input: Write a function to construct a neural network model in Python using Keras to classify the MNIST data set correctly. The function should return the compiled Keras model.
  
  assert construct_mnist_model().input_shape==[(None, 784)]
  assert construct_mnist_model().output_shape==(None, 10)
  assert type(construct_mnist_model())==keras.engine.functional.Functional
output: def construct_mnist_model():
      from tensorflow.keras.models import Sequential
      from tensorflow.keras.layers import Dense, Flatten
      model = Sequential()
      model.add(Flatten(input_shape=(28, 28)))
      model.add(Dense(128, activation='relu'))
      model.add(Dense(10, activation='softmax'))
      model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])
      return model