code: def __call__(self, trainer=None):
      ret = super().__call__(trainer)
      try:
          if trainer is not None:
              # force tensorboard to report evaluation log
              tb_logger = trainer.get_extension(
                  TensorboardLogger.default_name
              )
              tb_logger(trainer)
      except ValueError:
          pass
      return ret
  
imports: from chainer.training.extensions import Evaluator
  from espnet.utils.training.tensorboard_logger import TensorboardLogger
label_desc: Use image node_id 1 for calling the BaseEvaluator obj's underlying member method code with example usage: obj.__call__(trainer) and returns: ret