Dependencies:

• Python ofc
• pipenv
• TinySol dataset

To install, navigate to the package directory:

$ pipenv install

Pytorch is installed automatically, and will work fine for all CPU based usages. However, to configure this package for GPU usage, you must install your required pytorch version via:

$ pipenv run pip install torch==1.8.1+cu102 ...

Generally, to train this model you will run:

$ pipenv run train

This first generates a dataset of targets from the samples contained in the TinySOL dataset. This will happen automatically when:

• src/settings.py does match the settings used to generate the target dataset.
• a dataset has not already been generated.

In the event that you wish to manually generate a dataset before training, run:

$ pipenv run retrain

All of the model hyperparameters can be configured in src/settings.py. When training is complete, the trained model is automatically saved in the /models directory.

To test the model, run:

$ pipenv run orchestrate

This will prompt the user for a filepath to a target sound, and generate an orchestration using a pretrained model defined in src/settings.py. Generated samples are output to /out.

If you wish to run the entire process, including generating the dataset (when necessary), training and evaluating, use:

$ pipenv run pipeline

Alternatively, use $ pipenv run python index.py --help for more details on using optional arguments.