body_fn, params->name, &loop_outputs);

  // Update name_map with newly-created ops.
  // TODO(skyewm): right now BuildWhileLoop() may alter the graph if it returns
  // a bad status. Once we fix this, we may want to return early instead of
  // executing the following code.
  for (int i = first_new_node_id; i < parent->graph.num_node_ids(); ++i) {
    Node* new_node = parent->graph.FindNodeId(i);

  }

 private:
  bool first_call_ = true;
};

// After the graph pass is registered, it takes effect globally and can affect
// other test cases. Define a static variable to switch it on and off.
bool GraphErrorInjectionPass::enabled_ = false;

// Test to ensure that a registered graph optimization pass is only executed

      auto& indices = iter->second;
      if (std::find(indices.begin(), indices.end(), idx) != indices.end()) {
        return InvalidArgument("TF_Output ", node->name(), ":", idx,
                               " appears more than once in the input list");
      }
      indices.push_back(idx);
    }
  }
  return absl::OkStatus();
}

// Converts `noutputs` and `outputs` into `outputs_tensors` and does various
// checks while doing so.

    tensorflow::ImmediateExecutionTensorHandle* unwrapped_handle =
        tensorflow::unwrap(handles[i]);
    if (tensorflow::CustomDeviceTensorHandle::classof(unwrapped_handle)) {
      // One of the inputs we're trying to pack is on a custom device. We'll let
      // the first custom device we see handle all of the packing.
      auto* custom_device_handle =

  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);