Example #1
0
def create_predictor(trainer, model_type, use_gpu, action_dim=None):
    if model_type == ModelType.SOFT_ACTOR_CRITIC.value:
        predictor = GymSACPredictor(trainer, action_dim)
    elif model_type in (
        ModelType.PYTORCH_DISCRETE_DQN.value,
        ModelType.PYTORCH_PARAMETRIC_DQN.value,
    ):
        predictor = GymDQNPredictor(trainer, action_dim)
    else:
        raise NotImplementedError()
    return predictor
Example #2
0
def create_predictor(trainer, model_type, use_gpu):
    if model_type == ModelType.CONTINUOUS_ACTION.value:
        predictor = GymDDPGPredictor(trainer)
    elif model_type == ModelType.SOFT_ACTOR_CRITIC.value:
        predictor = GymSACPredictor(trainer)
    elif model_type in (
            ModelType.PYTORCH_DISCRETE_DQN.value,
            ModelType.PYTORCH_PARAMETRIC_DQN.value,
    ):
        predictor = GymDQNPredictor(trainer)
    else:
        raise NotImplementedError()
    return predictor