def _select_optimizer_cls()

in nevergrad/optimization/optimizerlib.py [0:0]

• 30 lines of code
• 19 McCabe index (conditional complexity)

    def _select_optimizer_cls(self) -> base.OptCls:
        # Extracting info as far as possible.
        assert self.budget is not None
        funcinfo = self.parametrization.function
        optimClass: base.OptCls
        if self.has_noise and (self.has_discrete_not_softmax or not funcinfo.metrizable):
            if self.budget > 10000:
                optimClass = RecombiningPortfolioOptimisticNoisyDiscreteOnePlusOne
            else:
                optimClass = ParametrizedOnePlusOne(
                    crossover=True, mutation="discrete", noise_handling="optimistic"
                )
        elif self._arity > 0:
            if self.budget < 1000 and self.num_workers == 1:
                optimClass = DiscreteBSOOnePlusOne
            elif self.num_workers > 2:
                optimClass = CMandAS2  # type: ignore
            else:
                optimClass = super()._select_optimizer_cls()
        else:
            if (
                not (self.has_noise and self.fully_continuous and self.dimension > 100)
                and not (self.has_noise and self.fully_continuous)
                and not (self.num_workers > self.budget / 5)
                and (self.num_workers == 1 and self.budget > 6000 and self.dimension > 7)
                and self.num_workers < self.budget
            ):
                optimClass = ChainMetaModelPowell
            else:
                optimClass = super()._select_optimizer_cls()

        return optimClass