



"""simple docstring"""






import unittest

from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow

from ...test_tokenization_common import TokenizerTesterMixin



@require_tokenizers
@require_sentencepiece
@slow  # see https://github.com/huggingface/transformers/issues/11457
class     A__     (						__SCREAMING_SNAKE_CASE						,	unittest.TestCase							):




 '''simple docstring'''





 SCREAMING_SNAKE_CASE					   =			BarthezTokenizer
 SCREAMING_SNAKE_CASE					   =			BarthezTokenizerFast
 SCREAMING_SNAKE_CASE					   =			True
 SCREAMING_SNAKE_CASE					   =			True

 def 							_SCREAMING_SNAKE_CASE     (  self:	Optional[int])       -> Any:

    """simple docstring"""

    super().setUp()

    __lowerCAmelCase   :						List[Any]				= BarthezTokenizerFast.from_pretrained("moussaKam/mbarthez")
    tokenizer.save_pretrained(self.tmpdirname)
    tokenizer.save_pretrained(self.tmpdirname ,    legacy_format=_SCREAMING_SNAKE_CASE)
    __lowerCAmelCase   :						str				= tokenizer

 def 							_SCREAMING_SNAKE_CASE     (  self:	str)       -> Tuple:

    """simple docstring"""

    __lowerCAmelCase   :						int				= "<pad>"
    __lowerCAmelCase   :						Tuple				= 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 							_SCREAMING_SNAKE_CASE     (  self:	Union[str, Any])       -> Optional[Any]:

    """simple docstring"""

    __lowerCAmelCase   :						List[Any]				= list(self.get_tokenizer().get_vocab().keys())

    self.assertEqual(vocab_keys[0] ,    "<s>")
    self.assertEqual(vocab_keys[1] ,    "<pad>")
    self.assertEqual(vocab_keys[-1] ,    "<mask>")
    self.assertEqual(len(_SCREAMING_SNAKE_CASE) ,    10_1122)

 def 							_SCREAMING_SNAKE_CASE     (  self:	Dict)       -> List[Any]:

    """simple docstring"""

    self.assertEqual(self.get_tokenizer().vocab_size ,    10_1122)

 @require_torch
 def 							_SCREAMING_SNAKE_CASE     (  self:	str)       -> int:

    """simple docstring"""

    __lowerCAmelCase   :						str				= ["A long paragraph for summarization.", "Another paragraph for summarization."]
    __lowerCAmelCase   :						Optional[Any]				= [0, 57, 3018, 7_0307, 91, 2]

    __lowerCAmelCase   :						List[Any]				= self.tokenizer(
        _SCREAMING_SNAKE_CASE ,    max_length=len(_SCREAMING_SNAKE_CASE) ,    padding=_SCREAMING_SNAKE_CASE ,    truncation=_SCREAMING_SNAKE_CASE ,    return_tensors="pt")
    self.assertIsInstance(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)

    self.assertEqual((2, 6) ,    batch.input_ids.shape)
    self.assertEqual((2, 6) ,    batch.attention_mask.shape)
    __lowerCAmelCase   :						str				= batch.input_ids.tolist()[0]
    self.assertListEqual(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)

 def 							_SCREAMING_SNAKE_CASE     (  self:	Tuple)       -> Any:

    """simple docstring"""

    if not self.test_rust_tokenizer:
       return

    __lowerCAmelCase   :						Any				= self.get_tokenizer()
    __lowerCAmelCase   :						str				= self.get_rust_tokenizer()

    __lowerCAmelCase   :						List[str]				= "I was born in 92000, and this is falsé."

    __lowerCAmelCase   :						Union[str, Any]				= tokenizer.tokenize(_SCREAMING_SNAKE_CASE)
    __lowerCAmelCase   :						Tuple				= rust_tokenizer.tokenize(_SCREAMING_SNAKE_CASE)
    self.assertListEqual(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)

    __lowerCAmelCase   :						str				= tokenizer.encode(_SCREAMING_SNAKE_CASE ,    add_special_tokens=_SCREAMING_SNAKE_CASE)
    __lowerCAmelCase   :						str				= rust_tokenizer.encode(_SCREAMING_SNAKE_CASE ,    add_special_tokens=_SCREAMING_SNAKE_CASE)
    self.assertListEqual(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)

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







 @slow
 def 							_SCREAMING_SNAKE_CASE     (  self:	List[str])       -> List[str]:

    """simple docstring"""

    __lowerCAmelCase   :						Optional[Any]				= {"input_ids": [[0, 490, 1_4328, 4507, 354, 47, 4_3669, 95, 25, 7_8117, 2_0215, 1_9779, 190, 22, 400, 4, 3_5343, 8_0310, 603, 86, 2_4937, 105, 3_3438, 9_4762, 196, 3_9642, 7, 15, 1_5933, 173, 2, 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, 1_0534, 87, 25, 66, 3358, 196, 5_5289, 8, 8_2961, 81, 2204, 7_5203, 7, 15, 763, 1_2956, 216, 178, 1_4328, 9595, 1377, 6_9693, 7, 448, 7_1021, 196, 1_8106, 1437, 1_3974, 108, 9083, 4, 4_9315, 7, 39, 86, 1326, 2793, 4_6333, 4, 448, 196, 7_4588, 7, 4_9315, 7, 39, 21, 822, 3_8470, 74, 21, 6_6723, 6_2480, 8, 2_2050, 5, 2]], "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, 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, 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, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
    # fmt: on

    # moussaKam/mbarthez is a french model. So we also use french texts.
    __lowerCAmelCase   :						Any				= [
        "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="moussaKam/mbarthez" ,    revision="c2e4ecbca5e3cd2c37fe1ac285ca4fbdf1366fb6" ,    sequences=_SCREAMING_SNAKE_CASE ,    )




"""simple docstring"""






def     _lowercase       (						__snake_case = 3      ,__snake_case = 7      ,__snake_case = 1_000_000			)		->     int:
			__lowerCAmelCase   :						Optional[Any]				= 0
			__lowerCAmelCase   :						List[str]				= 1

			for current_denominator in range(1      ,limit + 1			):
						__lowerCAmelCase   :						Optional[int]				= current_denominator * numerator // denominator
						if current_denominator % denominator == 0:
									current_numerator -= 1
						if current_numerator * max_denominator > current_denominator * max_numerator:
									__lowerCAmelCase   :						Union[str, Any]				= current_numerator
									__lowerCAmelCase   :						int				= current_denominator
			return max_numerator


if __name__ == "__main__":
	print(solution(numerator=3, denominator=7, limit=1_000_000))