code: def asr_stream_config_file(request, tmp_path: Path, token_list):
      main_type = request.param.split("_")[1]
  
      enc_body_conf = (
          "{'body_conf': [{'block_type': '%s', 'hidden_size': 4, "
          "'linear_size': 4, 'conv_mod_kernel_size': 3},"
          "{'block_type': 'conv1d', 'kernel_size': 2, 'output_size': 2, "
          "'batch_norm': True, 'relu': True}], "
          "'main_conf': {'dynamic_chunk_training': True',"
          "'short_chunk_size': 1, 'num_left_chunks': 1}}"
      ) % (main_type)
  
      if request.param.startswith("vgg"):
          enc_body_conf = enc_body_conf[:-1] + (
              ",'input_conf': {'vgg_like': True}}"
          )
  
      decoder_conf = "{'hidden_size': 4}"
      joint_net_conf = "{'joint_space_size': 4}"
  
      ASRTransducerTask.main(
          cmd=[
              "--dry_run",
              "true",
              "--output_dir",
              str(tmp_path / "asr_stream"),
              "--token_list",
              str(token_list),
              "--token_type",
              "char",
              "--encoder_conf",
              enc_body_conf,
              "--decoder",
              "rnn",
              "--decoder_conf",
              decoder_conf,
              "--joint_network_conf",
              joint_net_conf,
          ]
      )
      return tmp_path / "asr_stream" / "config.yaml"
  
imports: import string
  from argparse import ArgumentParser
  from distutils.version import LooseVersion
  from pathlib import Path
  from typing import List
  import numpy
  import pytest
  import torch
  from espnet2.asr_transducer.beam_search_transducer import Hypothesis
  from espnet2.bin.asr_transducer_inference import Speech2Text, get_parser, main
  from espnet2.tasks.asr_transducer import ASRTransducerTask
  from espnet2.tasks.lm import LMTask
label_desc: Use image node_id 6 for calling a global function with example usage: asr_stream_config_file(request, tmp_path, token_list) and returns: unknown