message: Updated optimizers.py according to PR feedback
diff: @@ -112,8 +112,8 @@ def optimize_loss(loss,
  clip_gradients: float, callable or `None`. If a float is provided, a global
  clipping is applied to prevent the norm of the gradient from exceeding
  this value. Alternatively, a callable can be provided, e.g.,
  - adaptive_clipping_fn(). This callable takes a `list` of
  - `(gradients, variables)` `tuple`s and returns the same thing with the
  + `adaptive_clipping_fn()`. This callable takes a list of
  + `(gradients, variables)` tuples and returns the same thing with the
  gradients modified.
  learning_rate_decay_fn: function, takes `learning_rate` and `global_step`
  `Tensor`s, returns `Tensor`.
  