input: def create_mnist_classifier():
      """Construct a neural network model in Python to classify the MNIST data set correctly.
      >>> create_mnist_classifier()
      <keras.engine.functional.Functional object at 0x...>
      """
      import keras
  
      # Input layer
      input_layer = keras.layers.Input(shape=(784,))
  
      # Hidden layer
      hidden_layer = keras.layers.Dense(128, 
                                        activation='relu')(input_layer)
  
      # Output layer
      output_layer = keras.layers.Dense(10, 
                                        activation='softmax')(hidden_layer)
  
      # Model
      model = keras.Model(inputs=input_layer, outputs=output_layer)
  
      # Compile model
      model.compile(optimizer='adam', 
                    loss='sparse_categorical_crossentropy',
                    metrics=['accuracy'])
      
      return model
output:     return model