I implemented Restructuring Vector Quantization with the Rotation Trick by fifty et al.and built a PyPI library for the ICLR 2025 Rotation Trick.The Rotation Trick replaces the Straight-Through Estimator (STE) with a geometric rotation of the gradient. It preserves angular information between the encoder output and codebook vector, leading to higher codebook utilization.I have also benchmarked it on audio. Documented everything from paper to mathematics behind in \docs in github-repoThe implementation uses matrix-free Householder reflection (O(d) memory). PyPI: pip install vqrotate Benchmark: https://github.com/develepo/vqrotate-benchmarkI also explored an adaptive scaling extension. It achieved lower MSE but introduced assignment instability, an interesting trade-off that I would love to hear thoughts on.Would love any feedback, especially on Residual VQ extensions.