code: def make_arg(**kwargs):
      defaults = dict(
          elayers=1,
          subsample="2_2",
          etype="blstm",
          eunits=16,
          eprojs=16,
          dtype="lstm",
          dlayers=1,
          dunits=16,
          atype="add",
          aheads=2,
          mtlalpha=0.5,
          lsm_type="",
          lsm_weight=0.0,
          sampling_probability=0.0,
          adim=16,
          dropout_rate=0.0,
          dropout_rate_decoder=0.0,
          nbest=5,
          beam_size=3,
          penalty=0.5,
          maxlenratio=1.0,
          minlenratio=0.0,
          ctc_weight=0.0,  # dummy
          ctc_window_margin=0,  # dummy
          verbose=2,
          char_list=["あ", "い", "う", "え", "お"],
          outdir=None,
          report_bleu=False,
          sym_space="<space>",
          sym_blank="<blank>",
          sortagrad=0,
          context_residual=False,
          tie_src_tgt_embedding=False,
          tie_classifier=False,
          multilingual=False,
          replace_sos=False,
          tgt_lang=False,
      )
      defaults.update(kwargs)
      return argparse.Namespace(**defaults)
  
imports: from __future__ import division
  import argparse
  import importlib
  import os
  import tempfile
  from test.utils_test import make_dummy_json_mt
  import chainer
  import numpy
  import pytest
  import torch
  from espnet.nets.pytorch_backend.nets_utils import pad_list
  from espnet.utils.training.batchfy import make_batchset
label_desc: Use image node_id 1 for calling a global function with example usage: make_arg() and returns: argparse