haskell git version
    • TensorFlow C library 1.9.0
    • stack resolver: lts-12.26
    • GHC 8.4.4
  • Docker
    • GPU support
    • TensorFlow Haskell version 0.2.0.0
    • TensorFlow C library 1.9.0
    • stack resolver: lts-11.9
    • GHC 8.2.2

Setup Compiling Environment on Native CentOS with Stack

To automatically setup the environment, check CentOS 7.6 Environment Setup Script. Manual steps are as follows:

Install Stack

curl -sSL https://get.haskellstack.org/ | sh

Install Protocol Buffers

The rpm version on CentOS 7.6 is too old (2.5.0-8.el7 released in 2015). All Fedora rpms cannot be installed on CentOS due to broken dependencies. To compile the latest version of protobuf from git:

sudo yum install autoconf automake libtool unzip gcc-c++ git -y
git clone https://github.com/google/protobuf.git
cd protobuf
git submodule update --init --recursive
./autogen.sh
./configure --prefix=/usr
make
sudo make install

Install Snappy

snappy is usually installed. To ensure the installation:

sudo yum install snappy -y

Install TensorFlow C Library

wget https://storage.googleapis.com/tensorflow/libtensorflow/libtensorflow-cpu-linux-x86_64-1.9.0.tar.gz
tar zxf libtensorflow-cpu-linux-x86_64-1.9.0.tar.gz
sudo cp -r lib/* /usr/lib64/
sudo cp -r include/* /usr/include/
sudo ldconfig

Develop Your Haskell Project with Stack Using TensorFlow

  1. Create your Haskell project
stack new my-project
cd my-project
  1. Edit the stack.yaml file
resolver: lts-12.26

extra-deps:
- git: https://github.com/tensorflow/haskell.git
  commit: c7426a3f00d959ccff8bd631e34ba4c805f7e654
  subdirs:
      - tensorflow
      - tensorflow-ops
      - tensorflow-core-ops
      - tensorflow-logging
      - tensorflow-proto
      - tensorflow-opgen
      - tensorflow-test
      - tensorflow-mnist
      - tensorflow-mnist-input-data
  1. Compile
stack setup
stack build
  1. Run your project
stack exec my-project-exe