Metadata-Version: 2.1
Name: enniolearning
Version: 0.2.0
Summary: A Machine Learning engine for MID music files, based on PyTorch framework.
Home-page: https://github.com/Mara-tech/Ennio-Learning
Author: Pierrick Baudet
Author-email: pbaudet.enseirb@gmail.com
License: see LICENSE.txt
Description: # Ennio-Learning
        Ennio is a machine learning program.
        It takes musics in MID format to learn a theme.
        Themes are collections of datasets (collection of MID files) having common features, for example :
        - Heroic fantasy
        - Thriller
        - Horror
        - Suspense
        - Classic
        - Manga
        - etc.
        
        Once learning (training) for one theme is done, the model (network weights) is serialized and can be reused for later music generation.
        Such models are used for instance in [Ennio app project](https://github.com/Mara-tech/Ennio).
        
        ### Training features
        Ennio Learning handles [Jordan](https://github.com/Mara-tech/jordan) features during training and model evaluation. As these are long processes, Jordan app gives remote access to logs (and ETA), and some control over loops. For example, one may skip a training task if it is not going to be efficient (loss is not decreasing).
        
        ### Logging
        A default logger exists, at level `logging.INFO`. You may adjust this level by calling
        
            import logging
            from enniolearning.utils import set_default_logger_level
            
            set_default_logger_level(logging.DEBUG)
                
        You can also provide your own logger (defined from [logging library](https://docs.python.org/3/howto/logging.html))
        by passing `logger` argument. For example :
        
            import logging, logging.config
            logging.config.fileConfig('logging.yml')
            logger_from_config = logging.getLogger('simpleExample')
            
            from ennio_training import train
            train(logger=logger_from_config)
Platform: UNKNOWN
Description-Content-Type: text/markdown
