}
	}
}

func tenRunes(r rune) string {
	runes := make([]rune, 10)
	for i := range runes {
		runes[i] = r
	}
	return string(runes)
}

// User-defined self-inverse mapping function
func rot13(r rune) rune {
	const step = 13
	if r >= 'a' && r <= 'z' {
		return ((r - 'a' + step) % 26) + 'a'
	}
	if r >= 'A' && r <= 'Z' {
		return ((r - 'A' + step) % 26) + 'A'
	}

      // Run shape inference function for newly added node.
      status->status = desc->graph->refiner.AddNode(ret);
    }
    if (status->status.ok()) {
      // Add the node to the name-to-node mapping.
      desc->graph->name_map[ret->name()] = ret;
    } else if (ret != nullptr) {
      desc->graph->graph.RemoveNode(ret);
      ret = nullptr;
    }
  }

  delete desc;

Initially, the bound type parameters are known but the map is empty.
During type unification, if a new type argument <code>A</code> is inferred,
the respective mapping <code>P ➞ A</code> from type parameter to argument
is added to the map.
Conversely, when comparing types, a known type argument
(a type argument for which a map entry already exists)

*   `tf.print`:
    *   Bug fix in `tf.print()` with `OrderedDict` where if an `OrderedDict`
        didn't have the keys sorted, the keys and values were not being printed
        in accordance with their correct mapping.
*   `tf.train.Checkpoint`:
    *   Now accepts a `root` argument in the initialization, which generates a
        checkpoint with a root object. This allows users to create a