ax/models/torch/botorch.py [312:325]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    @copy_doc(TorchModel.gen)
    def gen(
        self,
        n: int,
        bounds: List[Tuple[float, float]],
        objective_weights: Tensor,
        outcome_constraints: Optional[Tuple[Tensor, Tensor]] = None,
        linear_constraints: Optional[Tuple[Tensor, Tensor]] = None,
        fixed_features: Optional[Dict[int, float]] = None,
        pending_observations: Optional[List[Tensor]] = None,
        model_gen_options: Optional[TConfig] = None,
        rounding_func: Optional[Callable[[Tensor], Tensor]] = None,
        target_fidelities: Optional[Dict[int, float]] = None,
    ) -> Tuple[Tensor, Tensor, TGenMetadata, Optional[List[TCandidateMetadata]]]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



ax/models/torch/rembo.py [171:184]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    @copy_doc(TorchModel.gen)
    def gen(
        self,
        n: int,
        bounds: List[Tuple[float, float]],
        objective_weights: Tensor,
        outcome_constraints: Optional[Tuple[Tensor, Tensor]] = None,
        linear_constraints: Optional[Tuple[Tensor, Tensor]] = None,
        fixed_features: Optional[Dict[int, float]] = None,
        pending_observations: Optional[List[Tensor]] = None,
        model_gen_options: Optional[TConfig] = None,
        rounding_func: Optional[Callable[[Tensor], Tensor]] = None,
        target_fidelities: Optional[Dict[int, float]] = None,
    ) -> Tuple[Tensor, Tensor, TGenMetadata, Optional[List[TCandidateMetadata]]]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



