autrainer: A Modular and Extensible Deep Learning Toolkit for Computer Audition Tasks

TL;DR

autrainer is a flexible, low-code deep learning toolkit built on PyTorch, designed to facilitate rapid, reproducible, and extensible training across diverse computer audition tasks.

Contribution

It introduces a modular, extensible framework that simplifies training workflows for computer audition, supporting various neural networks and preprocessing routines.

Findings

Supports a wide range of neural network architectures

Enables rapid and reproducible training workflows

Offers low-code interface for ease of use

Abstract

This work introduces the key operating principles for autrainer, our new deep learning training framework for computer audition tasks. autrainer is a PyTorch-based toolkit that allows for rapid, reproducible, and easily extensible training on a variety of different computer audition tasks. Concretely, autrainer offers low-code training and supports a wide range of neural networks as well as preprocessing routines. In this work, we present an overview of its inner workings and key capabilities.