class_docstr: A subclass which adds words prediction to RNN arch.
class_docstr_tok: ["A","subclass","which","adds","words","prediction","to","RNN","arch","."]
code: def add_args(parser):
      rnn.RNNModel.add_args(parser)
      parser.add_argument(
          "--predictor-hidden-dim",
          type=int,
          metavar="N",
          help="word predictor num units",
      )
  
      parser.add_argument(
          "--topk-labels-per-source-token",
          type=int,
          metavar="N",
          help="Top k predicted words from the word predictor module for use"
          "as translation candidates in vocab reduction module, as a multiple"
          "of source tokens.",
      )
  
file_path: translate/pytorch_translate/word_prediction/word_prediction_model.py
imports: from fairseq.models import FairseqEncoderDecoderModel, register_model, register_model_architecture
  from pytorch_translate import rnn
  from pytorch_translate.rnn import LSTMSequenceEncoder, RNNDecoder, RNNEncoder, RNNModel
  from pytorch_translate.utils import torch_find
  from pytorch_translate.word_prediction import word_predictor
label_desc: Use image node_id 1 for calling the RNNWordPredictionModel obj's underlying member method code with example usage: obj.add_args(parser) without return types