






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


lowerCAmelCase_           = get_tests_dir('fixtures/test_sentencepiece.model')
lowerCAmelCase_           = get_tests_dir('fixtures/test_sentencepiece_bpe.model')

lowerCAmelCase_           = 'pt' if is_torch_available() else 'tf'
@require_sentencepiece
@require_tokenizers
class      UpperCamelCase (				snake_case__			,       unittest.TestCase ):







		"""simple docstring"""



		snake_case    =   CamembertTokenizer
		snake_case    =   CamembertTokenizerFast
		snake_case    =   True
		snake_case    =   True
		def       A(  self		:       List[str]		)    ->   Dict:


						'''simple docstring'''
						super().setUp()

						# We have a SentencePiece fixture for testing
						A	 =      CamembertTokenizer(_SCREAMING_SNAKE_CASE		)
						tokenizer.save_pretrained(self.tmpdirname		)
		def       A(  self		:       Optional[int]		)    ->   Optional[Any]:


						'''simple docstring'''
						A	 =      '<pad>'
						A	 =      1

						self.assertEqual(self.get_tokenizer()._convert_token_to_id(_SCREAMING_SNAKE_CASE		)						,_SCREAMING_SNAKE_CASE		)
						self.assertEqual(self.get_tokenizer()._convert_id_to_token(_SCREAMING_SNAKE_CASE		)						,_SCREAMING_SNAKE_CASE		)
		def       A(  self		:       List[str]		)    ->   Tuple:


						'''simple docstring'''
						A	 =      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(_SCREAMING_SNAKE_CASE		)						,1_0_0_4		)
		def       A(  self		:       Optional[Any]		)    ->   str:


						'''simple docstring'''
						self.assertEqual(self.get_tokenizer().vocab_size						,1_0_0_5		)
		def       A(  self		:       Optional[Any]		)    ->   List[Any]:


						'''simple docstring'''
						A	 =      CamembertTokenizer(_SCREAMING_SNAKE_CASE		)
						tokenizer.save_pretrained(self.tmpdirname		)
						A	 =      CamembertTokenizerFast.from_pretrained(self.tmpdirname		)

						A	 =      'I was born in 92000, and this is falsé.'

						A	 =      tokenizer.encode(_SCREAMING_SNAKE_CASE		)
						A	 =      rust_tokenizer.encode(_SCREAMING_SNAKE_CASE		)
						self.assertListEqual(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE		)

						A	 =      tokenizer.encode(_SCREAMING_SNAKE_CASE						,add_special_tokens=_SCREAMING_SNAKE_CASE		)
						A	 =      rust_tokenizer.encode(_SCREAMING_SNAKE_CASE						,add_special_tokens=_SCREAMING_SNAKE_CASE		)
						self.assertListEqual(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE		)

						# <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)
						A	 =      tokenizer.convert_ids_to_tokens(_SCREAMING_SNAKE_CASE		)
						A	 =      rust_tokenizer.tokenize(_SCREAMING_SNAKE_CASE		)
						self.assertListEqual(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE		)
		def       A(  self		:       Any		)    ->   Dict:


						'''simple docstring'''
						if not self.test_rust_tokenizer:
										return

						A	 =      self.get_tokenizer()
						A	 =      self.get_rust_tokenizer()

						A	 =      'I was born in 92000, and this is falsé.'

						A	 =      tokenizer.tokenize(_SCREAMING_SNAKE_CASE		)
						A	 =      rust_tokenizer.tokenize(_SCREAMING_SNAKE_CASE		)
						self.assertListEqual(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE		)

						A	 =      tokenizer.encode(_SCREAMING_SNAKE_CASE						,add_special_tokens=_SCREAMING_SNAKE_CASE		)
						A	 =      rust_tokenizer.encode(_SCREAMING_SNAKE_CASE						,add_special_tokens=_SCREAMING_SNAKE_CASE		)
						self.assertListEqual(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE		)

						A	 =      self.get_rust_tokenizer()
						A	 =      tokenizer.encode(_SCREAMING_SNAKE_CASE		)
						A	 =      rust_tokenizer.encode(_SCREAMING_SNAKE_CASE		)
						self.assertListEqual(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE		)







		@slow
		def       A(  self		:       str		)    ->   Tuple:


						'''simple docstring'''
						# fmt: off
						A	 =      {'input_ids': [[5, 5_4, 7_1_9_6, 2_9_7, 3_0, 2_3, 7_7_6, 1_8, 1_1, 3_2_1_5, 3_7_0_5, 8_2_5_2, 2_2, 3_1_6_4, 1_1_8_1, 2_1_1_6, 2_9, 1_6, 8_1_3, 2_5, 7_9_1, 3_3_1_4, 2_0, 3_4_4_6, 3_8, 2_7_5_7_5, 1_2_0, 6, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [5, 4_6_8, 1_7, 1_1, 9_0_8_8, 2_0, 1_5_1_7, 8, 2_2_8_0_4, 1_8_8_1_8, 1_0, 3_8, 6_2_9, 6_0_7, 6_0_7, 1_4_2, 1_9, 7_1_9_6, 8_6_7, 5_6, 1_0_3_2_6, 2_4, 2_2_6_7, 2_0, 4_1_6, 5_0_7_2, 1_5_6_1_2, 2_3_3, 7_3_4, 7, 2_3_9_9, 2_7, 1_6, 3_0_1_5, 1_6_4_9, 7, 2_4, 2_0, 4_3_3_8, 2_3_9_9, 2_7, 1_3, 3_4_0_0, 1_4, 1_3, 6_1_8_9, 8, 9_3_0, 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.
						A	 =      [
						    '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=_SCREAMING_SNAKE_CASE						,model_name='camembert-base'						,revision='3a0641d9a1aeb7e848a74299e7e4c4bca216b4cf'						,sequences=_SCREAMING_SNAKE_CASE						,)













