input: Write a python function to build a Convolutional Neural Network (CNN) model using TensorFlow and Keras.
  assert build_cnn_model().layers[0].__class__.__name__ == 'Conv2D'
  assert build_cnn_model().layers[1].__class__.__name__ == 'MaxPooling2D'
  assert build_cnn_model().layers[-1].units == 10
output: def build_cnn_model():
      from tensorflow.keras.models import Sequential
      from tensorflow.keras.layers import Conv2D, MaxPooling2D, Flatten, Dense
      
      model = Sequential()
      model.add(Conv2D(32, (3, 3), activation='relu', input_shape=(28, 28, 1)))
      model.add(MaxPooling2D((2, 2)))
      model.add(Flatten())
      model.add(Dense(128, activation='relu'))
      model.add(Dense(10, activation='softmax'))
      
      return model