PyTorch Adapt
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PyTorch Adapt. / Musgrave, Kevin; Belongie, Serge; Lim, Ser-Nam.
arXiv.org, 2022.Research output: Working paper › Preprint › Research
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TY - UNPB
T1 - PyTorch Adapt
AU - Musgrave, Kevin
AU - Belongie, Serge
AU - Lim, Ser-Nam
PY - 2022
Y1 - 2022
N2 - 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 this https URL
AB - 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 this https URL
M3 - Preprint
BT - PyTorch Adapt
PB - arXiv.org
ER -
ID: 384619158