input: Write a function to create and compile a TensorFlow model with a specific architecture.
  assert isinstance(create_and_compile_model(), tf.keras.Sequential)
  assert len(create_and_compile_model().layers) == 3
output: import tensorflow as tf
  
  def create_and_compile_model():
      model = tf.keras.Sequential([
          tf.keras.layers.Dense(128, activation='relu', input_shape=(784,)),
          tf.keras.layers.Dense(64, activation='relu'),
          tf.keras.layers.Dense(10, activation='softmax')
      ])
      model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])
      return model