message: Testable Doc Strings for `tf.nn.softmax_cross_entropy_with_logits`.
diff: @@ -3068,6 +3068,13 @@ def softmax_cross_entropy_with_logits_v2(labels, logits, axis=-1, name=None):
  If using exclusive `labels` (wherein one and only
  one class is true at a time), see `sparse_softmax_cross_entropy_with_logits`.
  + Usage:
  + >>> logits = [[0.6, 0.2, 0.2], [0.0, 0.9, 0.1]]
  + >>> labels = [[1.0, 0.0, 0.0], [0.0, 1.0, 0.0]]
  + >>> tf.nn.softmax_cross_entropy_with_logits(labels, logits)
  + <tf.Tensor: id=103, shape=(2,), dtype=float32,
  + numpy=array([0.8504244, 0.6183691], dtype=float32)>
  +
  **WARNING:** This op expects unscaled logits, since it performs a `softmax`
  on `logits` internally for efficiency. Do not call this op with the
  output of `softmax`, as it will produce incorrect results.
  