


import json
import logging
import os
import sys
from time import time
from unittest.mock import patch

from transformers.testing_utils import TestCasePlus, require_torch_tpu


logging.basicConfig(level=logging.DEBUG)

__lowerCAmelCase		       =							logging.getLogger()




def    snake_case_     (  snake_case     )  ->				List[str]:
       lowercase__:   int  			=   {}
       lowercase__:   int  			=   os.path.join(snake_case			,							'all_results.json'     )
       if os.path.exists(snake_case     ):
              with open(snake_case			,							'r'     ) as f:
                     lowercase__:   Tuple  			=   json.load(snake_case     )
       else:
              raise ValueError(f'can\'t find {path}'     )
       return results


__lowerCAmelCase		       =							logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)





@require_torch_tpu
class   __a			(    __UpperCamelCase      ):
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				Union[str, Any]:




        '''simple docstring'''
        import xla_spawn

        lowercase__:   Any  			=   self.get_auto_remove_tmp_dir()
        lowercase__:   Dict  			=   F'\n            ./examples/pytorch/text-classification/run_glue.py\n            --num_cores=8\n            ./examples/pytorch/text-classification/run_glue.py\n            --model_name_or_path distilbert-base-uncased\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --train_file ./tests/fixtures/tests_samples/MRPC/train.csv\n            --validation_file ./tests/fixtures/tests_samples/MRPC/dev.csv\n            --do_train\n            --do_eval\n            --debug tpu_metrics_debug\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=1\n            --learning_rate=1e-4\n            --max_steps=10\n            --warmup_steps=2\n            --seed=42\n            --max_seq_length=128\n            '.split()

        with patch.object(lowerCAmelCase__				, 'argv'				, lowerCAmelCase__ ):
               lowercase__:   Union[str, Any]  			=   time()
               xla_spawn.main()
               lowercase__:   Dict  			=   time()

               lowercase__:   str  			=   get_results(lowerCAmelCase__ )
               self.assertGreaterEqual(result['eval_accuracy']				, 0.7_5 )

               # Assert that the script takes less than 500 seconds to make sure it doesn't hang.
               self.assertLess(end - start				, 500 )
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				str:




        '''simple docstring'''
        import xla_spawn

        lowercase__:   Optional[Any]  			=   '\n            ./tests/test_trainer_tpu.py\n            --num_cores=8\n            ./tests/test_trainer_tpu.py\n            '.split()
        with patch.object(lowerCAmelCase__				, 'argv'				, lowerCAmelCase__ ):
               xla_spawn.main()






from __future__ import annotations




def    snake_case_     (  snake_case			,							snake_case     )  ->				list[int]:
       lowercase__:   List[str]  			=   0
       lowercase__:   Dict  			=   len(snake_case     ) - 1

       while i < j:
              if nums[i] + nums[j] == target:
                     return [i, j]
              elif nums[i] + nums[j] < target:
                     lowercase__:   Dict  			=   i + 1
              else:
                     lowercase__:   List[Any]  			=   j - 1

       return []


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 print(F'''{two_pointer([2, 7, 11, 15], 9) = }''')