def      snake_case		(							UpperCAmelCase	:       Optional[int],						UpperCAmelCase	:       Union[str, Any]   ):
				A	 =      ''
				for i in table:
								res += inp[i - 1]
				return res







def      snake_case		(							UpperCAmelCase	:       Union[str, Any]   ):
				return data[1:] + data[0]







def      snake_case		(							UpperCAmelCase	:       Union[str, Any],						UpperCAmelCase	:       Dict   ):
				A	 =      ''
				for i in range(len(UpperCAmelCase   )   ):
								if a[i] == b[i]:
												res += "0"
								else:
												res += "1"
				return res







def      snake_case		(							UpperCAmelCase	:       int,						UpperCAmelCase	:       Optional[Any]   ):
				A	 =      int('0b' + data[0] + data[-1],						2   )
				A	 =      int('0b' + data[1:3],						2   )
				return bin(s[row][col]   )[2:]







def      snake_case		(							UpperCAmelCase	:       Optional[Any],						UpperCAmelCase	:       Any,						UpperCAmelCase	:       Union[str, Any],						UpperCAmelCase	:       Optional[Any],						UpperCAmelCase	:       Optional[int]   ):
				A	 =      message[:4]
				A	 =      message[4:]
				A	 =      apply_table(UpperCAmelCase,						UpperCAmelCase   )
				A	 =      xor(UpperCAmelCase,						UpperCAmelCase   )
				A	 =      apply_sbox(UpperCAmelCase,						temp[:4]   )  # noqa: E741
				A	 =      apply_sbox(UpperCAmelCase,						temp[4:]   )
				A	 =      '0' * (2 - len(UpperCAmelCase   )) + l  # noqa: E741
				A	 =      '0' * (2 - len(UpperCAmelCase   )) + r
				A	 =      apply_table(l + r,						UpperCAmelCase   )
				A	 =      xor(UpperCAmelCase,						UpperCAmelCase   )
				return temp + right


if __name__ == "__main__":
					lowerCAmelCase_           = input('Enter 10 bit key: ')
					lowerCAmelCase_           = input('Enter 8 bit message: ')

					lowerCAmelCase_           = [6, 3, 7, 4, 8, 5, 10, 9]
					lowerCAmelCase_           = [3, 5, 2, 7, 4, 10, 1, 9, 8, 6]
					lowerCAmelCase_           = [2, 4, 3, 1]
					lowerCAmelCase_           = [2, 6, 3, 1, 4, 8, 5, 7]
					lowerCAmelCase_           = [4, 1, 3, 5, 7, 2, 8, 6]
					lowerCAmelCase_           = [4, 1, 2, 3, 2, 3, 4, 1]
					lowerCAmelCase_           = [[1, 0, 3, 2], [3, 2, 1, 0], [0, 2, 1, 3], [3, 1, 3, 2]]
					lowerCAmelCase_           = [[0, 1, 2, 3], [2, 0, 1, 3], [3, 0, 1, 0], [2, 1, 0, 3]]

					# key generation
					lowerCAmelCase_           = apply_table(key, paa_table)
					lowerCAmelCase_           = temp[:5]
					lowerCAmelCase_           = temp[5:]
					lowerCAmelCase_           = left_shift(left)
					lowerCAmelCase_           = left_shift(right)
					lowerCAmelCase_           = apply_table(left + right, pa_table)
					lowerCAmelCase_           = left_shift(left)
					lowerCAmelCase_           = left_shift(right)
					lowerCAmelCase_           = left_shift(left)
					lowerCAmelCase_           = left_shift(right)
					lowerCAmelCase_           = apply_table(left + right, pa_table)

					# encryption
					lowerCAmelCase_           = apply_table(message, IP)
					lowerCAmelCase_           = function(expansion, sa, sa, keya, temp)
					lowerCAmelCase_           = temp[4:] + temp[:4]
					lowerCAmelCase_           = function(expansion, sa, sa, keya, temp)
					lowerCAmelCase_           = apply_table(temp, IP_inv)
					print('Cipher text is:', CT)

					# decryption
					lowerCAmelCase_           = apply_table(CT, IP)
					lowerCAmelCase_           = function(expansion, sa, sa, keya, temp)
					lowerCAmelCase_           = temp[4:] + temp[:4]
					lowerCAmelCase_           = function(expansion, sa, sa, keya, temp)
					lowerCAmelCase_           = apply_table(temp, IP_inv)
					print('Plain text after decypting is:', PT)





