Activate dropout in a pre-trained VGG16 model

Question

I'm using Tensorflow 2.0 and a pre-trained VGG16 model and want to activate dropout during prediction. So far I tried the following without success:

model = tf.keras.applications.VGG16(input_shape=(224, 224, 3), weights='imagenet', is_training=True)

model = tf.keras.applications.VGG16(input_shape=(224, 224, 3), weights='imagenet', dropout_rate=0.5)

However, none of these approaches worked. How can I enable dropout during the prediction phase?

Answer 1

The VGG16 architecture does not contain a dropout layer by default. You would need to insert a dropout layer in the model.

Here is a post I found useful to solve this: Add dropout layers between pretrained dense layers in keras