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Keras/en

"Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano." (Source: Keras website)

If you are porting a Keras program to one of our clusters, you should follow our tutorial on the subject.

Installing

  1. Install TensorFlow, CNTK, or Theano in a Python virtual environment.
  2. Activate the Python virtual environment (named $HOME/tensorflow in our example). 
    source $HOME/tensorflow/bin/activate
  3. Install Keras in your virtual environment. 
    pip install keras

R package

This section details how to install Keras for R and use TensorFlow as the backend.

  1. Install TensorFlow for R by following these instructions.
  2. Follow the instructions from the parent section.
  3. Load the required modules. 
    module load gcc/7.3.0 r/3.5.2
  4. Launch R. 
    R
  5. In R, install the Keras package with devtools. 
    devtools::install_github('rstudio/keras')

Important Note

You are then good to go. Do not call install_keras() in R, as Keras and TensorFlow have already been installed in your virtual environment with pip. To use the Keras package installed in your virtual environment, enter the following commands in R after the environment has been activated.

library(keras)
use_virtualenv(Sys.getenv('VIRTUAL_ENV'))

References