input: 
  def create_cnn_model():
      """ Create a Convolutional Neural Network (CNN) model using Keras to classify images of cats and dogs.
      The model should be able to distinguish between cats and dogs based on the given dataset of images.
      >>> create_cnn_model()
      <keras.engine.sequential.Sequential object at 0x7f8b1c0f1a90>
      """
  
output:     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=(64, 64, 3)))
      model.add(MaxPooling2D(pool_size=(2, 2)))
      model.add(Conv2D(64, (3, 3), activation='relu'))
      model.add(MaxPooling2D(pool_size=(2, 2)))
      model.add(Flatten())
      model.add(Dense(128, activation='relu'))
      model.add(Dense(1, activation='sigmoid'))
  
      return model