input: 
  from typing import List
  
  def distinguish_cats_and_dogs(model, dataset_path: str) -> None:
      """
      Train a machine learning model to distinguish between cats and dogs using a pre-defined neural network.
      
      >>> distinguish_cats_and_dogs(model, '/path/to/dataset')
      None
      """
      datagen = ImageDataGenerator(rescale = 1./255, shear_range = 0.2, zoom_range = 0.2, horizontal_flip = True)
      train_generator = datagen.flow_from_directory(directory = dataset_path, target_size = (64, 64), color_mode = 'rgb', class_mode = 'binary', batch_size = 32)
      model.fit_generator(generator = train_generator, steps_per_epoch = 800, epochs = 5, validation_data = test_generator, validation_steps = 200)
  
output:     test_datagen = ImageDataGenerator(rescale = 1./255)
      test_generator = test_datagen.flow_from_directory(directory = dataset_path, target_size = (64, 64), color_mode = 'rgb', class_mode = 'binary', batch_size = 32)