code: 
  
  
  
  
  
  
  # as due to their complexity multi-gpu tests could impact other tests, and to aid debug we have those in a separate module.
  
  import os
  import sys
  
  from transformers.testing_utils import TestCasePlus, execute_subprocess_async, get_gpu_count, require_torch_gpu, slow
  
  from .utils import load_json
  
  
  
  
  
  class     __a						(					A__ ):
  
  
  
  
  
  
  
   @classmethod
   def       __lowercase      (	cls      :     List[Any]		):
  
  
        '''simple docstring'''
  
  
  
  
  
  
        return cls
  
  
  
  
  
  
  
   @slow
   @require_torch_gpu
   def       __lowercase      (	self      :     Dict		):
  
  
        '''simple docstring'''
  
  
  
  
  
  
        UpperCamelCase__    :     Optional[Any]        =						self.get_auto_remove_tmp_dir()
        UpperCamelCase__    :     Tuple        =						F'\n            --model_name Helsinki-NLP/opus-mt-en-ro\n            --save_dir {output_dir}\n            --data_dir {self.test_file_dir_str}/test_data/wmt_en_ro\n            --num_beams 2\n            --task translation\n        '.split()
  
        # we want this test to run even if there is only one GPU, but if there are more we use them all
        UpperCamelCase__    :     str        =						get_gpu_count()
        UpperCamelCase__    :     Optional[int]        =						F'\n            -m torch.distributed.launch\n            --nproc_per_node={n_gpu}\n            {self.test_file_dir}/run_distributed_eval.py\n        '.split()
        UpperCamelCase__    :     Optional[int]        =						[sys.executable] + distributed_args + args
        execute_subprocess_async(SCREAMING_SNAKE_CASE							,     env=self.get_env()		)
  
        UpperCamelCase__    :     Optional[int]        =						os.path.join(SCREAMING_SNAKE_CASE							,     "test_bleu.json"		)
        UpperCamelCase__    :     Tuple        =						load_json(SCREAMING_SNAKE_CASE		)
        # print(metrics)
        self.assertGreaterEqual(metrics["bleu"]							,     25		)
style_context: 
  
  
  
  
  
  
  def 	SCREAMING_SNAKE_CASE							(      __lowerCAmelCase    )				->			str:
       return "".join(chr(ord(__lowerCAmelCase    ) + 32    ) if "A" <= char <= "Z" else char for char in word    )
  
  
  if __name__ == "__main__":
   from doctest import testmod
  
   testmod()