How does data normalization work in keras during prediction?

Question

I see that the imageDataGenerator allows me to specify different styles of data normalization, e.g. featurewise_center, samplewise_center, etc.

I see from the exampl

Answer 1

I am using the datagen.fit function itself.

from keras.preprocessing.image import ImageDataGenerator

train_datagen = ImageDataGenerator(
    featurewise_center=True,
    featurewise_std_normalization=True)
train_datagen.fit(train_data)

test_datagen = ImageDataGenerator(  
    featurewise_center=True, 
    featurewise_std_normalization=True)
test_datagen.fit(train_data)

Ideally with this, test_datagen fitted on training dataset will learn the training datasets statistics. Then it will use these statistics to normalize testing data.