fancy-cnn

Convolutional Neural Networks for multi-sentence sentiment analysis (Stanford CS224N)

##General Considerations First off, this class of sequential convolutional networks is quite GEMM intensive, and really isn't suited to a CPU. You also really should use CuDNN when training.

Bleeding edge installations of Theano and Keras are required.

For reference:

• On a 2.6 GHz Intel Core i7, one epoch of IMDB training takes ~3.5 days
• On a GRID K520 without CuDNN, one epoch of IMDB training takes ~1 hour
• On a GRID K520 with CuDNN, one epoch of IMDB training takes ~30 minutes
• On a GTX Titan X with CuDNN, one epoch of IMDB training takes ~11 minutes

If you want to use CuDNN, you really should also

[dnn]
conv.algo_fwd = time_on_shape_change
conv.algo_bwd = time_on_shape_change

to your .theanorc.

IMDB Dataset

Run python prepare-imdb.py to prepare your data! Look at this to see how to train the IMDB model.

Yelp Humor Dataset

Run python prepare-yelp.py to prepare your data! Look at this to see how to train a model on Yelp.