Skip to content

devid-rudesheim/libtensorflow-pharo-bindings

 
 

Repository files navigation

libtensorflow-pharo-bindings

This is a fork of https://github.com/Cuis-Smalltalk/Machine-Learning for Pharo. This library was also ported to VA Smalltalk : https://github.com/vasmalltalk/tensorflow-vast

You will need a 64 bits Pharo VM in order to run the code. The code has only be tested on Pharo 9.0 on macOS and Windows with TensorFlow 1.15.5: https://github.com/tensorflow/tensorflow/releases/tag/v1.15.5.

Installation

To install the project on your Pharo image you can execute the following script:

    Metacello new
    	githubUser: 'PolyMathOrg' project: 'libtensorflow-pharo-bindings' commitish: 'master' path: '';
    	baseline: 'LibTensorFlowPharoBinding';
    	load

Alternatively you can use Iceberg to load the code of this repository (See the video here: https://www.youtube.com/watch?v=U6Ttcc1KJUg&feature=youtu.be)

To add the project to your baseline just add this:

    spec
    	baseline: 'LibTensorFlowPharoBinding'
    	with: [ spec repository: 'github://PolyMathOrg/libtensorflow-pharo-bindings' ]

Installation of TensorFlow C API on MacOS

  • Install TensorFlow C API on your computer. On macOS, the simpliest way to do that is to use Brew: brew install tensorflow If you don't use brew, check the installation guide
  • check method TensorFlowCAPI>>macModulenameto put the path to where Tensorflow libraries are located on your computer:
TensorFlowCAPI>>macModulename
  ^ '/usr/local/Cellar/libtensorflow/1.15.5/lib/libtensorflow.so'

Installation of TensorFlow C API on Windows

Installation of TensorFlow C API on Linux

  • Check the Tensorflow for C installation guide
  • check method TensorFlowCAPI>>unixModulenameto put the path to where Tensorflow libraries are located on your computer:
TensorFlowCAPI>>unixModulename
  ^ '/usr/local/lib/libtensorflow.so'

About

TensorFlow library bindings for Pharo

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Smalltalk 100.0%