class_docstr: Train Transformer models for multiple language pairs simultaneously.
  
  Requires `--task multilingual_translation`.
  
  We inherit all arguments from TransformerModel and assume that all language
  pairs use a single Transformer architecture. In addition, we provide several
  options that are specific to the multilingual setting.
  
  Args:
      --share-encoder-embeddings: share encoder embeddings across all source languages
      --share-decoder-embeddings: share decoder embeddings across all target languages
      --share-encoders: share all encoder params (incl. embeddings) across all source languages
      --share-decoders: share all decoder params (incl. embeddings) across all target languages
docstr: Add model-specific arguments to the parser.
docstr_tok: ["Add","model-specific","arguments","to","the","parser","."]
code: def add_args(parser):
      """Add model-specific arguments to the parser."""
      TransformerModel.add_args(parser)
      parser.add_argument(
          "--share-encoder-embeddings",
          action="store_true",
          help="share encoder embeddings across languages",
      )
      parser.add_argument(
          "--share-decoder-embeddings",
          action="store_true",
          help="share decoder embeddings across languages",
      )
      parser.add_argument(
          "--share-encoders",
          action="store_true",
          help="share encoders across languages",
      )
      parser.add_argument(
          "--share-decoders",
          action="store_true",
          help="share decoders across languages",
      )
  
file_path: fairseq/fairseq/models/multilingual_transformer.py
imports: from collections import OrderedDict
  from fairseq import utils
  from fairseq.models import FairseqMultiModel, register_model, register_model_architecture
  from fairseq.models.transformer import Embedding, TransformerDecoder, TransformerEncoder, TransformerModel, base_architecture
  from fairseq.utils import safe_hasattr
label_desc: Use image node_id 2 for calling the MultilingualTransformerModel obj's underlying member method code with example usage: obj.add_args(parser) without return types