






from __future__ import annotations

SCREAMING_SNAKE_CASE__		:							List[str] 				=				8.988e9  # units = N * m^s * C^-2





def  _lowerCamelCase						(						__lowerCamelCase ,							__lowerCamelCase ,							__lowerCamelCase ,							__lowerCamelCase       ) ->			dict[str, float]:

     '''simple docstring'''
     UpperCAmelCase__      :  int				      =			abs(chargea * chargea       )

     if (force, chargea, chargea, distance).count(0       ) != 1:
          raise ValueError("""One and only one argument must be 0"""       )
     if distance < 0:
          raise ValueError("""Distance cannot be negative"""       )
     if force == 0:
          UpperCAmelCase__      :  int				      =			COULOMBS_CONSTANT * charge_product / (distance**2)
          return {"force": force}
     elif chargea == 0:
          UpperCAmelCase__      :  str				      =			abs(__lowerCamelCase       ) * (distance**2) / (COULOMBS_CONSTANT * chargea)
          return {"charge1": chargea}
     elif chargea == 0:
          UpperCAmelCase__      :  Union[str, Any]				      =			abs(__lowerCamelCase       ) * (distance**2) / (COULOMBS_CONSTANT * chargea)
          return {"charge2": chargea}
     elif distance == 0:
          UpperCAmelCase__      :  Optional[Any]				      =			(COULOMBS_CONSTANT * charge_product / abs(__lowerCamelCase       )) ** 0.5
          return {"distance": distance}
     raise ValueError("""Exactly one argument must be 0"""       )


if __name__ == "__main__":
      import doctest

      doctest.testmod()












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__		     =     logging.getLogger()





def 				A__ (snake_case   :		Tuple				)     ->						Dict:
					__UpperCamelCase					:	Dict             =      {}
					__UpperCamelCase					:	Dict             =      os.path.join(snake_case		,	"""all_results.json"""				)
					if os.path.exists(snake_case				):
										with open(snake_case		,	"""r"""				) as f:
															__UpperCamelCase					:	List[Any]             =      json.load(snake_case				)
					else:
										raise ValueError(F'''can\'t find {path}'''				)
					return results


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







@require_torch_tpu
class    SCREAMING_SNAKE_CASE_				(       _UpperCamelCase   ):



	"""simple docstring"""


	def 					lowerCamelCase__     (					self		:						Dict	)	->       Dict:







						"""simple docstring"""







						import xla_spawn

						__UpperCamelCase					:	Dict             =      self.get_auto_remove_tmp_dir()
						__UpperCamelCase					:	str             =      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(lowerCAmelCase					,     """argv"""					,     lowerCAmelCase	):
											__UpperCamelCase					:	Union[str, Any]             =      time()
											xla_spawn.main()
											__UpperCamelCase					:	List[str]             =      time()

											__UpperCamelCase					:	Optional[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					,     500	)






	def 					lowerCamelCase__     (					self		:						int	)	->       List[Any]:







						"""simple docstring"""







						import xla_spawn

						__UpperCamelCase					:	List[Any]             =      """
            ./tests/test_trainer_tpu.py
            --num_cores=8
            ./tests/test_trainer_tpu.py
            """.split()
						with patch.object(lowerCAmelCase					,     """argv"""					,     lowerCAmelCase	):
											xla_spawn.main()






