Hi Barry,
The normalization is applied on every batch of the data that passes through any particular data input layer whether being sequenceInputLayer or imageInputLayer. So, when the training or testing happens it calls a forward function which invokes the batch normalization for that input layer with option like “zscore”, “zerocenter” etc.
No need to worry about saving any parameter about normalization because it varies from batch to batch but be sure that normalization applies to both training and testing data while passing it through the Network.
