mtrl/agent/grad_manipulation.py [26:42]:
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    def __init__(
        self,
        env_obs_shape: List[int],
        action_shape: List[int],
        action_range: Tuple[int, int],
        multitask_cfg: ConfigType,
        agent_cfg: ConfigType,
        device: torch.device,
        cfg_to_load_model: Optional[ConfigType] = None,
        should_complete_init: bool = True,
    ):
        """Base Class for Gradient Manipulation Algorithms."""
        agent_cfg_copy = deepcopy(agent_cfg)
        OmegaConf.set_struct(agent_cfg_copy, False)
        agent_cfg_copy.cfg_to_load_model = None
        agent_cfg_copy.should_complete_init = False
        agent_cfg_copy.loss_reduction = "none"
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mtrl/agent/gradnorm.py [15:31]:
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    def __init__(
        self,
        env_obs_shape: List[int],
        action_shape: List[int],
        action_range: Tuple[int, int],
        multitask_cfg: ConfigType,
        agent_cfg: ConfigType,
        device: torch.device,
        cfg_to_load_model: Optional[ConfigType] = None,
        should_complete_init: bool = True,
    ):
        """GradNorm algorithm."""
        agent_cfg_copy = deepcopy(agent_cfg)
        OmegaConf.set_struct(agent_cfg_copy, False)
        agent_cfg_copy.cfg_to_load_model = None
        agent_cfg_copy.should_complete_init = False
        agent_cfg_copy.loss_reduction = "none"
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