class_docstr: To use, you must extend this class and define single_model_cls as a class
  variable. Example:
  
      @register_model("multilingual_transformer")
      class MultilingualTransformerModel(MultilingualModel):
          single_model_cls = TransformerModel
  
          @staticmethod
          def add_args(parser):
              TransformerModel.add_args(parser)
              MultilingualModel.add_args(parser)
docstr: Add model-specific arguments to the parser.
code: def add_args(parser):
      """Add model-specific arguments to the 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: translate/pytorch_translate/multilingual_model.py
imports: from collections import OrderedDict
  import torch.nn
  from fairseq.models import FairseqMultiModel, register_model
  from pytorch_translate import common_layers, utils
label_desc: Use image node_id 2 for calling the MultilingualModel obj's underlying member method code with example usage: obj.add_args(parser) without return types