Implementation of basic linear algebra routines

Hello. While trying to invert a model via your framework I've faced an absence of inverse matrix computation support (torch.inverse). I've tried to implement it by myself (via looking your code and creating my own operator via numpy), but it fails right after custom conversion: "ValueError: Cannot add const = matrixinv(x=%test, name="x")" at matmul operation which involved inverted matrix.
Since there was another issue (with use of SVD) I think it would be great if raw torch and tensorflow routines would be added or a coincise method to register a custom op would be provided.

Start by reproducing the reported ValueError when a custom matrix-inverse operator reaches matmul. Review the requested torch.inverse and TensorFlow routine support alongside the proposed custom-op registration path, and define done as successful inverse-matrix conversion and validation in a matmul operation.

Written by the indexing model from the issue text.