def start_trainer(self, trainer: Trainer, env_manager: EnvManager) -> None:
     self.trainers[trainer.brain_name] = trainer
     self.logger.info(trainer)
     if self.train_model:
         trainer.write_tensorboard_text("Hyperparameters",
                                        trainer.parameters)
     env_manager.set_policy(trainer.brain_name, trainer.policy)
 def trainer_update_func(self, trainer: Trainer) -> None:
     while not self.kill_trainers:
         with hierarchical_timer("trainer_advance"):
             trainer.advance()