training.py 文件源码

def training(self):
        training_dir = self._training_dir
        hyperparam_path = os.path.join(training_dir, 'hyperparams-config.yaml')
        model_weights_path = os.path.join(training_dir, 'model-weights.hdf5')

        config_builder = config.FileConfigBuilder(hyperparam_path)
        config_dict = config_builder.build_config()._asdict()
        if self._config_override:
            config_dict.update(self._config_override)
            config_dict['time_limit'] = parse_timedelta(
                                                    config_dict['time_limit'])
            if 'epochs' in self._config_override:
                config_dict['time_limit'] = None
            elif 'time_limit' in self._config_override:
                config_dict['epochs'] = None

        conf = config.Config(**config_dict)
        model_weights_path = (model_weights_path if self._load_model_weights
                              else None)
        return Training(training_label=self._new_training_label,
                        conf=conf,
                        model_weights_path=model_weights_path,
                        log_metrics_period=self._log_metrics_period,
                        explode_patience=sys.maxsize)