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_and_check(
      self,
      stage,
      dtype,
      model_name: str = T5_SMALL,
      eval_steps: int = 10,
      distributed: bool = True,
      do_train: bool = True,
      do_eval: bool = True,
      quality_checks: bool = True,
      fp32: bool = False,
      extra_args_str: str = None,
      remove_args_str: str = None,
  ):
      # we are doing quality testing so using a small real model
      output_dir = self.run_trainer(
          stage=stage,
          dtype=dtype,
          model_name=model_name,
          eval_steps=eval_steps,
          num_train_epochs=1,
          do_train=do_train,
          do_eval=do_eval,
          distributed=distributed,
          fp32=fp32,
          extra_args_str=extra_args_str,
          remove_args_str=remove_args_str,
      )
  
      self.do_checks(
          output_dir,
          do_train=do_train,
          do_eval=do_eval,
          quality_checks=quality_checks,
      )
  
      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 8 for calling the TestDeepSpeedWithLauncher obj's underlying member method code with example usage: obj.run_and_check(stage, dtype, model_name, eval_steps, distributed, do_train, do_eval, quality_checks, fp32, extra_args_str, remove_args_str) and returns: output_dir