code: def __init__(self, args, proj_to_decoder):
      super().__init__()
  
      self.layers = nn.ModuleList([])
      self.layers.extend(
          [
              fairseq_transformer.TransformerEncoderLayer(args)
              for i in range(args.encoder_layers)
          ]
      )
  
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 1 to create a new TransformerEncoderGivenEmbeddings object from inherited base classes: nn with example: obj = TransformerEncoderGivenEmbeddings(args, proj_to_decoder)