** Currently, you need the following version of theano to use the sparse implementation:
https://bitbucket.org/ynd/theano/overview

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SCRIPTS DESCRIPTIONS:
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** model.py contains all the tools to build, train and evaluate a model.

** datatools.py shows how to build the necessary data file (sparse matrices, dictionnaries), from 
the nlu/ data.

** simpleexpe.py is a simplified version of the training script (only using WordNet3.0 data),
you can change directly the hard-coded parameters and run the code in the WakaBST folder using
one of the two following commands: 

THEANO_FLAGS=floatX=float32,device=gpu python simpleexpe.py 
(for gpu use)
or
THEANO_FLAGS=floatX=float32,device=cpu python simpleexpe.py
(for cpu use)


** utils.py is a simple script to load a model and create ranking lists.

THEANO_FLAGS=floatX=float32,device=[cpu/gpu] python utils.py


** evaluation.py shows how to do the different evaluations procedure (mean rank, WSD, ...etc)

THEANO_FLAGS=floatX=float32,device=[cpu/gpu] python evaluation.py resultfolder idjob evalnumber

** expeWAKA.py (sorry for the headache...) is the training script over all the different training sets
using the jobman interface.

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Contact: myusername ..at.. iro.umontreal.ca