code: def training_args(
      self,
      wordvec_pretrain_file,
      tmpdirname,
      train_treebank_file,
      eval_treebank_file,
      *additional_args,
  ):
      # let's not make the model huge...
      args = [
          "--pattn_num_layers",
          "0",
          "--pattn_d_model",
          "128",
          "--lattn_d_proj",
          "0",
          "--use_lattn",
          "--hidden_size",
          "20",
          "--delta_embedding_dim",
          "10",
          "--wordvec_pretrain_file",
          wordvec_pretrain_file,
          "--data_dir",
          tmpdirname,
          "--save_dir",
          tmpdirname,
          "--save_name",
          "test.pt",
          "--save_each_name",
          os.path.join(tmpdirname, "each_%02d.pt"),
          "--train_file",
          train_treebank_file,
          "--eval_file",
          eval_treebank_file,
          "--epoch_size",
          "6",
          "--train_batch_size",
          "3",
          "--shorthand",
          "en_test",
      ]
      args = args + list(additional_args)
      args = constituency_parser.parse_args(args)
      # just in case we change the defaults in the future
      args["wandb"] = None
      return args
  
imports: from collections import defaultdict
  import logging
  import pathlib
  import tempfile
  import pytest
  import torch
  from torch import optim
  from stanza import Pipeline
  from stanza.models import constituency_parser
  from stanza.models.common import pretrain
  from stanza.models.common.bert_embedding import load_bert, load_tokenizer
  from stanza.models.common.foundation_cache import FoundationCache
  from stanza.models.common.utils import set_random_seed
  from stanza.models.constituency import lstm_model
  from stanza.models.constituency import trainer
  from stanza.models.constituency import tree_reader
  from stanza.tests import *
label_desc: Use image node_id 8 for calling the TestTrainer obj's underlying member method code with example usage: obj.training_args(wordvec_pretrain_file, tmpdirname, train_treebank_file, eval_treebank_file) and returns: args