Random Search for Hyper Parameters

I want to tune my neural network and find the some good lambda and eta values. I can do exhaustive grid search to find the best combo. However Bergstra in this http://www.jmlr.org/papers/volume13/bergstra12a/bergstra12a.pdf proposes random search.

How am I supposed to do this?

Heres is how i think of it:

generate 100 random etas

eta=rand(1-100)


do the same for lambdas

lambdas=rand(1-100)


and then I have to sample random pairs i think. But how many samples should I take from the this pool of 100 elements per hyperparameter?