message: Fix documentation for inverse_time_decay.
diff: @@ -362,7 +362,13 @@ def inverse_time_decay(learning_rate, global_step, decay_steps, decay_rate,
  The function returns the decayed learning rate. It is computed as:
  ```python
  - decayed_learning_rate = learning_rate / (1 + decay_rate * t)
  + decayed_learning_rate = learning_rate / (1 + decay_rate * global_step / decay_step)
  + ```
  +
  + or, if `staircase` is `True`, as:
  +
  + ```python
  + decayed_learning_rate = learning_rate / (1 + decay_rate * floor(global_step / decay_step))
  ```
  Example: decay 1/t with a rate of 0.5:
  @@ -371,8 +377,9 @@ def inverse_time_decay(learning_rate, global_step, decay_steps, decay_rate,
  ...
  global_step = tf.Variable(0, trainable=False)
  learning_rate = 0.1
  - k = 0.5
  - learning_rate = tf.train.inverse_time_decay(learning_rate, global_step, k)
  + decay_steps = 1.0
  + decay_rate = 0.5
  + learning_rate = tf.train.inverse_time_decay(learning_rate, global_step, decay_steps, decay_rate)
  # Passing global_step to minimize() will increment it at each step.
  learning_step = (
  