"""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)

lowerCAmelCase__						:						Tuple		  =			logging.getLogger()



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


lowerCAmelCase__						:						Any		  =			logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)







@require_torch_tpu
class        snake_case (				__UpperCAmelCase       ):




					"""simple docstring"""

					def 	__lowerCAmelCase		(       self     :			List[str]    ):
									import xla_spawn

									UpperCAmelCase__    =							self.get_auto_remove_tmp_dir()
									UpperCAmelCase__    =							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__    =							time()
													xla_spawn.main()
													UpperCAmelCase__    =							time()

													UpperCAmelCase__    =							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 	__lowerCAmelCase		(       self     :			str    ):
									import xla_spawn

									UpperCAmelCase__    =							'\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"""






import random
class        snake_case :




					"""simple docstring"""

					@staticmethod
					def 	__lowerCAmelCase		(       lowerCamelCase__     :			str    ):
									UpperCAmelCase__    =							[ord(lowerCamelCase__    ) for i in text]
									UpperCAmelCase__    =							[]
									UpperCAmelCase__    =							[]
									for i in plain:
													UpperCAmelCase__    =							random.randint(1					,300    )
													UpperCAmelCase__    =							(i + k) * k
													cipher.append(lowerCamelCase__    )
													key.append(lowerCamelCase__    )
									return cipher, key







					@staticmethod
					def 	__lowerCAmelCase		(       lowerCamelCase__     :			list[int]					,lowerCamelCase__     :			list[int]    ):
									UpperCAmelCase__    =							[]
									for i in range(len(lowerCamelCase__    )    ):
													UpperCAmelCase__    =							int((cipher[i] - (key[i]) ** 2) / key[i]    )
													plain.append(chr(lowerCamelCase__    )    )
									return "".join(lowerCamelCase__    )


if __name__ == "__main__":
						lowerCAmelCase__  ,			lowerCAmelCase__						:						Dict		  =			Onepad().encrypt('Hello')
						print(c, k)
						print(Onepad().decrypt(c, k))



