code: def forward(self, x, positions, encoder_padding_mask):
      # encoder layers
      for layer in self.layers:
          x = layer(x, encoder_padding_mask)
  
      return x
  
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 2 for calling the TransformerEncoderGivenEmbeddings obj's underlying member method code with example usage: obj.forward(x, positions, encoder_padding_mask) and returns: x