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How frequently to prune?: Body weight magnitude is commonly only a noisy proxy for excess weight relevance. Pruning only one time at the conclusion of education (
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On this check out, the point while in the loss landscape at which we start off optimizing — which is, just how we initialize the weights originally of training — is probably not where the principle action is.
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In the situation of convolutional neural networks, the subnetwork may vary determined by how you choose the pruning granularity. Inside the LTH, they implement an unstructured pruning, i.e. they replace personal weights from the convolution filters by a 0 value. But you could possibly visualize applying a structured pruning, replacing vectors, kernels as well as entire filters by zeroes.
The authors empirically observe that the pruning masks modify significantly in the course of the to start with epochs of training but seem to converge before long (see left Element of the figure below).