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Implementation of C-RNN-GAN.
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Implementation of C-RNN-GAN.

Publication: Title: C-RNN-GAN: Continuous recurrent neural networks with adversarial training Information: http://mogren.one/publications/2016/c-rnn-gan/

Bibtex:

@inproceedings{mogren2016crnngan, title={C-RNN-GAN: A continuous recurrent neural network with adversarial training}, author={Olof Mogren}, booktitle={Constructive Machine Learning Workshop (CML) at NIPS 2016}, pages={1}, year={2016} }

A generative adversarial model that works on continuous sequential data. Implementation uses Python and Tensorflow, and depends on https://github.com/vishnubob/python-midi for MIDI file IO.

Requirements

tensorflow, python-midi (or python3-midi)

How to run?

python rnn_gan.py --datadir "relative-path-to-data" --traindir "path-to-generated-output" --feed_previous --feature_matching --bidirectional_d --learning_rate 0.1 --pretraining_epochs 6

Author: Olof Mogren (olofmogren) Contributors: Dhruv Sharma (dhruvsharma1992)

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