def upgrade_state_dict_named(self, state_dict, name):
        """
        Rename layer norm states from `...layer_norms.0.weight` to
        `...self_attn_layer_norm.weight` and `...layer_norms.1.weight` to
        `...final_layer_norm.weight`
        """
        layer_norm_map = {
            '0': 'self_attn_layer_norm',
            '1': 'final_layer_norm'
        }
        for old, new in layer_norm_map.items():
            for m in ('weight', 'bias'):
                k = '{}.layer_norms.{}.{}'.format(name, old, m)
                if k in state_dict:
                    state_dict[
                        '{}.{}.{}'.format(name, new, m)
                    ] = state_dict[k]
                    del state_dict[k]

        Rename layer norm states from `...layer_norms.0.weight` to
        `...self_attn_layer_norm.weight` and `...layer_norms.1.weight` to
        `...final_layer_norm.weight`
        
infoxlm/fairseq/fairseq/modules/transformer_layer.py