var (
		idx              int
		inName           bool
		afterParenthesis bool
		namedMap         = make(map[string]interface{}, len(expr.Vars))
	)

	for _, v := range expr.Vars {
		switch value := v.(type) {
		case sql.NamedArg:
			namedMap[value.Name] = value.Value
		case map[string]interface{}:
			for k, v := range value {
				namedMap[k] = v
			}
		default:
			var appendFieldsToMap func(reflect.Value)

        ArgumentCaptor<String> nameCap = ArgumentCaptor.forClass(String.class);
        ArgumentCaptor<String> hostCap = ArgumentCaptor.forClass(String.class);
        ArgumentCaptor<String> domCap = ArgumentCaptor.forClass(String.class);
        ArgumentCaptor<Integer> rnCap = ArgumentCaptor.forClass(Integer.class);

			fns = append(fns, cs[idx].handler)
		}
	}

	return
}

func removeCallbacks(cs []*callback, nameMap map[string]bool) []*callback {
	callbacks := make([]*callback, 0, len(cs))
	for _, callback := range cs {
		if nameMap[callback.name] {
			continue
		}
		callbacks = append(callbacks, callback)
	}
	return callbacks

  g->mu.unlock();
  if (del) delete g;
}

TF_Operation* TF_GraphOperationByName(TF_Graph* graph, const char* oper_name) {
  mutex_lock l(graph->mu);
  auto iter = graph->name_map.find(oper_name);
  if (iter == graph->name_map.end()) {
    return nullptr;
  } else {
    return ToOperation(iter->second);
  }
}

TF_Operation* TF_GraphNextOperation(TF_Graph* graph, size_t* pos) {

  // Runs shape inference.
  tensorflow::ShapeRefiner refiner TF_GUARDED_BY(mu);

  // Maps from name of an operation to the Node* in 'graph'.
  std::unordered_map<tensorflow::string, tensorflow::Node*> name_map
      TF_GUARDED_BY(mu);

  // The keys of this map are all the active sessions using this graph. Each
  // value records whether the graph has been mutated since the corresponding