class_docstr: Two phase decoding:
  www.microsoft.com/en-us/research/uploads/prod/2018/03/final-achieving-human.pdf
  Args:
      encoder (TransformerEncoder): the encoder
      decoder (TransformerTwoPhaseDecoder): the decoder
code: def build_encoder(cls, args, src_dict, embed_tokens):
      return TransformerEncoder(args, src_dict, embed_tokens)
  
imports: import math
  import torch
  import torch.nn
  import torch.nn.functional
  from fairseq import options, utils
  from fairseq.models import FairseqEncoderDecoderModel, FairseqIncrementalDecoder, register_model, register_model_architecture
  from fairseq.models.transformer import Embedding, Linear, TransformerDecoder, TransformerEncoder
  from fairseq.modules import AdaptiveSoftmax, LayerNorm, MultiheadAttention, PositionalEmbedding, SinusoidalPositionalEmbedding
label_desc: Use image node_id 4 for calling the TwoPhaseTransformerModel obj's underlying member method code with example usage: obj.build_encoder(cls, args, src_dict, embed_tokens) and returns: TransformerEncoder