class_docstr: This class is for testing via an external script - can do multiple gpus
class_docstr_tok: ["This","class","is","for","testing","via","an","external","script","-","can","do","multiple","gpus"]
code: def run_trainer(
      self,
      stage: str,
      dtype: str,
      model_name: str,
      eval_steps: int = 10,
      num_train_epochs: int = 1,
      do_train: bool = False,
      do_eval: bool = True,
      distributed: bool = True,
      fp32: bool = False,
      extra_args_str: str = None,
      remove_args_str: str = None,
  ):
      max_len = 32
      data_dir = (
          self.test_file_dir / "../fixtures/tests_samples/wmt_en_ro"
      )
      output_dir = self.get_auto_remove_tmp_dir()
      args = f"""
              --model_name_or_path {model_name}
              --train_file {data_dir}/train.json
              --validation_file {data_dir}/val.json
              --output_dir {output_dir}
              --overwrite_output_dir
              --max_source_length {max_len}
              --max_target_length {max_len}
              --val_max_target_length {max_len}
              --warmup_steps 8
              --predict_with_generate
              --save_steps 0
              --eval_steps {eval_steps}
              --group_by_length
              --label_smoothing_factor 0.1
              --source_lang en
              --target_lang ro
              --report_to none
          """.split()
      args.extend(
          ["--source_prefix", '"translate English to Romanian: "']
      )
  
      if not fp32:
          args.extend([f"--{dtype}"])
  
      actions = 0
      if do_train:
          actions += 1
          args.extend(
              f"""
              --do_train
              --num_train_epochs {str(num_train_epochs)}
              --max_train_samples 16
              --per_device_train_batch_size 2
              --learning_rate 3e-3
              """.split()
          )
  
      if do_eval:
          actions += 1
          args.extend(
              """
              --do_eval
              --max_eval_samples 16
              --per_device_eval_batch_size 2
              """.split()
          )
  
      assert (
          actions > 0
      ), "need at least do_train or do_eval for the test to run"
  
      if extra_args_str is not None:
          args.extend(extra_args_str.split())
  
      # currently only works for bool args
      if remove_args_str is not None:
          remove_args = remove_args_str.split()
          args = [x for x in args if x not in remove_args]
  
      ds_args = f"--deepspeed {self.test_file_dir_str}/ds_config_{stage}.json".split()
      script = [
          f"{self.examples_dir_str}/pytorch/translation/run_translation.py"
      ]
      launcher = 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 dataclasses
  import io
  import itertools
  import json
  import os
  import unittest
  from copy import deepcopy
  import datasets
  from parameterized import parameterized
  from tests.trainer.test_trainer import TrainerIntegrationCommon
  from transformers import AutoModel, TrainingArguments, is_torch_available, logging
  from transformers.deepspeed import HfDeepSpeedConfig, is_deepspeed_available, unset_hf_deepspeed_config
  from transformers.testing_utils import CaptureLogger, CaptureStd, CaptureStderr, LoggingLevel, TestCasePlus, execute_subprocess_async, get_gpu_count, mockenv_context, require_deepspeed, require_optuna, require_torch_gpu, require_torch_multi_gpu, slow
  from transformers.trainer_utils import get_last_checkpoint, set_seed
  from transformers.utils import WEIGHTS_NAME, is_torch_bf16_gpu_available
label_desc: Use image node_id 9 for calling the TestDeepSpeedWithLauncher obj's underlying member method code with example usage: obj.run_trainer(stage, dtype, model_name, eval_steps, num_train_epochs, do_train, do_eval, distributed, fp32, extra_args_str, remove_args_str) and returns: output_dir