code: def base_architecture_wp(args):
      # default architecture
      rnn.base_architecture(args)
      args.predictor_hidden_dim = getattr(
          args, "predictor_hidden_dim", 512
      )
      args.topk_labels_per_source_token = getattr(
          args, "topk_labels_per_source_token", None
      )
  
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 a global function with example usage: base_architecture_wp(args) without return types