

'''simple docstring'''

import unittest

from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


lowercase__         =      get_tests_dir("fixtures/test_sentencepiece.model")
lowercase__         =      get_tests_dir("fixtures/test_sentencepiece_bpe.model")

lowercase__         =      "pt" if is_torch_available() else "tf"




@require_sentencepiece
@require_tokenizers
class 	A_			(    _snake_case	,       unittest.TestCase							):






     '''simple docstring'''



     UpperCAmelCase_						:     Dict  		=  CamembertTokenizer
     UpperCAmelCase_						:     Optional[Any]  		=  CamembertTokenizerFast
     UpperCAmelCase_						:     Union[str, Any]  		=  True
     UpperCAmelCase_						:     Union[str, Any]  		=  True


     def        UpperCAmelCase_	(		self			:					str	)						->     List[Any]:
      super().setUp()

      # We have a SentencePiece fixture for testing
      UpperCAmelCase	:     int						 =			CamembertTokenizer(lowercase_	)
      tokenizer.save_pretrained(self.tmpdirname	)


     def        UpperCAmelCase_	(		self			:					Optional[Any]	)						->     int:
      UpperCAmelCase	:     Dict						 =			'<pad>'
      UpperCAmelCase	:     int						 =			1

      self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowercase_	)					,      lowercase_	)
      self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowercase_	)					,      lowercase_	)


     def        UpperCAmelCase_	(		self			:					Optional[int]	)						->     Optional[int]:
      UpperCAmelCase	:     int						 =			list(self.get_tokenizer().get_vocab().keys()	)

      self.assertEqual(vocab_keys[0]					,      '<s>NOTUSED'	)
      self.assertEqual(vocab_keys[1]					,      '<pad>'	)
      self.assertEqual(vocab_keys[-1]					,      '<mask>'	)
      self.assertEqual(len(lowercase_	)					,      1_004	)


     def        UpperCAmelCase_	(		self			:					Union[str, Any]	)						->     List[Any]:
      self.assertEqual(self.get_tokenizer().vocab_size					,      1_005	)


     def        UpperCAmelCase_	(		self			:					Tuple	)						->     List[str]:
      UpperCAmelCase	:     Any						 =			CamembertTokenizer(lowercase_	)
      tokenizer.save_pretrained(self.tmpdirname	)
      UpperCAmelCase	:     Dict						 =			CamembertTokenizerFast.from_pretrained(self.tmpdirname	)

      UpperCAmelCase	:     Any						 =			'I was born in 92000, and this is falsé.'

      UpperCAmelCase	:     Dict						 =			tokenizer.encode(lowercase_	)
      UpperCAmelCase	:     Dict						 =			rust_tokenizer.encode(lowercase_	)
      self.assertListEqual(lowercase_					,      lowercase_	)

      UpperCAmelCase	:     List[str]						 =			tokenizer.encode(lowercase_					,      add_special_tokens=lowercase_	)
      UpperCAmelCase	:     str						 =			rust_tokenizer.encode(lowercase_					,      add_special_tokens=lowercase_	)
      self.assertListEqual(lowercase_					,      lowercase_	)

      # <unk> tokens are not the same for `rust` than for `slow`.
      # Because spm gives back raw token instead of `unk` in EncodeAsPieces
      # tokens = tokenizer.tokenize(sequence)
      UpperCAmelCase	:     List[Any]						 =			tokenizer.convert_ids_to_tokens(lowercase_	)
      UpperCAmelCase	:     Dict						 =			rust_tokenizer.tokenize(lowercase_	)
      self.assertListEqual(lowercase_					,      lowercase_	)


     def        UpperCAmelCase_	(		self			:					int	)						->     Optional[int]:
      if not self.test_rust_tokenizer:
       return

      UpperCAmelCase	:     str						 =			self.get_tokenizer()
      UpperCAmelCase	:     List[str]						 =			self.get_rust_tokenizer()

      UpperCAmelCase	:     str						 =			'I was born in 92000, and this is falsé.'

      UpperCAmelCase	:     List[str]						 =			tokenizer.tokenize(lowercase_	)
      UpperCAmelCase	:     Dict						 =			rust_tokenizer.tokenize(lowercase_	)
      self.assertListEqual(lowercase_					,      lowercase_	)

      UpperCAmelCase	:     Union[str, Any]						 =			tokenizer.encode(lowercase_					,      add_special_tokens=lowercase_	)
      UpperCAmelCase	:     Optional[int]						 =			rust_tokenizer.encode(lowercase_					,      add_special_tokens=lowercase_	)
      self.assertListEqual(lowercase_					,      lowercase_	)

      UpperCAmelCase	:     Union[str, Any]						 =			self.get_rust_tokenizer()
      UpperCAmelCase	:     List[str]						 =			tokenizer.encode(lowercase_	)
      UpperCAmelCase	:     Dict						 =			rust_tokenizer.encode(lowercase_	)
      self.assertListEqual(lowercase_					,      lowercase_	)




