We present tntorch, a tensor learning framework that supports multiple decompositions (including Candecomp/Parafac, Tucker, and Tensor Train) under a unified interface. With our library, the user can learn and handle low-rank tensors with automatic differentiation, seamless GPU support, and the convenience of PyTorch's API. Besides decomposition algorithms, tntorch implements differentiable tensor algebra, rank truncation, cross-approximation, batch processing, comprehensive tensor arithmetics, and more.
翻译:我们在一个统一的界面下推出一个支持多重分解(包括Candecomp/Parafac、Tucker和Tensor train)的“Tentor”学习框架,即“tnorch ” 。 用我们的图书馆,用户可以自动区分、无缝 GPU 支持和方便PyTorch API 。 除了分解算法之外, Tentrch 安装了不同的高温代数、 排解、 交叉比对齐、 批量处理、 综合的“ 数十” 算术等等。