





# 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 						UpperCamelCase__					( lowerCAmelCase_  ):



     '''simple docstring'''

     @classmethod
     def 							SCREAMING_SNAKE_CASE__    (				cls		:       Union[str, Any]			)	->						Optional[int]:




           '''simple docstring'''


           return cls






     @slow
     @require_torch_gpu
     def 							SCREAMING_SNAKE_CASE__    (				self		:       int			)	->						Any:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE						=		self.get_auto_remove_tmp_dir()
           SCREAMING_SNAKE_CASE						=		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
           SCREAMING_SNAKE_CASE						=		get_gpu_count()
           SCREAMING_SNAKE_CASE						=		F"""
            -m torch.distributed.launch
            --nproc_per_node={n_gpu}
            {self.test_file_dir}/run_distributed_eval.py
        """.split()
           SCREAMING_SNAKE_CASE						=		[sys.executable] + distributed_args + args
           execute_subprocess_async(lowerCamelCase__		,env=self.get_env()			)

           SCREAMING_SNAKE_CASE						=		os.path.join(lowerCamelCase__		,"""test_bleu.json"""			)
           SCREAMING_SNAKE_CASE						=		load_json(lowerCamelCase__			)
           # print(metrics)
           self.assertGreaterEqual(metrics["""bleu"""]		,25			)









import os



def   __lowercase  ( )					->  int:


      '''simple docstring'''


      SCREAMING_SNAKE_CASE						=		os.path.dirname(os.path.realpath(_SCREAMING_SNAKE_CASE      )      )
      SCREAMING_SNAKE_CASE						=		os.path.join(_SCREAMING_SNAKE_CASE					,		"""triangle.txt"""      )

      with open(_SCREAMING_SNAKE_CASE      ) as in_file:
            SCREAMING_SNAKE_CASE						=		[[int(_SCREAMING_SNAKE_CASE      ) for i in line.split()] for line in in_file]

      while len(_SCREAMING_SNAKE_CASE      ) != 1:
            SCREAMING_SNAKE_CASE						=		triangle.pop()
            SCREAMING_SNAKE_CASE						=		triangle[-1]
            for j in range(len(_SCREAMING_SNAKE_CASE      ) - 1      ):
                  curr_row[j] += max(last_row[j]					,		last_row[j + 1]      )
      return triangle[0][0]


if __name__ == "__main__":
      print(solution())


