message: Add description and example to keras.callbacks.Callback.
  Add link to more comprehensive custom callback guide.
diff: @@ -611,6 +611,27 @@ class CallbackList(object):
  class Callback(object):
  """Abstract base class used to build new callbacks.
  + Callbacks can be passed to keras methods such as `fit`, `evaluate`, and
  + `predict` in order to hook into the various stages of the model training and
  + inference lifecycle.
  +
  + To create a custom callback, subclass `keras.callbacks.Callback` and override
  + the method associated with the stage of interest. See
  + https://www.tensorflow.org/guide/keras/custom_callback for more information.
  +
  + Example:
  +
  + >>> training_finished = False
  + >>> class MyCallback(tf.keras.callbacks.Callback):
  + ... def on_train_end(self, logs=None):
  + ... global training_finished
  + ... training_finished = True
  + >>> model = tf.keras.Sequential([tf.keras.layers.Dense(1, input_shape=(1,))])
  + >>> model.compile(loss='mean_squared_error')
  + >>> model.fit(tf.constant([[1.0]]), tf.constant([[1.0]]),
  + ... callbacks=[MyCallback()])
  + >>> assert training_finished == True
  +
  Attributes:
  params: Dict. Training parameters
  (eg. verbosity, batch size, number of epochs...).
  