     @slow
     def        UpperCAmelCase_	(		self			:					Optional[int]	)						->     int:
      # fmt: off
      UpperCAmelCase	:     Dict						 =			{'input_ids': [[5, 54, 7_196, 297, 30, 23, 776, 18, 11, 3_215, 3_705, 8_252, 22, 3_164, 1_181, 2_116, 29, 16, 813, 25, 791, 3_314, 20, 3_446, 38, 27_575, 120, 6, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [5, 468, 17, 11, 9_088, 20, 1_517, 8, 22_804, 18_818, 10, 38, 629, 607, 607, 142, 19, 7_196, 867, 56, 10_326, 24, 2_267, 20, 416, 5_072, 15_612, 233, 734, 7, 2_399, 27, 16, 3_015, 1_649, 7, 24, 20, 4_338, 2_399, 27, 13, 3_400, 14, 13, 6_189, 8, 930, 9, 6]], 'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
      # fmt: on

      # camembert is a french model. So we also use french texts.
      UpperCAmelCase	:     Dict						 =			[
          'Le transformeur est un modèle d\'apprentissage profond introduit en 2017, '
          'utilisé principalement dans le domaine du traitement automatique des langues (TAL).',
          'À l\'instar des réseaux de neurones récurrents (RNN), les transformeurs sont conçus '
          'pour gérer des données séquentielles, telles que le langage naturel, pour des tâches '
          'telles que la traduction et la synthèse de texte.',
      ]

      self.tokenizer_integration_test_util(
          expected_encoding=lowercase_					,      model_name='camembert-base'					,      revision='3a0641d9a1aeb7e848a74299e7e4c4bca216b4cf'					,      sequences=lowercase_					,      )







'''simple docstring'''

import os
import random
import sys

from . import cryptomath_module as cryptomath
from . import rabin_miller

lowercase__         =      3




def 				UpperCamelCase(					UpperCAmelCase_     ):
 print('Generating primitive root of p'     )
 while True:
  UpperCAmelCase	:     Union[str, Any]						 =			random.randrange(3  ,	UpperCAmelCase_     )
  if pow(UpperCAmelCase_  ,	2  ,	UpperCAmelCase_     ) == 1:
   continue
  if pow(UpperCAmelCase_  ,	UpperCAmelCase_  ,	UpperCAmelCase_     ) == 1:
   continue
  return g




def 				UpperCamelCase(					UpperCAmelCase_     ):
 print('Generating prime p...'     )
 UpperCAmelCase	:     str						 =			rabin_miller.generate_large_prime(UpperCAmelCase_     )  # select large prime number.
 UpperCAmelCase	:     List[str]						 =			primitive_root(UpperCAmelCase_     )  # one primitive root on modulo p.
 UpperCAmelCase	:     List[Any]						 =			random.randrange(3  ,	UpperCAmelCase_     )  # private_key -> have to be greater than 2 for safety.
 UpperCAmelCase	:     List[Any]						 =			cryptomath.find_mod_inverse(pow(UpperCAmelCase_  ,	UpperCAmelCase_  ,	UpperCAmelCase_     )  ,	UpperCAmelCase_     )

 UpperCAmelCase	:     Tuple						 =			(key_size, e_a, e_a, p)
 UpperCAmelCase	:     Optional[int]						 =			(key_size, d)

 return public_key, private_key




def 				UpperCamelCase(					UpperCAmelCase_  ,	UpperCAmelCase_     ):
 if os.path.exists(F"""{name}_pubkey.txt"""     ) or os.path.exists(F"""{name}_privkey.txt"""     ):
  print('\nWARNING:'     )
  print(
      F"""\"{name}_pubkey.txt\" or \"{name}_privkey.txt\" already exists. \n"""
      'Use a different name or delete these files and re-run this program.'     )
  sys.exit()

 UpperCAmelCase ,			UpperCAmelCase	:     Dict						 =			generate_key(UpperCAmelCase_     )
 print(F"""\nWriting public key to file {name}_pubkey.txt..."""     )
 with open(F"""{name}_pubkey.txt"""  ,	'w'     ) as fo:
  fo.write(F"""{public_key[0]},{public_key[1]},{public_key[2]},{public_key[3]}"""     )

 print(F"""Writing private key to file {name}_privkey.txt..."""     )
 with open(F"""{name}_privkey.txt"""  ,	'w'     ) as fo:
  fo.write(F"""{private_key[0]},{private_key[1]}"""     )




def 				UpperCamelCase(					):
 print('Making key files...'     )
 make_key_files('elgamal'  ,	20_48     )
 print('Key files generation successful'     )


if __name__ == "__main__":
 main()




