6c1fe5c811f82c571af94f787b4721f3a1cc7ca4,src/sdk/pynni/nni/nas/pytorch/darts/mutator.py,DartsMutator,sample_final,#DartsMutator#,30

Before Change

                result[mutable.key] = F.one_hot(index, num_classes=mutable.length).view(-1).bool()
        for mutable in self.mutables:
            if isinstance(mutable, InputChoice):
                weights = torch.tensor([edges_max.get(src_key, 0.) for src_key in mutable.choose_from])  // pylint: disable=not-callable
                _, topk_edge_indices = torch.topk(weights, mutable.n_chosen or mutable.n_candidates)
                selected_multihot = []
                for i, src_key in enumerate(mutable.choose_from):

After Change

        for mutable in self.mutables:
            if isinstance(mutable, InputChoice) and mutable.n_chosen is not None:
                weights = []
                for src_key in mutable.choose_from:
                    if src_key not in edges_max:
                        _logger.warning("InputChoice.NO_KEY in "%s" is weighted 0 when selecting inputs.", mutable.key)
                    weights.append(edges_max.get(src_key, 0.))
                weights = torch.tensor(weights)  // pylint: disable=not-callable
                _, topk_edge_indices = torch.topk(weights, mutable.n_chosen)
                selected_multihot = []
                for i, src_key in enumerate(mutable.choose_from):

Instances