Overview of NNI Model Pruning

Pruning is a common technique to compress neural network models. The pruning methods explore the redundancy in the model weights(parameters) and try to remove/prune the redundant and uncritical weights. The redundant elements are pruned from the model, their values are zeroed and we make sure they don’t take part in the back-propagation process.

The following concepts can help you understand pruning in NNI.