Signatory is a library for calculating and performing functionality related
to the signature and logsignature transforms. The focus is on machine learning,
and as such includes features such as CPU parallelism, GPU support, and
backpropagation. To our knowledge it is the first GPU-capable library for these
operations. Signatory implements new features not available in previous
libraries, such as efficient precomputation strategies. Furthermore, several
novel algorithmic improvements are introduced, producing substantial real-world
speedups even on the CPU without parallelism. The library operates as a Python
wrapper around C++, and is compatible with the PyTorch ecosystem. It may be
installed directly via \texttt{pip}. Source code, documentation, examples,
benchmarks and tests may be found at
\texttt{\url{https://github.com/patrick-kidger/signatory}}. The license is
Apache-2.0.Comment: Published at ICLR 202
