
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			:     Tuple           =   logging.getLogger()

def a__    (       A_					):






  '''simple docstring'''





  __magic_name__				     =       {}
  __magic_name__				     =       os.path.join(A_,     """all_results.json"""					)
  if os.path.exists(A_					):
    with open(A_,     """r"""					) as f:
      __magic_name__				     =       json.load(A_					)
  else:
    raise ValueError(f'''can\'t find {path}'''					)
  return results


__lowerCAmelCase			:     List[str]           =   logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)





@require_torch_tpu
class        UpperCAmelCase_			( _A     ):


  '''simple docstring'''







  def 							_lowercase							( self			: Any    )			->	int:







    """simple docstring"""






    import xla_spawn

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

    with patch.object(UpperCamelCase__			,							"""argv"""			,							UpperCamelCase__    ):
      __magic_name__				     =       time()
      xla_spawn.main()
      __magic_name__				     =       time()

      __magic_name__				     =       get_results(UpperCamelCase__    )
      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			,							500    )





  def 							_lowercase							( self			: List[Any]    )			->	Union[str, Any]:







    """simple docstring"""






    import xla_spawn

    __magic_name__				     =       """
            ./tests/test_trainer_tpu.py
            --num_cores=8
            ./tests/test_trainer_tpu.py
            """.split()
    with patch.object(UpperCamelCase__			,							"""argv"""			,							UpperCamelCase__    ):
      xla_spawn.main()








def    __lowerCamelCase					(							__a   :int = 1_0_0_0_0_0_0    )		->				int:






		"""simple docstring"""

		A__        =   limit + 1
		A__        =   [0] * limit
		for first_term in range(1    ,     __a    ):
				for n in range(__a    ,     __a    ,     __a    ):
						A__        =   first_term + n / first_term
						if common_difference % 4:  # d must be divisble by 4
								continue
						else:
								common_difference /= 4
								if (
								    first_term > common_difference
								    and first_term < 4 * common_difference
								):  # since x,y,z are positive integers
										frequency[n] += 1  # so z>0 and a>d ,also 4d<a

		A__        =   sum(1 for x in frequency[1:limit] if x == 1_0    )

		return count


if __name__ == "__main__":
					print(F'''{solution() = }''')



