Installation/Getting Started

This page will help you get started with OpenDeep. You'll be up and running in a jiffy!

What is OpenDeep?

OpenDeep is a general purpose commercial and research grade deep learning library for Python built from the ground up in Theano that brings unprecedented flexibility for both industry data scientists and cutting-edge researchers.

Use OpenDeep to:

  • Quickly prototype complex networks through a focus on complete modularity and containers similar to Torch.
  • Configure and train existing state-of-the-art models.
  • Write your own models from scratch in Theano and plug into OpenDeep for easy training and dataset integration.
  • Use visualization and debugging tools to see exactly what is happening with your neural net architecture.
  • Plug into your existing Numpy/Scipy/Pandas/Scikit-learn pipeline.
  • Run on the CPU or GPU.

This library is currently undergoing rapid development and is in its alpha stages.



  • Theano: Theano and its dependencies are required to use OpenDeep. You need to install the bleeding-edge version, which has installation instructions here.

  • Pillow (PIL): image manipulation functionality.

  • PyYAML (optional): used for YAML parsing of config files.

  • Bokeh (optional): if you want live charting/plotting of values during training or testing. Make sure you can use the bokeh-server command.

  • NLTK (optional): if you want NLP functions like word tokenization.

Install from source

Because OpenDeep is still in alpha, you have to install via Here are the steps to install:

  1. Navigate to your desired installation directory and download the github repository like so:
git clone
  1. Navigate to the top-level folder (should be named OpenDeep and contain the file and run with develop mode like so:
cd opendeep
python develop

Using python develop instead of the normal python install allows you to update the repository files by pulling from git and have the whole package update! No need to reinstall.

That's it! Now you should be able to import opendeep into python modules.

Check out some Tutorials in the navigation bar on the left.

To learn how to use existing models, check out Tutorial: First Steps.