


'''simple docstring'''




# 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__ ):
							"""simple docstring"""





							@classmethod
							def 		__SCREAMING_SNAKE_CASE( cls						)  ->Tuple:



											"""simple docstring"""







											return cls







							@slow
							@require_torch_gpu
							def 		__SCREAMING_SNAKE_CASE( self						)  ->Any:



											"""simple docstring"""







											__lowerCamelCase		:   List[Any]           =       self.get_auto_remove_tmp_dir()
											__lowerCamelCase		:   Union[str, Any]           =       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
											__lowerCamelCase		:   Optional[Any]           =       get_gpu_count()
											__lowerCamelCase		:   Dict           =       f'\n            -m torch.distributed.launch\n            --nproc_per_node={n_gpu}\n            {self.test_file_dir}/run_distributed_eval.py\n        '.split()
											__lowerCamelCase		:   List[Any]           =       [sys.executable] + distributed_args + args
											execute_subprocess_async(__A      ,					env=self.get_env()						)

											__lowerCamelCase		:   Optional[Any]           =       os.path.join(__A      ,					"test_bleu.json"						)
											__lowerCamelCase		:   int           =       load_json(__A						)
											# print(metrics)
											self.assertGreaterEqual(metrics["bleu"]      ,					25						)









'''simple docstring'''




import os





def 				a_							(    )      ->int:






				'''simple docstring'''

				__lowerCamelCase		:   Dict           =       os.path.dirname(os.path.realpath(lowercase     )     )
				__lowerCamelCase		:   Any           =       os.path.join(lowercase				,    "triangle.txt"     )

				with open(lowercase     ) as in_file:
								__lowerCamelCase		:   List[str]           =       [[int(lowercase     ) for i in line.split()] for line in in_file]

				while len(lowercase     ) != 1:
								__lowerCamelCase		:   List[str]           =       triangle.pop()
								__lowerCamelCase		:   Union[str, Any]           =       triangle[-1]
								for j in range(len(lowercase     ) - 1     ):
												curr_row[j] += max(last_row[j]				,    last_row[j + 1]     )
				return triangle[0][0]


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





