autrainer 0.10.0

A Modular and Extensible Deep Learning Toolkit for Computer Audition Tasks.

autrainer

A Modular and Extensible Deep Learning Toolkit for Computer Audition Tasks.

autrainer is built on top of PyTorch and Hydra, offering a modular and extensible way to perform reproducible deep learning experiments for computer audition tasks using YAML configuration files and the command line.

Installation

It is recommended to install autrainer within a virtual environment. To create a new virtual environment, refer to the Python venv documentation.

Next, install autrainer using pip.

pip install autrainer

Note

If you are using Windows, make sure that PyTorch (along with torchvision and torchaudio) version 2.0 or higher is installed beforehand. For installation instructions, refer to the PyTorch documentation.

The following optional dependencies can be installed to enable additional features:

• latex for LaTeX plotting (requires a LaTeX installation).

• mlflow for MLflow logging.

• tensorboard for TensorBoard logging.

• opensmile for audio feature extraction with openSMILE.

• albumentations for image augmentations with Albumentations.

• audiomentations for audio augmentations with audiomentations.

• torch-audiomentations for audio augmentations with torch-audiomentations.

pip install autrainer[latex]
pip install autrainer[mlflow]
pip install autrainer[tensorboard]
pip install autrainer[opensmile]
pip install autrainer[albumentations]
pip install autrainer[audiomentations]
pip install autrainer[torch-audiomentations]

To install autrainer with all optional dependencies, use the following command:

pip install autrainer[all]

To install autrainer from source, refer to the contribution guide.

Next Steps

To get started using autrainer, the quickstart guide outlines the creation of a simple training configuration and tutorials provide examples for implementing custom modules including their configurations.

For a complete list of available CLI commands, refer to the CLI reference or the CLI wrapper.