Query regarding inference of trained model and use of mutilated graphs

[kieron15]

Hi
I found the paper very interesting but have some doubts regarding the model and explanation to following points will greatly help in increasing my understanding of the model.

I see that you are training two models, Response prediction model and Perturbagen discovery model.
In some calls to model, mutilate_mutations input argument is used. (e.g. lines a, b)

As per my observation, this input is only used when initial state is 'diseased'. Are you using the mutilate_mutations argument to modify the links in base PPI network to mimic PPIs in disease state?
How do you get this data.mutations for any input sample for the model?

I am also clueless about how one can use the trained model for inference. I guess one needs to run only the trained Perturbagen discovery model during inference. Is this right?
During inference if you have a query vector of disease state and a vector of target/healthy state, what other inputs are needed. How does one get data.mutations during inference?

Can you please clarify how did you run inference for results presented in the paper? It will be very helpful if you can share the inference script, model checkpoints and the sample inputs.