Igraph and cugraph, and graph tool are far superior for a wide variety of reasons
- https://github.com/johnhany/awesome-list#graph lists a few Tensorflow and Pytorch + graphs applications
CuGraph docs > List of Supported and Planned Algorithms: https://docs.rapids.ai/api/cugraph/stable/graph_support/algo...
https://github.com/rapidsai/cugraph#news :
> NEW! nx-cugraph, a NetworkX backend that provides GPU acceleration to NetworkX with zero code change. :
pip install nx-cugraph-cu11 --extra-index-url https://pypi.nvidia.com
export NETWORKX_AUTOMATIC_BACKENDS=cugraph> pytype (Google) [1], PyAnnotate (Dropbox) [2], and MonkeyType (Instagram) [3] all do dynamic / runtime PEP-484 type annotation type inference [4] to generate type annotations.
Hypothesis generates tests from type annotations; and icontract and pycontracts do runtime type checking.