input: 
  def construct_mnist_model() -> keras.Model:
      """ Construct a neural network model using Keras to classify the MNIST data set.
      >>> model = construct_mnist_model()
      >>> model.summary()
      """
      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