def __deepcopy__()

in botorch/models/pairwise_gp.py [0:0]

• 26 lines of code
• 5 McCabe index (conditional complexity)

    def __deepcopy__(self, memo) -> PairwiseGP:
        attrs = (
            "datapoints",
            "comparisons",
            "covar",
            "covar_inv",
            "covar_chol",
            "likelihood_hess",
            "utility",
            "hlcov_eye",
        )
        if any(getattr(self, attr) is not None for attr in attrs):
            # Temporarily remove non-leaf tensors so that pytorch allows deepcopy
            old_attr = {}
            for attr in attrs:
                old_attr[attr] = getattr(self, attr)
                setattr(self, attr, None)
            new_model = deepcopy(self, memo)
            # now set things back
            for attr in attrs:
                setattr(self, attr, old_attr[attr])
            return new_model
        else:
            dcp = self.__deepcopy__
            # make sure we don't fall into the infinite recursive loop
            self.__deepcopy__ = None
            new_model = deepcopy(self, memo)
            self.__deepcopy__ = dcp
            return new_model