



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    SCREAMING_SNAKE_CASE			(							lowerCamelCase__			,      unittest.TestCase					):
							__lowerCamelCase	:	Optional[Any]    =CamembertTokenizer
							__lowerCamelCase	:	Tuple    =CamembertTokenizerFast
							__lowerCamelCase	:	List[str]    =True
							__lowerCamelCase	:	int    =True





							def 						UpperCamelCase_					(   self		:		Union[str, Any]	):

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

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





							def 						UpperCamelCase_					(   self		:		Optional[int]	):

											'''simple docstring'''
											__a       =		"""<pad>"""
											__a       =		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	):

											'''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(__lowercase	)      ,				1004	)





							def 						UpperCamelCase_					(   self		:		Dict	):

											'''simple docstring'''
											self.assertEqual(self.get_tokenizer().vocab_size      ,				1005	)





							def 						UpperCamelCase_					(   self		:		Optional[int]	):

											'''simple docstring'''
											__a       =		CamembertTokenizer(__lowercase	)
											tokenizer.save_pretrained(self.tmpdirname	)
											__a       =		CamembertTokenizerFast.from_pretrained(self.tmpdirname	)

											__a       =		"""I was born in 92000, and this is falsé."""

											__a       =		tokenizer.encode(__lowercase	)
											__a       =		rust_tokenizer.encode(__lowercase	)
											self.assertListEqual(__lowercase      ,				__lowercase	)

											__a       =		tokenizer.encode(__lowercase      ,				add_special_tokens=__lowercase	)
											__a       =		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)
											__a       =		tokenizer.convert_ids_to_tokens(__lowercase	)
											__a       =		rust_tokenizer.tokenize(__lowercase	)
											self.assertListEqual(__lowercase      ,				__lowercase	)





							def 						UpperCamelCase_					(   self		:		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(__lowercase	)
											__a       =		rust_tokenizer.tokenize(__lowercase	)
											self.assertListEqual(__lowercase      ,				__lowercase	)

											__a       =		tokenizer.encode(__lowercase      ,				add_special_tokens=__lowercase	)
											__a       =		rust_tokenizer.encode(__lowercase      ,				add_special_tokens=__lowercase	)
											self.assertListEqual(__lowercase      ,				__lowercase	)

											__a       =		self.get_rust_tokenizer()
											__a       =		tokenizer.encode(__lowercase	)
											__a       =		rust_tokenizer.encode(__lowercase	)
											self.assertListEqual(__lowercase      ,				__lowercase	)







							@slow
							def 						UpperCamelCase_					(   self		:		Union[str, Any]	):

											'''simple docstring'''
											# fmt: off
											__a       =		{"""input_ids""": [[5, 54, 7196, 297, 30, 23, 776, 18, 11, 3215, 3705, 8252, 22, 3164, 1181, 2116, 29, 16, 813, 25, 791, 3314, 20, 3446, 38, 27575, 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, 9088, 20, 1517, 8, 22804, 18818, 10, 38, 629, 607, 607, 142, 19, 7196, 867, 56, 10326, 24, 2267, 20, 416, 5072, 15612, 233, 734, 7, 2399, 27, 16, 3015, 1649, 7, 24, 20, 4338, 2399, 27, 13, 3400, 14, 13, 6189, 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.
											__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=__lowercase      ,				model_name="""camembert-base"""      ,				revision="""3a0641d9a1aeb7e848a74299e7e4c4bca216b4cf"""      ,				sequences=__lowercase      ,				)





def   lowerCAmelCase__						(							_SCREAMING_SNAKE_CASE       :			int = 3				,     _SCREAMING_SNAKE_CASE       :			int = 7				,     _SCREAMING_SNAKE_CASE       :			int = 100_0000    ):
				"""simple docstring"""







				__a       =		0
				__a       =		1

				for current_denominator in range(1				,     limit + 1    ):
								__a       =		current_denominator * numerator // denominator
								if current_denominator % denominator == 0:
												current_numerator -= 1
								if current_numerator * max_denominator > current_denominator * max_numerator:
												__a       =		current_numerator
												__a       =		current_denominator
				return max_numerator


if __name__ == "__main__":
						print(solution(numerator=3, denominator=7, limit=100_0000))
