code: def upgrade_state_dict_named(self, state_dict, name):
      for i in range(len(self.layers)):
          # update layer norms
          self.layers[i].upgrade_state_dict_named(
              state_dict, f"{name}.layers.{i}"
          )
  
imports: import abc
  import math
  import torch
  import torch.nn
  import torch.nn.functional
  from fairseq import utils
  from fairseq.models import FairseqIncrementalDecoder, transformer
  from pytorch_translate import rnn_cell, utils, vocab_reduction
  from pytorch_translate.research.lexical_choice import lexical_translation
label_desc: Use image node_id 3 for calling the TransformerEncoderGivenEmbeddings obj's underlying member method code with example usage: obj.upgrade_state_dict_named(state_dict, name) without return types