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  Deep Quaternionary Convolutional Neural Networks
  =====================
  
  This repository contains code which reproduces experiments presented in
  the paper ...
  
  Requirements
  ------------
  
  Install requirements for experiments with pip:
  ```
  pip install numpy tensorflow-gpu keras
  ```
  Depending on your Python installation you might want to use anaconda or other tools.
  
  
  Installation
  ------------
  
  ```
  python setup.py install
  ```
  
  Experiments
  -----------
  
  1. Get help:
  
      ```
      python scripts/run.py train --help
      ```
  
  2. Run models:
  
      ```
      python scripts/run.py train -w WORKDIR --model {real,complex,quaternion} --seg{chiheb,parcollet} --sf STARTFILTER --nb NUMBEROFBLOCKSPERSTAGE
      ```
  
      Other arguments may be added as well; Refer to run.py train --help for
      
        - Optimizer settings
        - Dropout rate
        - Clipping
        - ...
  
  Citation
  --------
  
  Please cite our work as 
  
  ```
  
  ```