This paper introduces torchsom, an open-source Python library that provides a reference implementation of the Self-Organizing Map (SOM) in PyTorch. This package offers three main features: (i) dimensionality reduction, (ii) clustering, and (iii) friendly data visualization. It relies on a PyTorch backend, enabling (i) fast and efficient training of SOMs through GPU acceleration, and (ii) easy and scalable integrations with PyTorch ecosystem. Moreover, torchsom follows the scikit-learn API for ease of use and extensibility. The library is released under the Apache 2.0 license with 90% test coverage, and its source code and documentation are available at https://github.com/michelin/TorchSOM.
翻译:本文介绍了torchsom,一个开源的Python库,提供了自组织映射(SOM)在PyTorch中的参考实现。该软件包提供三个主要功能:(i)降维,(ii)聚类,以及(iii)友好的数据可视化。它基于PyTorch后端,支持(i)通过GPU加速实现SOM的快速高效训练,以及(ii)与PyTorch生态系统轻松、可扩展地集成。此外,torchsom遵循scikit-learn API,便于使用和扩展。该库在Apache 2.0许可证下发布,测试覆盖率达90%,其源代码和文档可在https://github.com/michelin/TorchSOM获取。