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When input is fed into a neural network, the neural network essentially is doing a large number of matrix multiplications. If there are many many small non-zero weights, there are a lot of multiplications to do. If those weights are rounded down to zero, then obviously the multiplications don't need to happen so compute time is saved. Another benefit is that ...


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