Deep Learning LSTM sequenceInputLayer - Data normalization on Test Data?

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Hi all,
when using the sequenceInputLayer option "Normalization", "zscore" (for example) will the same normalization be applied on the Testing Data when using the classify or predict function? My understanding is that i always have to use the same normalization on the Test Data as i used on the Training Data. Or am i missing something?

Accepted Answer

Raunak Gupta
Raunak Gupta on 16 Aug 2020
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.

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