Pre-trained  VGG16 architecture does not contain a dropout layer except in the last classifier layer. How can I add dropout layer after every convolution layer in VGG 16 if I want to keep the value of VGG16 parameters (weights/Biases)? (FYI, I wanted to add dropout layer between the convolutional layers in order to quantify MC-Dropout uncertainty during prediction).