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 					snake_case__  ( __A       ):
  
  
  
  
  
  	@classmethod
  	def     A				(  cls							)		->			str:
  								"""simple docstring"""
  
  
  
  
  
  
  								return cls
  
  
  
  
  
  	@slow
  	@require_torch_gpu
  	def     A				(  self							)		->			Dict:
  								"""simple docstring"""
  
  
  
  
  
  
  								a_       :   Any			=	self.get_auto_remove_tmp_dir()
  								a_       :   Tuple			=	f"""
              --model_name Helsinki-NLP/opus-mt-en-ro
              --save_dir {output_dir}
              --data_dir {self.test_file_dir_str}/test_data/wmt_en_ro
              --num_beams 2
              --task translation
          """.split()
  
  								# we want this test to run even if there is only one GPU, but if there are more we use them all
  								a_       :   int			=	get_gpu_count()
  								a_       :   Optional[Any]			=	f"""
              -m torch.distributed.launch
              --nproc_per_node={n_gpu}
              {self.test_file_dir}/run_distributed_eval.py
          """.split()
  								a_       :   int			=	[sys.executable] + distributed_args + args
  								execute_subprocess_async(UpperCamelCase_				,    env=self.get_env()							)
  
  								a_       :   Union[str, Any]			=	os.path.join(UpperCamelCase_				,    """test_bleu.json"""							)
  								a_       :   Any			=	load_json(UpperCamelCase_							)
  								# print(metrics)
  								self.assertGreaterEqual(metrics["""bleu"""]				,    25							)
  
  
  
style_context: 
  
  
  from __future__ import annotations
  
  
  
  
  
  def 						_lowerCamelCase		(							SCREAMING_SNAKE_CASE_				: list      ):
  
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  							a_       :   Tuple			=	sorted(SCREAMING_SNAKE_CASE_      )
  							a_       :   Tuple			=	len(SCREAMING_SNAKE_CASE_      )
  							a_       :   Tuple			=	length >> 1
  							return (
  							    (sorted_list[mid_index] + sorted_list[mid_index - 1]) / 2
  							    if length % 2 == 0
  							    else sorted_list[mid_index]
  							)
  
  
  
  
  
  def 						_lowerCamelCase		(							):
  
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  							import doctest
  
  							doctest.testmod()
  
  
  if __name__ == "__main__":
  	main()
  
  
  