Evolution strategies in pytorch

I want to train a model using evolution strategies instead of backpropagation. I assume this would be done by doing something like differential evolution with the parameters of the model. I cannot find a lot of resources and implementations of that in pytorch. I would appreciate any directions of how to get this implemented.

Also, how reasonable is it to expect this to work on a RNN model (GRU)?