def __init__()

in theseus/core/objective.py [0:0]

• 13 lines of code
• 4 McCabe index (conditional complexity)

    def __init__(self, dtype: Optional[torch.dtype] = None):
        # maps variable names to the variable objects
        self.optim_vars: OrderedDict[str, Manifold] = OrderedDict()

        # maps variable names to variables objects, for optimization variables
        # that were registered when adding cost weights.
        self.cost_weight_optim_vars: OrderedDict[str, Manifold] = OrderedDict()

        # maps aux. variable names to the container objects
        self.aux_vars: OrderedDict[str, Variable] = OrderedDict()

        # maps variable name to variable, for any kind of variable added
        self._all_variables: OrderedDict[str, Variable] = OrderedDict()

        # maps cost function names to the cost function objects
        self.cost_functions: OrderedDict[str, CostFunction] = OrderedDict()

        # maps cost weights to the cost functions that use them
        # this is used when deleting cost function to check if the cost weight
        # variables can be deleted as well (when no other function uses them)
        self.cost_functions_for_weights: Dict[CostWeight, List[CostFunction]] = {}

        # ---- The following two methods are used just to get info from
        # ---- the objective, they don't affect the optimization logic.
        # a map from optimization variables to list of theseus functions it's
        # connected to
        self.functions_for_optim_vars: Dict[Manifold, List[TheseusFunction]] = {}

        # a map from all aux. variables to list of theseus functions it's connected to
        self.functions_for_aux_vars: Dict[Variable, List[TheseusFunction]] = {}

        self._batch_size: Optional[int] = None

        self.device: torch.device = torch.device("cpu")

        self.dtype: Optional[torch.dtype] = dtype or torch.get_default_dtype()

        # this increases after every add/erase operation, and it's used to avoid
        # an optimizer to run on a stale version of the objective (since changing the
        # objective structure might break optimizer initialization).
        self.current_version = 0