code: def main():
      np.random.seed(123)
      inputs = np.random.uniform(size=(8, 32, 32, 1))
  
      # Just for visual purposes.
      np.set_printoptions(precision=2)
  
      print("NESTED MODELS")
      nested_model = create_network_with_one_subnet()
  
      # will get the activations of every layer, EXCLUDING subnet layers.
      utils.print_names_and_values(
          keract.get_activations(nested_model, inputs)
      )
  
      # will get the activations of every layer, including subnet.
      utils.print_names_and_values(
          keract.get_activations(nested_model, inputs, nested=True)
      )
  
file_path: keract/examples/model_in_model.py
imports: import numpy
  import tensorflow
  from tensorflow import keras
  from tensorflow.keras.utils import plot_model
  import keract
  import utils
label_desc: Use image node_id 2 for calling a global function with example usage: main() without return types