code: def build_decoder(cls, args, tgt_dict, embed_tokens):
      return TransformerDecoderFromPretrainedXLM(
          args, tgt_dict, embed_tokens
      )
  
file_path: fairseq/fairseq/models/transformer_from_pretrained_xlm.py
imports: import os
  from typing import Any, Dict
  from fairseq import checkpoint_utils
  from fairseq.data.legacy.masked_lm_dictionary import MaskedLMDictionary
  from fairseq.models import register_model, register_model_architecture
  from fairseq.models.transformer import TransformerDecoder, TransformerEncoder, TransformerModel, base_architecture
label_desc: Use image node_id 4 for calling the TransformerFromPretrainedXLMModel obj's underlying member method code with example usage: obj.build_decoder(cls, args, tgt_dict, embed_tokens) and returns: TransformerDecoderFromPretrainedXLM