code: def base_architecture(args):
      pytorch_translate_transformer.base_architecture(args)
      args.student_decoder_embed_dim = getattr(
          args, "student_decoder_embed_dim", 128
      )
      args.student_decoder_layers = getattr(
          args, "student_decoder_layers", 3
      )
      args.student_decoder_attention_heads = getattr(
          args, "student_decoder_attention_heads", 8
      )
      args.student_decoder_lstm_units = getattr(
          args, "student_decoder_lstm_units", 128
      )
      args.student_decoder_out_embed_dim = getattr(
          args, "student_decoder_out_embed_dim", 128
      )
      args.student_decoder_reduced_attention_dim = getattr(
          args, "student_decoder_reduced_attention_dim", None
      )
  
file_path: translate/pytorch_translate/research/knowledge_distillation/dual_decoder_kd_model.py
imports: from fairseq.models import FairseqEncoderDecoderModel, register_model, register_model_architecture
  from pytorch_translate import hybrid_transformer_rnn, transformer
  from pytorch_translate.utils import torch_find
label_desc: Use image node_id 1 for calling a global function with example usage: base_architecture(args) without return types