code: def base_architecture(args):
      # default architecture
      hybrid_transformer_rnn.base_architecture(args)
      args.char_cnn_params = getattr(
          args, "char_cnn_params", "[(50, 1), (100,2)]"
      )
      args.char_cnn_nonlinear_fn = getattr(
          args, "chr_cnn_nonlinear_fn", "relu"
      )
      args.char_cnn_num_highway_layers = getattr(
          args, "char_cnn_num_highway_layers", "2"
      )
  
imports: import math
  from ast import literal_eval
  from typing import List
  import torch
  import torch.nn
  import torch.nn.functional
  from fairseq.models import register_model, register_model_architecture
  from pytorch_translate import char_encoder, char_source_hybrid, char_source_model, hybrid_transformer_rnn, transformer, vocab_constants
  from pytorch_translate.data.dictionary import TAGS
  from pytorch_translate.utils import maybe_cuda
label_desc: Use image node_id 1 for calling a global function with example usage: base_architecture(args) without return types