


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					)  ->    str:
       lowercase__:       Dict        =       {}
       lowercase__:       Tuple        =       os.path.join(snake_case      ,							'all_results.json'					)
       if os.path.exists(snake_case					):
              with open(snake_case      ,							'r'					) as f:
                     lowercase__:       Optional[Any]        =       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			) ->    List[str]:




        '''simple docstring'''
        import xla_spawn

        lowercase__:       str        =       self.get_auto_remove_tmp_dir()
        lowercase__:       Optional[int]        =       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__:       Any        =       time()
               xla_spawn.main()
               lowercase__:       List[Any]        =       time()

               lowercase__:       Dict        =       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			) ->    Union[str, Any]:




        '''simple docstring'''
        import xla_spawn

        lowercase__:       int        =       '\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__:       Tuple        =       0
       lowercase__:       str        =       len(snake_case					) - 1

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

       return []


if __name__ == "__main__":
 import doctest

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


