    def upgrade_state_dict_named(self, state_dict, name):
        """Upgrade a (possibly old) state dict for new versions of fairseq."""
        for i in range(self.num_layers):
            # update layer norms
            self.layers[i].upgrade_state_dict_named(
                state_dict, "{}.layers.{}".format(name, i)
            )

        version_key = "{}.version".format(name)
        if utils.item(state_dict.get(version_key, torch.Tensor([1]))[0]) < 2:
            # earlier checkpoints did not normalize after the stack of layers
            self.layer_norm = None
            self.normalize = False
            state_dict[version_key] = torch.Tensor([1])
        return state_dict
Upgrade a (possibly old) state dict for new versions of fairseq.
fairseq/models/transformer/transformer_encoder.py