The adoption of neural networks and deep learning in non-Euclidean domains has been hindered until recently by the lack of scalable and efficient learning frameworks. Existing toolboxes in this space were mainly motivated by research and education use cases, whereas practical aspects, such as deploying and maintaining machine learning models, were often overlooked. We attempt to bridge this gap by proposing TensorFlow ManOpt, a Python library for optimization on Riemannian manifolds in TensorFlow. The library is designed with the aim for a seamless integration with the TensorFlow ecosystem, targeting not only research, but also streamlining production machine learning pipelines.

中文翻译：

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TensorFlow ManOpt：黎曼流形优化库

直到最近，由于缺乏可扩展和高效的学习框架，神经网络和深度学习在非欧域中的采用一直受到阻碍。该领域现有的工具箱主要由研究和教育用例驱动，而实际方面，例如部署和维护机器学习模型，则经常被忽视。我们尝试通过提出 TensorFlow ManOpt 来弥合这一差距，TensorFlow ManOpt 是一个 Python 库，用于优化 TensorFlow 中的黎曼流形。该库旨在与 TensorFlow 生态系统无缝集成，不仅针对研究，还针对简化生产机器学习管道。