This repository contains a Pytorch implementation of the paper "The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks" by Jonathan Frankle and Michael Carbin that can be easily adapted to any model/dataset.
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Does it give inference speed/memory usage improvement? #23
If this is used for Lottery Ticket Hypothesis experiments on a model, will it result in improvement in terms of inference speed/memory usage of the models?
As far as I know, even if the models are pruned, they would use the same memory as earlier and hence would take the time and memory as before.
If this is used for Lottery Ticket Hypothesis experiments on a model, will it result in improvement in terms of inference speed/memory usage of the models?
As far as I know, even if the models are pruned, they would use the same memory as earlier and hence would take the time and memory as before.