LibMTL: A Python Library for Multi-Task Learning

• URL: http://arxiv.org/abs/2203.14338v1
• Date: Sun, 27 Mar 2022 16:00:48 GMT
• Title: LibMTL: A Python Library for Multi-Task Learning
• Authors: Baijiong Lin and Yu Zhang
• Abstract summary: LibMTL is an open-source Python library built on PyTorch that provides a unified, comprehensive, reproducible, and implementation framework for Multi-Task Learning (MTL) LibMTL considers different settings and approaches in MTL, and it supports a large number of state-of-the-art MTL methods.
• Score: 4.531240717484252
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper presents LibMTL, an open-source Python library built on PyTorch, which provides a unified, comprehensive, reproducible, and extensible implementation framework for Multi-Task Learning (MTL). LibMTL considers different settings and approaches in MTL, and it supports a large number of state-of-the-art MTL methods, including 12 loss weighting strategies, 7 architectures, and 84 combinations of different architectures and loss weighting methods. Moreover, the modular design in LibMTL makes it easy-to-use and well extensible, thus users can easily and fast develop new MTL methods, compare with existing MTL methods fairly, or apply MTL algorithms to real-world applications with the support of LibMTL. The source code and detailed documentations of LibMTL are available at https://github.com/median-research-group/LibMTL and https://libmtl.readthedocs.io, respectively.

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