code: def build_decoder(cls, args, tgt_dict, embed_tokens):
      decoder = InsertionTransformerDecoder(
          args, tgt_dict, embed_tokens
      )
      if getattr(args, "apply_bert_init", False):
          decoder.apply(init_bert_params)
      return decoder
  
imports: import numpy
  import torch
  import torch.nn.functional
  from fairseq.models import register_model, register_model_architecture
  from fairseq.models.nat import FairseqNATModel, LevenshteinTransformerDecoder, LevenshteinTransformerModel, ensemble_decoder
  from fairseq.models.transformer import Linear
  from fairseq.modules.transformer_sentence_encoder import init_bert_params
  from fairseq.utils import new_arange
label_desc: Use image node_id 3 for calling the InsertionTransformerModel obj's underlying member method code with example usage: obj.build_decoder(cls, args, tgt_dict, embed_tokens) and returns: decoder