Code to accompany Efficient training of energy-based models via spin-glass control
Alejandro Pozas-Kerstjens, Gorka Muñoz-Gil, Miguel Angel García-March, Antonio Acín, Maciej Lewenstein, and Przemyslaw R. Grzybowski
This is a repository containing the code for models with Restricted Axons and training via Pattern-InDuced correlations (RAPID), developed in the article "Efficient training of energy-based models via spin-glass control. Alejandro Pozas-Kerstjens, Gorka Muñoz-Gil, Miguel Angel García-March, Antonio Acín, Maciej Lewenstein, and Przemyslaw R. Grzybowski. arXiv:1910.01592."
All code is written in Python.
Libraries required:
- ebm-torch for energy-based models
- gc for garbage collection
- itertools for combinatorial operations
- math and numpy for math operations
- matplotlib for plot generation
- pytorch >= 0.4.0 as ML framework
- tqdm for custom progress bar
Files:
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comparison: example of use. Trains restricted Boltzmann machines using commonplace samplers and via RAPID, and computes various indicators of quality of training.
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rapid: contains the relevant classes.
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utils: additional functions relevant for the example.