This latest release brings several improvements, new features, and update our Python support to 3.9 to 3.13.
New Paddle backend
PaddlePaddle is a deep learning framework similar to PyTorch (both in terms of functionality and API design). Users can leverage dynamic graph mode for algorithm development, and then utilize Paddle's provided tools for model exporting, model compression, and inference libraries. Paddle deeply integrates with inference libraries like ONNX and TensorRT. Thanks to @HydrogenSulfate , #565
Package reorganization
We now have a solvers submodule that contains all our optimization-related code, thanks to @cohenjer, #550.
Algorithmic improvements
The CP regression now supports multi-dimensional output thanks to @merajhashemi in #252.
Quality of life improvements and other changes
Documentation improvements, unit-tests have been improved and made more reliable, and small improvements have been made to several of our algorithms.
- Add checks for data structure and rank feasibility by @aarmey in #566
- Fix the documentation and remove last reference to mxnet by @aarmey in #567
- Virtually all tests working across backends by @aarmey in #572
- Fix badge in documentation by @JeanKossaifi in edd74d1
- [Paddle] Update index.html and pyramid png by @HydrogenSulfate in #573
- Fix f-string In backend error message by @characat0 in #574
- Add dummy keyword arguments to Backend svd to throw a more informative error by @characat0 in #575
- Upgrade Python version by @aarmey in #576
- Cleanup PARAFAC2 tolerances by @aarmey in #564
Many thanks to the whole TensorLy team and all contributors @aarmey @cohenjer @yngvem @JeanKossaifi @merajhashemi, and our new contributors @HydrogenSulfate and @characat0.