wide_and_deep_subclassing.py

class WideAndDeepModel(keras.Model):
	def __init__(self, units=30, activation="relu", **kwargs):
    	super().__init__(**kwargs) # handles standard aruments ( name, etc.)
      self.hidden1 = keras.layers.Dense(units, activation=activation)
      self.hidden2 = keras.layers.Dense(units, activation=activation)
      self.main_output = keras.layers.Dense(1)
      self.aux_output = keras.layers.Dense(1)
       
    def call(self, inputs):
    	input_A, input_B = inputs
      hidden1 = self.hidden1(inputs_B)
      hidden2 = self.hidden2(hidden1)
      concat = keras.layers.Concatenate([input_A, hidden2])
      main_ouput = self.main_ouput(concat)
      aux_ouput = self.aux_ouput(hidden2)
      return main_ouput, aux_output
        
model = WideAndDeepModel()