PyTorch Adapt

• URL: http://arxiv.org/abs/2211.15673v1
• Date: Mon, 28 Nov 2022 18:59:09 GMT
• Title: PyTorch Adapt
• Authors: Kevin Musgrave, Serge Belongie, Ser-Nam Lim
• Abstract summary: PyTorch Adapt is a library for domain adaptation. domain adaptation is a type of machine learning algorithm that re-purposes existing models to work in new domains. It is a fully-featured toolkit, allowing users to create a complete train/test pipeline in a few lines of code.
• Score: 37.03614011735927
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: PyTorch Adapt is a library for domain adaptation, a type of machine learning algorithm that re-purposes existing models to work in new domains. It is a fully-featured toolkit, allowing users to create a complete train/test pipeline in a few lines of code. It is also modular, so users can import just the parts they need, and not worry about being locked into a framework. One defining feature of this library is its customizability. In particular, complex training algorithms can be easily modified and combined, thanks to a system of composable, lazily-evaluated hooks. In this technical report, we explain in detail these features and the overall design of the library. Code is available at https://www.github.com/KevinMusgrave/pytorch-adapt

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