We updated TanSacNet Project for developing tangent space adaptive control networks.
- New PyTorch Implementation: Introduced a PyTorch-based 2-D LSUN framework, including batch processing in
orthonormalTransform.py
and a low-dimensional approximation sample. Optimized gradient computation and sequential matrix processing to improve efficiency in PyTorch and CUDA environments. - Enhanced MATLAB Support: Improved data type and device management to ensure stability and performance in MATLAB workflows.
- Code Refactoring and Stability: Streamlined code structure for maintainability and resolved initialization and CPU processing issues across both frameworks.
This pre-release highlights the new PyTorch implementation, along with key updates to MATLAB support and overall code stability.
Paper Published in IAPSIPA Transactions on Signal and Information Processing