This repository contains a Ruby API for utilizing TensorFlow.
Everything is at RubyDoc.
You can also generate docs by
bundle exec rake doc.
It's easiest to get started using the prebuilt Docker container.
docker run --rm -it nethsix/ruby-tensorflow-ubuntu:0.0.1 /bin/bash
cd /repos/tensorflow.rb/ bundle exec rspec
Image Classification Tutorial:
cd /repos/tensorflow.rb/image/ cat README
For more details about all the fun machine-learning stuff already pre-installed, see: https://hub.docker.com/r/nethsix/ruby-tensorflow-ubuntu/
Outside of Docker
Alternatively, you can install outside of a Docker container by following the following steps.
All the dependencies mentioned above must be installed in your system before you proceed further.
Clone and Install TensorFlow
This package depends on the TensorFlow shared libraries, in order to compile these libraries do the following:
git clone --recurse-submodules https://github.com/tensorflow/tensorflow cd tensorflow ./configure
This command clones the repository and a few sub modules. After this you should do:
bazel build -c opt //tensorflow:libtensorflow.so
This command takes in the order of 10-15 minutes to run and creates a shared library. When finished, copy the newly generated libtensorflow.so shared library:
# Linux sudo cp bazel-bin/tensorflow/libtensorflow.so /usr/lib/ # OSX sudo cp bazel-bin/tensorflow/libtensorflow.so /usr/local/lib export LIBRARY_PATH=$PATH:/usr/local/lib (may be required)
Clone and install this Ruby API:
git clone https://github.com/somaticio/tensorflow.rb.git cd tensorflow.rb/ext/sciruby/tensorflow_c ruby extconf.rb make make install # Creates ../lib/ruby/site_ruby/X.X.X/<arch>/tf/Tensorflow.bundle (.so Linux) cd ./../../.. bundle exec rake install
The last command is for installing the gem.
Run tests and verify install
bundle exec rake spec
This command is to run the tests.
I have also made a make shift install script in tools directory. You are free to use it, but it still needs some work and its best if you follow the installation procedure above or use docker. You are welcome to make improvements to the script.
You can run tensorboard on tensorflow.rb too. Just take a look at tensorboard.md file.
Copyright (c) 2016, Arafat Dad Khan. somatic
All rights reserved.