Metadata-Version: 2.1
Name: museflow
Version: 1.0.0
Summary: Music sequence learning toolkit
Home-page: https://github.com/cifkao/museflow
Author: Ondřej Cífka
Author-email: ondra@cifka.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: BSD License
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Utilities
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: cached-property
Requires-Dist: coloredlogs
Requires-Dist: confugue
Requires-Dist: lmdb
Requires-Dist: numpy
Requires-Dist: pretty-midi
Requires-Dist: pyyaml
Requires-Dist: note-seq
Provides-Extra: gpu
Requires-Dist: tensorflow-gpu (<2.0) ; extra == 'gpu'
Provides-Extra: nogpu
Requires-Dist: tensorflow (<2.0) ; extra == 'nogpu'

# museflow
museflow is an experimental music sequence learning toolkit, built on top of TensorFlow.

The most important modules are:
- `museflow.components` – building blocks for TensorFlow models (e.g. RNN decoder)
- `museflow.encodings` – classes defining ways to encode music for use with the models
- `museflow.trainer` – a basic implementation of model loading, saving and training
- `museflow.models` – implementations of basic models (accessible via the `museflow model` command)
- `museflow.scripts` – pre- and post-processing scripts (accessible via the `museflow script` command)

To install, run:
```sh
pip install 'museflow[gpu]'
```
To install without GPU support:
```sh
pip install 'museflow[nogpu]'
```

## License
This software is distributed under the [BSD 3-Clause License](https://github.com/cifkao/museflow/blob/master/LICENSE).

Copyright 2019 Ondřej Cífka of Télécom Paris, Institut Polytechnique de Paris.  
All rights reserved.


