input: Write a function to construct a neural network model using Keras in Python to classify the MNIST data set correctly. The function should return the compiled model.
  
  assert construct_mnist_classifier().__class__.__name__ == 'Model'
  assert construct_mnist_classifier().optimizer.__class__.__name__ == 'Adam'
  assert construct_mnist_classifier().loss == 'sparse_categorical_crossentropy'
output: def construct_mnist_classifier():
      from tensorflow.keras.models import Sequential
      from tensorflow.keras.layers import Dense, Flatten
      model = Sequential([
          Flatten(input_shape=(28, 28)),
          Dense(128, activation='relu'),
          Dense(10, activation='softmax')
      ])
      model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])
      return model