message: Correct natural exp decay documentation.
diff: @@ -356,7 +356,15 @@ def natural_exp_decay(learning_rate,
  The function returns the decayed learning rate. It is computed as:
  ```python
  - decayed_learning_rate = learning_rate * exp(-decay_rate * global_step)
  + decayed_learning_rate = learning_rate * exp(-decay_rate * global_step /
  + decay_step)
  + ```
  +
  + or, if `staircase` is `True`, as:
  +
  + ```python
  + decayed_learning_rate = learning_rate * exp(-decay_rate * floor(global_step /
  + decay_step))
  ```
  Example: decay exponentially with a base of 0.96:
  @@ -365,8 +373,10 @@ def natural_exp_decay(learning_rate,
  ...
  global_step = tf.Variable(0, trainable=False)
  learning_rate = 0.1
  + decay_steps = 5
  k = 0.5
  - learning_rate = tf.train.exponential_time_decay(learning_rate, global_step, k)
  + learning_rate = tf.train.natural_exp_decay(learning_rate, global_step,
  + decay_steps, k)
  # Passing global_step to minimize() will increment it at each step.
  learning_step = (
  