Method test_loss_dict

tests/handlers/test_handler_stats.py:123–153

(self)

            self.assertEqual(content_count, 2)  # 2 = len([1, 3]) from event_filter

    def test_loss_dict(self):
        log_stream = StringIO()
        log_handler = logging.StreamHandler(log_stream)
        log_handler.setLevel(logging.INFO)
        key_to_handler = "test_logging"
        key_to_print = "myLoss1"

        # set up engine
        def _train_func(engine, batch):
            return [torch.tensor(0.0)]

        engine = Engine(_train_func)

        # set up testing handler
        logger = logging.getLogger(key_to_handler)
        logger.setLevel(logging.INFO)
        logger.addHandler(log_handler)
        stats_handler = StatsHandler(name=key_to_handler, output_transform=lambda x: {key_to_print: x[0]})
        stats_handler.attach(engine)

        engine.run(range(3), max_epochs=2)

        # check logging output
        output_str = log_stream.getvalue()
        log_handler.close()
        has_key_word = re.compile(f".*{key_to_print}.*")
        content_count = 0
        for line in output_str.split("\n"):
            if has_key_word.match(line):
                content_count += 1
        self.assertGreater(content_count, 0)

    def test_loss_file(self):
        key_to_handler = "test_logging"