
'''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)

A__   :		List[Any] 		=logging.getLogger()







def        A_     (						__SCREAMING_SNAKE_CASE						:  Dict )				->       Union[str, Any]:





  """simple docstring"""

  __A		:     Optional[int]												=		{}
  __A		:     Optional[Any]												=		os.path.join(_A			,     """all_results.json""" )
  if os.path.exists(_A ):
    with open(_A			,     """r""" ) as f:
      __A		:     Optional[Any]												=		json.load(_A )
  else:
    raise ValueError(F"can't find {path}" )
  return results


A__   :		Tuple 		=logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)







@require_torch_tpu
class  __A				( lowercase__			):
 def 		lowercase_(   self			:    int       ):



   """simple docstring"""





   import xla_spawn

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

     __A		:     int												=		get_results(__lowerCamelCase       )
     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 		lowercase_(   self			:    str       ):



   """simple docstring"""





   import xla_spawn

   __A		:     List[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()





'''simple docstring'''
def        A_     (						__SCREAMING_SNAKE_CASE						:  list			,     __SCREAMING_SNAKE_CASE						:  list			,     __SCREAMING_SNAKE_CASE						:  int			,     __SCREAMING_SNAKE_CASE						:  int			,     __SCREAMING_SNAKE_CASE						:  int )				->       int:





  """simple docstring"""

  if index == number_of_items:
    return 0
  __A		:     List[Any]												=		0
  __A		:     Union[str, Any]												=		0
  __A		:     List[Any]												=		knapsack(__SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE			,     index + 1 )
  if weights[index] <= max_weight:
    __A		:     Tuple												=		values[index] + knapsack(
        __SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE			,     max_weight - weights[index]			,     index + 1 )
  return max(__SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE )


if __name__ == "__main__":
     import doctest

     doctest.testmod()



