I trained a model in keras and I'm thinking of pruning my fully connected network. I'm little bit lost on how to prune the layers.
Author of 'Learning both Weights and Connections for Efficient Neural Networks', say that they add a mask to threshold weights of a layer. I can try to do the same and fine tune the trained model. But, how does it reduce model size and # of computations?
from How to implement neural network pruning?
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