"""simple docstring"""
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)

lowercase__					       =	logging.getLogger()







def 						__a   (	_SCREAMING_SNAKE_CASE   )	->Any:
  a__:     Union[str, Any]										=	{}
  a__:     List[str]										=	os.path.join(_SCREAMING_SNAKE_CASE		,     'all_results.json'   )
  if os.path.exists(_SCREAMING_SNAKE_CASE   ):
    with open(_SCREAMING_SNAKE_CASE		,     'r'   ) as f:
      a__:     List[Any]										=	json.load(_SCREAMING_SNAKE_CASE   )
  else:
    raise ValueError(F'can\'t find {path}'   )
  return results


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




@require_torch_tpu
class    __snake_case       (     __lowerCAmelCase				):



      def   lowerCamelCase_   (						self)	->			Dict:





        '''simple docstring'''





        import xla_spawn

        a__:     Optional[Any]										=	self.get_auto_remove_tmp_dir()
        a__:     Optional[Any]										=	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(lowercase    ,			'argv'    ,			lowercase):
          a__:     Any										=	time()
          xla_spawn.main()
          a__:     Union[str, Any]										=	time()

          a__:     Tuple										=	get_results(lowercase)
          self.assertGreaterEqual(result['eval_accuracy']    ,			0.75)

          # Assert that the script takes less than 500 seconds to make sure it doesn't hang.
          self.assertLess(end - start    ,			5_00)



      def   lowerCamelCase_   (						self)	->			List[str]:





        '''simple docstring'''





        import xla_spawn

        a__:     Tuple										=	'\n            ./tests/test_trainer_tpu.py\n            --num_cores=8\n            ./tests/test_trainer_tpu.py\n            '.split()
        with patch.object(lowercase    ,			'argv'    ,			lowercase):
          xla_spawn.main()



"""simple docstring"""
def 						__a   (	_SCREAMING_SNAKE_CASE		,     _SCREAMING_SNAKE_CASE = False   )	->str:

  if not isinstance(_SCREAMING_SNAKE_CASE		,     _SCREAMING_SNAKE_CASE   ):
    a__:     Optional[int]										=	F'Expected string as input, found {type(_SCREAMING_SNAKE_CASE   )}'
    raise ValueError(_SCREAMING_SNAKE_CASE   )
  if not isinstance(_SCREAMING_SNAKE_CASE		,     _SCREAMING_SNAKE_CASE   ):
    a__:     List[str]										=	F'Expected boolean as use_pascal parameter, found {type(_SCREAMING_SNAKE_CASE   )}'
    raise ValueError(_SCREAMING_SNAKE_CASE   )

  a__:     int										=	input_str.split('_'   )

  a__:     List[str]										=	0 if use_pascal else 1

  a__:     List[str]										=	words[start_index:]

  a__:     List[str]										=	[word[0].upper() + word[1:] for word in words_to_capitalize]

  a__:     List[str]										=	'' if use_pascal else words[0]

  return "".join([initial_word, *capitalized_words]   )


if __name__ == "__main__":
 from doctest import testmod

 testmod()


