



"""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


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

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







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



						"""simple docstring"""
						__UpperCamelCase		    =							CamembertTokenizer
						__UpperCamelCase		    =							CamembertTokenizerFast
						__UpperCamelCase		    =							True
						__UpperCamelCase		    =							True






						def      UpperCAmelCase__					( self			:int )    ->      int:
												super().setUp()

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






						def      UpperCAmelCase__					( self			:List[Any] )    ->      Tuple:
												UpperCAmelCase					=			'<pad>'
												UpperCAmelCase					=			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			:Dict )    ->      str:
												UpperCAmelCase					=			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_ )       ,  10_04 )






						def      UpperCAmelCase__					( self			:Optional[Any] )    ->      Optional[int]:
												self.assertEqual(self.get_tokenizer().vocab_size       ,  10_05 )






						def      UpperCAmelCase__					( self			:Any )    ->      Tuple:
												UpperCAmelCase					=			CamembertTokenizer(lowercase_ )
												tokenizer.save_pretrained(self.tmpdirname )
												UpperCAmelCase					=			CamembertTokenizerFast.from_pretrained(self.tmpdirname )

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

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

												UpperCAmelCase					=			tokenizer.encode(lowercase_       ,  add_special_tokens=lowercase_ )
												UpperCAmelCase					=			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					=			tokenizer.convert_ids_to_tokens(lowercase_ )
												UpperCAmelCase					=			rust_tokenizer.tokenize(lowercase_ )
												self.assertListEqual(lowercase_       ,  lowercase_ )






						def      UpperCAmelCase__					( self			:int )    ->      Tuple:
												if not self.test_rust_tokenizer:
																		return

												UpperCAmelCase					=			self.get_tokenizer()
												UpperCAmelCase					=			self.get_rust_tokenizer()

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

												UpperCAmelCase					=			tokenizer.tokenize(lowercase_ )
												UpperCAmelCase					=			rust_tokenizer.tokenize(lowercase_ )
												self.assertListEqual(lowercase_       ,  lowercase_ )

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

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






						@slow
						def      UpperCAmelCase__					( self			:Dict )    ->      Tuple:
												# fmt: off
												UpperCAmelCase					=			{'input_ids': [[5, 54, 71_96, 2_97, 30, 23, 7_76, 18, 11, 32_15, 37_05, 82_52, 22, 31_64, 11_81, 21_16, 29, 16, 8_13, 25, 7_91, 33_14, 20, 34_46, 38, 2_75_75, 1_20, 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_68, 17, 11, 90_88, 20, 15_17, 8, 2_28_04, 1_88_18, 10, 38, 6_29, 6_07, 6_07, 1_42, 19, 71_96, 8_67, 56, 1_03_26, 24, 22_67, 20, 4_16, 50_72, 1_56_12, 2_33, 7_34, 7, 23_99, 27, 16, 30_15, 16_49, 7, 24, 20, 43_38, 23_99, 27, 13, 34_00, 14, 13, 61_89, 8, 9_30, 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					=			[
												    '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"""


def 			_lowerCAmelCase				(       lowercase_						):

						if not isinstance(lowercase_		,     lowercase_						):
												UpperCAmelCase					=			F"""Input value of [number={number}] must be an integer"""
												raise TypeError(lowercase_						)

						if number < 1:
												UpperCAmelCase					=			F"""Input value of [number={number}] must be > 0"""
												raise ValueError(lowercase_						)

						UpperCAmelCase					=			1

						for i in range(1		,     lowercase_						):
												current_number *= 4 * i - 2
												current_number //= i + 1

						return current_number


if __name__ == "__main__":
				import doctest

				doctest.testmod()





