def METHOD_NAME(self, x: np.ndarray, out: dict, *args, **kwargs):
    num_x = x.shape[0]
    xcont = x[:, : self.space.num_numeric].astype(float)
    xenum = x[:, self.space.num_numeric :].round().astype(int)  # noqa: E203
    if self.fix is not None:
        df_x = self.space.inverse_transform(xcont, xenum)
        for k, v in self.fix.items():
            df_x[k] = v
        xcont, xenum = self.space.transform(df_x)
    tot_dims = self.acq.num_obj + self.acq.num_constr
    acq_eval = self.acq(xcont, xenum).reshape(num_x, tot_dims)
    out["F"] = acq_eval[:, : self.acq.num_obj]
    if self.acq.num_constr > 0:
        out["G"] = acq_eval[:, -1 * self.acq.num_constr :]  # noqa: E203