How to use pre-trained features from VGG-16 as input to GlobalAveragePooling2D() layer in Keras

Is it possible to use pre-trained model features from VGG-16 and pass to GlobalAveragePooling2D() layer of other model in Keras?

Sample code for storing offline features of VGG-16 network:

model = applications.VGG16(include_top=False, weights='imagenet')

bottleneck_features_train = model.predict(input)

Sample code for top model:

model = Sequential()
model.add(GlobalAveragePooling2D()) # Here I want to use pre-trained feature from VGG-16 net as input.

I can not use Flatten() layer as I want to predict multi-labels with multi-classes.

Yes, check out the Lesson 7 notebook for an example of that.

Thanks for the reply. I will check it