code: def run_trainer(
      self,
      stage: str,
      model_name: str,
      eval_steps: int = 10,
      num_train_epochs: int = 1,
      distributed: bool = True,
      fp16: bool = True,
  ):
      output_dir = self.get_auto_remove_tmp_dir("./xxx", after=False)
      args = f"""
              --model_name_or_path {model_name}
              --dataset_name hf-internal-testing/librispeech_asr_dummy
              --dataset_config_name clean
              --train_split_name validation
              --validation_split_name validation
              --output_dir {output_dir}
              --num_train_epochs {str(num_train_epochs)}
              --per_device_train_batch_size 2
              --per_device_eval_batch_size 2
              --evaluation_strategy steps
              --learning_rate 5e-4
              --warmup_steps 8
              --orthography timit
              --preprocessing_num_workers 1
              --group_by_length
              --freeze_feature_extractor
              --report_to none
              --save_steps 0
              --eval_steps {eval_steps}
              --report_to none
          """.split()
  
      if fp16:
          args.extend(["--fp16"])
  
      # currently ds_config_wav2vec2_zero.json requires "zero_optimization.find_unused_parameters": true,
      # hence the separate config files
      ds_args = f"--deepspeed {self.test_file_dir_str}/ds_config_wav2vec2_{stage}.json".split()
      script = [
          f"{self.examples_dir_str}/research_projects/wav2vec2/run_asr.py"
      ]
      launcher = self.get_launcher(distributed)
  
      cmd = launcher + script + args + ds_args
      # keep for quick debug
      # print(" ".join([f"\nPYTHONPATH={self.src_dir_str}"] +cmd)); die
      execute_subprocess_async(cmd, env=self.get_env())
  
      return output_dir
  
imports: import sys
  from pathlib import Path
  import dataclasses
  import io
  import itertools
  import json
  import os
  import unittest
  from copy import deepcopy
  from parameterized import parameterized
  from transformers import TrainingArguments, is_torch_available
  from transformers.deepspeed import is_deepspeed_available
  from transformers.file_utils import WEIGHTS_NAME
  from transformers.testing_utils import CaptureLogger, ExtendSysPath, TestCasePlus, execute_subprocess_async, get_gpu_count, mockenv_context, require_deepspeed, require_torch_gpu, require_torch_multi_gpu, slow
  from transformers.trainer_utils import set_seed
label_desc: Use image node_id 7 for calling the TestDeepSpeedWav2Vec2 obj's underlying member method code with example usage: obj.run_trainer(stage, model_name, eval_steps, num_train_epochs, distributed, fp16) and returns: output_dir