theseus/optimizer/nonlinear/gauss_newton.py [18:40]:
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    def __init__(
        self,
        objective: Objective,
        linear_solver_cls: Optional[Type[LinearSolver]] = None,
        linearization_cls: Optional[Type[Linearization]] = None,
        linearization_kwargs: Optional[Dict[str, Any]] = None,
        linear_solver_kwargs: Optional[Dict[str, Any]] = None,
        abs_err_tolerance: float = 1e-10,
        rel_err_tolerance: float = 1e-8,
        max_iterations: int = 20,
        step_size: float = 1.0,
    ):
        super().__init__(
            objective,
            linear_solver_cls=linear_solver_cls,
            linearization_cls=linearization_cls,
            linearization_kwargs=linearization_kwargs,
            linear_solver_kwargs=linear_solver_kwargs,
            abs_err_tolerance=abs_err_tolerance,
            rel_err_tolerance=rel_err_tolerance,
            max_iterations=max_iterations,
            step_size=step_size,
        )
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theseus/optimizer/nonlinear/levenberg_marquardt.py [20:42]:
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    def __init__(
        self,
        objective: Objective,
        linear_solver_cls: Optional[Type[LinearSolver]] = None,
        linearization_cls: Optional[Type[Linearization]] = None,
        linearization_kwargs: Optional[Dict[str, Any]] = None,
        linear_solver_kwargs: Optional[Dict[str, Any]] = None,
        abs_err_tolerance: float = 1e-10,
        rel_err_tolerance: float = 1e-8,
        max_iterations: int = 20,
        step_size: float = 1.0,
    ):
        super().__init__(
            objective,
            linear_solver_cls=linear_solver_cls,
            linearization_cls=linearization_cls,
            linearization_kwargs=linearization_kwargs,
            linear_solver_kwargs=linear_solver_kwargs,
            abs_err_tolerance=abs_err_tolerance,
            rel_err_tolerance=rel_err_tolerance,
            max_iterations=max_iterations,
            step_size=step_size,
        )
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