Metadata-Version: 2.3
Name: autrainer
Version: 0.7.0
Summary: A Modular and Extensible Deep Learning Toolkit for Computer Audition Tasks.
License: MIT
Keywords: computer audition,deep learning,artificial intelligence,pytorch,hydra-core,command-line,yaml
Author: Simon Rampp
Author-email: simon.rampp@tum.de
Requires-Python: >=3.9,<4.0
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Provides-Extra: albumentations
Provides-Extra: all
Provides-Extra: audiomentations
Provides-Extra: latex
Provides-Extra: mlflow
Provides-Extra: opensmile
Provides-Extra: tensorboard
Provides-Extra: torch-audiomentations
Requires-Dist: Pillow (>=9.3.0,<10.0.0)
Requires-Dist: PyYAML (>=6.0.1,<7.0.0)
Requires-Dist: Requests (>=2.31.0,<3.0.0)
Requires-Dist: albumentations (>=1.4.10,<2.0.0) ; extra == "albumentations" or extra == "all"
Requires-Dist: audeer (>=2.2.1,<3.0.0)
Requires-Dist: audiofile (>=1.3.0,<2.0.0)
Requires-Dist: audiomentations (>=0.37.0,<0.38.0) ; (python_version >= "3.9" and python_full_version <= "3.12.0") and (extra == "audiomentations" or extra == "all")
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Requires-Dist: hydra-core (>=1.3.2,<2.0.0)
Requires-Dist: hydra-filter-sweeper (>=1.1.0,<2.0.0)
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Requires-Dist: opensmile (>=2.5.0,<3.0.0) ; extra == "opensmile" or extra == "all"
Requires-Dist: pandas (>=2.1.1,<3.0.0)
Requires-Dist: psutil (>=5.0.0,<6.0.0)
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Requires-Dist: seaborn (>=0.13.0,<0.14.0)
Requires-Dist: speechbrain (>=1.0.0,<2.0.0)
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Requires-Dist: timm (>=1.0.3,<2.0.0)
Requires-Dist: torch
Requires-Dist: torch-audiomentations (>=0.11.1,<0.12.0) ; extra == "torch-audiomentations" or extra == "all"
Requires-Dist: torchaudio
Requires-Dist: torchinfo (>=1.8.0,<2.0.0)
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Requires-Dist: torchvision
Requires-Dist: tqdm (>=4.66.1,<5.0.0)
Requires-Dist: transformers (>=4.34.0,<5.0.0)
Project-URL: Documentation, https://autrainer.github.io/autrainer/
Project-URL: Repository, https://github.com/autrainer/autrainer
Description-Content-Type: text/markdown

<div align="center">
  <img src="https://autrainer.github.io/autrainer/_images/logo_banner.png" alt="autrainer — A Modular and Extensible Deep Learning Toolkit for Computer Audition Tasks">
</div>

# autrainer

[![autrainer PyPI Version](https://img.shields.io/pypi/v/autrainer?logo=pypi&logoColor=b4befe&color=b4befe)](https://pypi.org/project/autrainer/)
[![autrainer Python Versions](https://img.shields.io/pypi/pyversions/autrainer?logo=python&logoColor=b4befe&color=b4befe)](https://pypi.org/project/autrainer/)
[![autrainer Hugging Face](https://img.shields.io/badge/Hugging_Face-autrainer-b4befe?logo=huggingface&logoColor=b4befe)](https://huggingface.co/autrainer)
[![autrainer GitHub License](https://img.shields.io/badge/license-MIT-b4befe?logo=c)](https://github.com/autrainer/autrainer/blob/main/LICENSE)

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

_autrainer_ is built on top of [PyTorch](https://pytorch.org/) and [Hydra](https://hydra.cc/),
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

To install _autrainer_, first ensure that PyTorch (along with torchvision and torchaudio) version 2.0 or higher is installed.
For installation instructions, refer to the [PyTorch website](https://pytorch.org/get-started/locally/).

It is recommended to install _autrainer_ within a virtual environment.
To create a new virtual environment, refer to the [Python venv documentation](https://docs.python.org/3/library/venv.html).

Next, install _autrainer_ using _pip_.

```bash
pip install autrainer
```

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

- `latex` for LaTeX plotting (requires a LaTeX installation).
- `mlflow` for [MLflow](https://mlflow.org/) logging.
- `tensorboard` for [TensorBoard](https://www.tensorflow.org/tensorboard) logging.
- `opensmile` for audio feature extraction with [openSMILE](https://audeering.com/opensmile/).
- `albumentations` for image augmentations with [Albumentations](https://albumentations.ai/).
- `audiomentations` for audio augmentations with [audiomentations](https://github.com/iver56/audiomentations).
- `torch-audiomentations` for audio augmentations with [torch-audiomentations](https://github.com/asteroid-team/torch-audiomentations).

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

```bash
pip install autrainer[all]
```

To install _autrainer_ from source, refer to the [contribution guide](https://autrainer.github.io/autrainer/development/contributing.html).

## Next Steps

To get started using _autrainer_, the [quickstart guide](https://autrainer.github.io/autrainer/usage/quickstart.html) outlines the creation of a simple training configuration
and [tutorials](https://autrainer.github.io/autrainer/usage/tutorials.html) provide examples for implementing custom modules including their configurations.

For a complete list of available CLI commands, refer to the [CLI reference](https://autrainer.github.io/autrainer/usage/cli_reference.html) or the [CLI wrapper](https://autrainer.github.io/autrainer/usage/cli_wrapper.html).

