input: 
  def construct_MNIST_classifier_model() -> keras.Model:
      """Construct a neural network model in Python to classify the MNIST data set correctly.
      >>> model = construct_MNIST_classifier_model()
      >>> isinstance(model, keras.Model)
      True
      """
  
output:     model = keras.Sequential([
          keras.layers.InputLayer(input_shape=(28, 28)),
          keras.layers.Reshape((28, 28, 1)),
          keras.layers.Conv2D(32, (3, 3), activation='relu'),
          keras.layers.MaxPooling2D((2, 2)),
          keras.layers.Conv2D(64, (3, 3), activation='relu'),
          keras.layers.MaxPooling2D((2, 2)),
          keras.layers.Flatten(),
          keras.layers.Dense(128, activation='relu'),
          keras.layers.Dense(10, activation='softmax')
      ])
      return model