auto collective_executor_handle = context->GetCollectiveExecutorHandle();
  tensorflow::Notification done;
  collective_executor_handle->get()->remote_access()->CheckPeerHealth(
      task, timeout_in_ms, [&done, status](const Status& s) {
        status->status = s;
        done.Notify();
      });
  done.WaitForNotification();
}

TF_ShapeAndTypeList* TF_NewShapeAndTypeList(int num_items) {

  TF_Graph* graph = TF_NewGraph();

  // Make two scalar constants.
  TF_Operation* one = ScalarConst(1, graph, s, "one");
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  TF_Operation* two = ScalarConst(2, graph, s, "two");
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  // Add oper.
  TF_Operation* add = Add(one, two, graph, s, "add");
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

                       var_name,
                       query_item,
                       enabled_by_default,
                       question=None,
                       yes_reply=None,
                       no_reply=None,
                       bazel_config_name=None):
  """Set boolean action_env variable.

  Ask user if query_item will be enabled. Default is used if no input is given.

      "important to you");
  return EmptyWhileParams();
#else
  if (ninputs == 0) {
    status->status =
        InvalidArgument("TF_NewWhile() must be passed at least one input");
    return EmptyWhileParams();
  }

  TF_Graph* cond_graph = TF_NewGraph();
  TF_Graph* body_graph = TF_NewGraph();
  cond_graph->parent = g;
  cond_graph->parent_inputs = inputs;

        of built-in training loops such as `tf.keras` `compile` and `fit`, we
        expect reduction value to be `SUM` or `NONE`. Using `AUTO` in that case
        will raise an error.
    *   `NONE`: Weighted losses with one dimension reduced (axis=-1, or axis
        specified by loss function). When this reduction type used with built-in