message: Minor correction in description of clip_by_norm.
diff: @@ -126,8 +126,8 @@ def clip_by_norm(t, clip_norm, axes=None, name=None):
  In this case, the L2-norm of the output tensor is `clip_norm`.
  As another example, if `t` is a matrix and `axes == [1]`, then each row
  - of the output will have L2-norm equal to `clip_norm`. If `axes == [0]`
  - instead, each column of the output will be clipped.
  + of the output will have L2-norm less than or equal to `clip_norm`. If
  + `axes == [0]` instead, each column of the output will be clipped.
  This operation is typically used to clip gradients before applying them with
  an optimizer.
  