def METHOD_NAME(self):
    with tempfile.TemporaryDirectory() as tempdir:
        # set up engine
        def _train_func(engine, batch):
            return [batch + 1.0]
        engine = Engine(_train_func)
        # set up dummy metric
        @engine.on(Events.EPOCH_COMPLETED)
        def _update_metric(engine):
            current_metric = engine.state.metrics.get("acc", 0.1)
            engine.state.metrics["acc"] = current_metric + 0.1
        # set up testing handler
        stats_handler = TensorBoardStatsHandler(log_dir=tempdir, iteration_log=False, epoch_log=True)
        stats_handler.attach(engine)
        engine.run(range(3), max_epochs=2)
        stats_handler.close()
        # check logging output
        self.assertTrue(len(glob.glob(tempdir)) > 0)