
"""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 	_lowercase       (    __UpperCAmelCase    ,	unittest.TestCase		):
	lowercase_				=     BarthezTokenizer
	lowercase_				=     BarthezTokenizerFast
	lowercase_				=     True
	lowercase_				=     True




	def       _UpperCamelCase   (			self )		->							Optional[Any]:
		super().setUp()

		lowerCamelCase					:      Optional[Any]          =   BarthezTokenizerFast.from_pretrained('moussaKam/mbarthez' )
		tokenizer.save_pretrained(self.tmpdirname )
		tokenizer.save_pretrained(self.tmpdirname		,			legacy_format=UpperCAmelCase_ )
		lowerCamelCase					:      List[Any]          =   tokenizer




	def       _UpperCamelCase   (			self )		->							List[str]:
		lowerCamelCase					:      Union[str, Any]          =   '<pad>'
		lowerCamelCase					:      Tuple          =   1

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




	def       _UpperCamelCase   (			self )		->							Optional[int]:
		lowerCamelCase					:      int          =   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(UpperCAmelCase_ )		,			101122 )




	def       _UpperCamelCase   (			self )		->							Any:
		self.assertEqual(self.get_tokenizer().vocab_size		,			101122 )




	@require_torch
	def       _UpperCamelCase   (			self )		->							Tuple:
		lowerCamelCase					:      str          =   ['A long paragraph for summarization.', 'Another paragraph for summarization.']
		lowerCamelCase					:      List[Any]          =   [0, 57, 3018, 70307, 91, 2]

		lowerCamelCase					:      Tuple          =   self.tokenizer(
		    UpperCAmelCase_		,			max_length=len(UpperCAmelCase_ )		,			padding=UpperCAmelCase_		,			truncation=UpperCAmelCase_		,			return_tensors='pt' )
		self.assertIsInstance(UpperCAmelCase_		,			UpperCAmelCase_ )

		self.assertEqual((2, 6)		,			batch.input_ids.shape )
		self.assertEqual((2, 6)		,			batch.attention_mask.shape )
		lowerCamelCase					:      Dict          =   batch.input_ids.tolist()[0]
		self.assertListEqual(UpperCAmelCase_		,			UpperCAmelCase_ )




	def       _UpperCamelCase   (			self )		->							Optional[Any]:
		if not self.test_rust_tokenizer:
			return

		lowerCamelCase					:      List[str]          =   self.get_tokenizer()
		lowerCamelCase					:      Union[str, Any]          =   self.get_rust_tokenizer()

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

		lowerCamelCase					:      List[Any]          =   tokenizer.tokenize(UpperCAmelCase_ )
		lowerCamelCase					:      Dict          =   rust_tokenizer.tokenize(UpperCAmelCase_ )
		self.assertListEqual(UpperCAmelCase_		,			UpperCAmelCase_ )

		lowerCamelCase					:      Optional[int]          =   tokenizer.encode(UpperCAmelCase_		,			add_special_tokens=UpperCAmelCase_ )
		lowerCamelCase					:      List[Any]          =   rust_tokenizer.encode(UpperCAmelCase_		,			add_special_tokens=UpperCAmelCase_ )
		self.assertListEqual(UpperCAmelCase_		,			UpperCAmelCase_ )

		lowerCamelCase					:      str          =   self.get_rust_tokenizer()
		lowerCamelCase					:      Optional[int]          =   tokenizer.encode(UpperCAmelCase_ )
		lowerCamelCase					:      Any          =   rust_tokenizer.encode(UpperCAmelCase_ )
		self.assertListEqual(UpperCAmelCase_		,			UpperCAmelCase_ )




	@slow
	def       _UpperCamelCase   (			self )		->							Dict:
		# fmt: off
		lowerCamelCase					:      Tuple          =   {'input_ids': [[0, 490, 14328, 4507, 354, 47, 43669, 95, 25, 78117, 20215, 19779, 190, 22, 400, 4, 35343, 80310, 603, 86, 24937, 105, 33438, 94762, 196, 39642, 7, 15, 15933, 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, 10534, 87, 25, 66, 3358, 196, 55289, 8, 82961, 81, 2204, 75203, 7, 15, 763, 12956, 216, 178, 14328, 9595, 1377, 69693, 7, 448, 71021, 196, 18106, 1437, 13974, 108, 9083, 4, 49315, 7, 39, 86, 1326, 2793, 46333, 4, 448, 196, 74588, 7, 49315, 7, 39, 21, 822, 38470, 74, 21, 66723, 62480, 8, 22050, 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					:      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=UpperCAmelCase_		,			model_name='moussaKam/mbarthez'		,			revision='c2e4ecbca5e3cd2c37fe1ac285ca4fbdf1366fb6'		,			sequences=UpperCAmelCase_		,			)








"""simple docstring"""

def 		UpperCAmelCase (		a_      ):





		'''simple docstring'''


		lowerCamelCase					:      List[Any]          =   1
		for i in range(1,						num + 1      ):
				fact *= i
		return fact
def 		UpperCAmelCase (		a_      ):





		'''simple docstring'''


		lowerCamelCase					:      Optional[Any]          =   0
		while number > 0:
				lowerCamelCase					:      str          =   number % 10
				sum_of_digits += last_digit
				lowerCamelCase					:      Tuple          =   number // 10  # Removing the last_digit from the given number
		return sum_of_digits
def 		UpperCAmelCase (		a_ = 100      ):





		'''simple docstring'''


		lowerCamelCase					:      Optional[Any]          =   factorial(a_      )
		lowerCamelCase					:      int          =   split_and_add(a_      )
		return result


if __name__ == "__main__":
					print(solution(int(input('Enter the Number: ').strip())))






