A simple module for Torch7 and the nn package.
luarocks install --server=https://raw.github.com/Atcold/net-toolkit/master net-toolkitThis package allows to save and retrive to/from disk a lighter version of the network that is being training.
saveNet() saves a lighter version of your current network, removing all unnecessary data from it (such as gradients, activation units' state and etc...) and returns a new couple of flattened weight and gradients. Usage:
w, dw = saveNet(model, fileName)saveNetFields() saves your current network, removing all Tensor data you don't want to save and returns a new couple of flattened weight and gradients. Usage:
w, dw = saveNetFields(model, fileName, {'weight', 'bias'})Only weight and bias Tensors will be saved and the rest will be discarded.
Let's say we would like to load a network we have previously saved with saveNet() for continuing a training session on it. Some inner parameters (something about gradients) have to be restored, since saveNet() did a pruning operation on the network in order to save space. Here is how we can handle this case:
model, w, dw = loadNet(fileName)Now we can keep training, perhaps without forgetting to (re-)define a criterion loss (the criterion is not saved with the network, so we have to re-define it, if we don't already do it somewhere else in the code).