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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def relabel_variables(self, mapping, inplace=True):
 """Relabel variables of a binary quadratic model as specified by mapping. Args: mapping (dict):
 Dict mapping current variable labels to new ones. If an incomplete mapping is provided, unmapped variables retain their current labels. inplace (bool, optional, default=True):
 If True, the binary quadratic model is updated in-place; otherwise, a new binary quadratic model is returned. Returns: :class:`.BinaryQuadraticModel`: A binary quadratic model with the variables relabeled. If `inplace` is set to True, returns itself. Examples: This example creates a binary quadratic model with two variables and relables one. BinaryQuadraticModel({1: 1.0, 'a': 0.0}, {('a', 1):
 -1}, 0.0, Vartype.SPIN) This example creates a binary quadratic model with two variables and returns a new model with relabled variables. {('a', 'b'):
 -1} """

        try:
            old_labels = set(mapping)
            new_labels = set(itervalues(mapping))
        except TypeError:
            raise ValueError("mapping targets must be hashable objects")

        for v in new_labels:
            if v in self.linear and v not in old_labels:
                raise ValueError(('A variable cannot be relabeled "{}" without also relabeling '
                                  "the existing variable of the same name").format(v))

        if inplace:
            shared = old_labels & new_labels
            if shared:
                old_to_intermediate, intermediate_to_new = resolve_label_conflict(mapping, old_labels, new_labels)

                self.relabel_variables(old_to_intermediate, inplace=True)
                self.relabel_variables(intermediate_to_new, inplace=True)
                return self

            linear = self.linear
            quadratic = self.quadratic
            adj = self.adj

            # rebuild linear and adj with the new labels
            for old in list(linear):
                if old not in mapping:
                    continue

                new = mapping[old]

                # get the new interactions that need to be added
                new_interactions = [(new, v, adj[old][v]) for v in adj[old]]

                self.add_variable(new, linear[old])
                self.add_interactions_from(new_interactions)
                self.remove_variable(old)

            return self
        else:
            return BinaryQuadraticModel({mapping.get(v, v): bias for v, bias in iteritems(self.linear)},
                                        {(mapping.get(u, u), mapping.get(v, v)): bias
                                         for (u, v), bias in iteritems(self.quadratic)},
                                        self.offset, self.vartype)