I am new to graph deep learning and I am trying to generate a graph from a matrix of node features by computing graph edges for all nodes within a given distance. I have found a concise way to do this with torch_geometric.nn.radius_graph() but I would like a similarly concise method of accomplishing the same task with tensorflow tensors.
My code is kind of a mess right now and I would like to change it significantly based on whatever method that is convenient for processing a graph dataset in this form. I am aware that I can write a class of connectivity utility functions but I don't think that is ideal.