| from chainer.training.extensions import Evaluator | |
| from espnet.utils.training.tensorboard_logger import TensorboardLogger | |
| class BaseEvaluator(Evaluator): | |
| """Base Evaluator in ESPnet""" | |
| 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 | |