Visualizing a model's architecture

Due to their complexity, one of the most effective ways to debug a neural network is by visualizing its architecture. In this recipe, we'll learn about two different ways we can display a model's architecture:

• Using a text summary
• Using a visual diagram

Getting ready

We'll need both Pillow and pydot to generate a visual representation of a network's architecture. We can install both libraries using pip, as follows:

$> pip install Pillow pydot

How to do it…

Visualizing a model's architecture is pretty easy, as we'll learn in the following steps:

1. Import all the required libraries:

   from PIL import Image
   from tensorflow.keras import Model
   from tensorflow.keras.layers import BatchNormalization
   from tensorflow.keras.layers import Conv2D
   from tensorflow.keras.layers import Dense
   from tensorflow.keras.layers import Dropout
   from tensorflow.keras.layers import Flatten
   from tensorflow...