message: Fixing updated LearningRateScheduler comment to include example with schedule using epoch and lr.
diff: @@ -1608,19 +1608,20 @@ class RemoteMonitor(Callback):
  class LearningRateScheduler(Callback):
  """Learning rate scheduler.
  - At the beginning of every epoch, this callback gets the learning rate
  - value from `schedule` function provided at `__init__`, with the current epoch,
  - and applies that learning rate on the optimizer.
  + At the beginning of every epoch, this callback gets the updated learning rate
  + value from `schedule` function provided at `__init__`, with the current epoch
  + and current learning rate, and applies the updated learning rate
  + on the optimizer.
  Example:
  - >>> # This function keeps the learning rate at 0.001 for the first ten epochs
  + >>> # This function keeps the initial learning rate for the first ten epochs
  >>> # and decreases it exponentially after that.
  - >>> def scheduler(epoch):
  + >>> def scheduler(epoch, lr):
  ... if epoch < 10:
  - ... return 0.001
  + ... return lr
  ... else:
  - ... return 0.001 * tf.math.exp(0.1 * (10 - epoch))
  + ... return lr * tf.math.exp(-0.1)
  >>>
  >>> model = tf.keras.models.Sequential([tf.keras.layers.Dense(10)])
  >>> model.compile(tf.keras.optimizers.SGD(), loss='mse')
  @@ -1629,9 +1630,9 @@ class LearningRateScheduler(Callback):
  >>> callback = tf.keras.callbacks.LearningRateScheduler(scheduler)
  >>> history = model.fit(np.arange(100).reshape(5, 20), np.zeros(5),
  - ... epochs=2, callbacks=[callback], verbose=0)
  + ... epochs=15, callbacks=[callback], verbose=0)
  >>> round(model.optimizer.lr.numpy(), 5)
  - 0.001
  + 0.00607
  """
  @@ -1639,8 +1640,8 @@ class LearningRateScheduler(Callback):
  """Initialize a `keras.callbacks.LearningRateScheduler` callback.
  Arguments:
  - schedule: a function that takes an epoch index as input
  - (integer, indexed from 0) and returns a new
  + schedule: a function that takes an epoch index (integer, indexed from 0)
  + and current learning rate (float) as inputs and returns a new
  learning rate as output (float).
  verbose: int. 0: quiet, 1: update messages.
  """
  