Support for random walk kernel

[JuliusSchwartz]

Converting the work done in https://github.com/leojklarner/GProTorch/blob/kernels/gprotorch/kernels/graph_kernels/random_walk.py from pytorch to tensorflow and using https://www.jmlr.org/papers/volume11/vishwanathan10a/vishwanathan10a.pdf as a reference.

Have only implented eigendecomposition approach so far (meaning that one test for which GraKel uses Conjugate Gradient Descent only passes if method_type="baseline" is specified as an argument to the constructor of GraKel's random walk kernel)

Tests with non-null values of p don't pass although I suspect this might be due to a bug in GraKel (see https://github.com/ysig/GraKeL/issues/71)

[Ryan-Rhys]

I'll just add Leo to the review since he coded up the random walk kernel in GProTorch.

[JuliusSchwartz]

I'll just add Leo to the review since he coded up the random walk kernel in GProTorch.

Good idea (I don't seem to be able to add people myself)