input: Write a python function to initialize and compile a Convolutional Neural Network (CNN) model using TensorFlow and Keras.
  assert isinstance(initialize_compile_CNN(), tf.keras.Model)
  assert initialize_compile_CNN().layers[0].__class__.__name__ == 'Conv2D'
  assert initialize_compile_CNN().layers[-1].units == 10
output: def initialize_compile_CNN():
      import tensorflow as tf
      from tensorflow.keras.models import Sequential
      from tensorflow.keras.layers import Conv2D, MaxPooling2D, Flatten, Dense
  
      model = Sequential([
          Conv2D(32, (3, 3), activation='relu', input_shape=(28, 28, 1)),
          MaxPooling2D((2, 2)),
          Flatten(),
          Dense(64, activation='relu'),
          Dense(10, activation='softmax')
      ])
  
      model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])
      
      return model