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)
code: def __init__(self, task, encoders, decoders):
      super().__init__(encoders, decoders)
      self.task = task
      self.models = nn.ModuleDict(
          {
              key: self.__class__.single_model_cls(
                  task, encoders[key], decoders[key]
              )
              for key in self.keys
          }
      )
  
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 1 to create a new MultilingualModel object from inherited base classes: FairseqMultiModel with example: obj = MultilingualModel(task, encoders, decoders)