The original polyphonic music data can be downloaded from http://www-etud.iro.umontreal.ca/~boulanni/icml2012, we process the cPickle file into .mat format.

This code is written in python. To use it you will need:

• Python 2.7
• Theano 0.7
• A recent version of NumPy and SciPy

This code can be run in CPU/GPU devices directly.

Example commands:

Running any optimization algorithm (i.e. SGD, SGD-M, RMSprop & Adam):

python eval_music.py sys.argv[1] sys.argv[2]

Two examples:

python eval_music.py Piano SGD

python eval_music.py JSB Adam

sys.argv[1] indicates which dataset to use, sys.argv[2] indicates which algorithm to use.

In order to monitor the training process, all the output information will be printed out in the .log file. The final parameters we learned will be stored in a .npz file.