
'''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     UpperCAmelCase_	(						_SCREAMING_SNAKE_CASE			,				unittest.TestCase					):






						'''simple docstring'''






						_lowercase						: Tuple										=  BarthezTokenizer
						_lowercase						: Union[str, Any]										=  BarthezTokenizerFast
						_lowercase						: Any										=  True
						_lowercase						: Optional[int]										=  True




						def    _lowercase      (   self ):

												"""simple docstring"""



												super().setUp()

												_lowerCAmelCase    		=					BarthezTokenizerFast.from_pretrained("""moussaKam/mbarthez""" )
												tokenizer.save_pretrained(self.tmpdirname )
												tokenizer.save_pretrained(self.tmpdirname       ,  legacy_format=_lowercase )
												_lowerCAmelCase    		=					tokenizer




						def    _lowercase      (   self ):

												"""simple docstring"""



												_lowerCAmelCase    		=					"""<pad>"""
												_lowerCAmelCase    		=					1

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




						def    _lowercase      (   self ):

												"""simple docstring"""



												_lowerCAmelCase    		=					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(_lowercase )       ,  101_122 )




						def    _lowercase      (   self ):

												"""simple docstring"""



												self.assertEqual(self.get_tokenizer().vocab_size       ,  101_122 )




						@require_torch
						def    _lowercase      (   self ):

												"""simple docstring"""



												_lowerCAmelCase    		=					["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
												_lowerCAmelCase    		=					[0, 57, 3_018, 70_307, 91, 2]

												_lowerCAmelCase    		=					self.tokenizer(
												    _lowercase       ,  max_length=len(_lowercase )       ,  padding=_lowercase       ,  truncation=_lowercase       ,  return_tensors="""pt""" )
												self.assertIsInstance(_lowercase       ,  _lowercase )

												self.assertEqual((2, 6)       ,  batch.input_ids.shape )
												self.assertEqual((2, 6)       ,  batch.attention_mask.shape )
												_lowerCAmelCase    		=					batch.input_ids.tolist()[0]
												self.assertListEqual(_lowercase       ,  _lowercase )




						def    _lowercase      (   self ):

												"""simple docstring"""



												if not self.test_rust_tokenizer:
																		return

												_lowerCAmelCase    		=					self.get_tokenizer()
												_lowerCAmelCase    		=					self.get_rust_tokenizer()

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

												_lowerCAmelCase    		=					tokenizer.tokenize(_lowercase )
												_lowerCAmelCase    		=					rust_tokenizer.tokenize(_lowercase )
												self.assertListEqual(_lowercase       ,  _lowercase )

												_lowerCAmelCase    		=					tokenizer.encode(_lowercase       ,  add_special_tokens=_lowercase )
												_lowerCAmelCase    		=					rust_tokenizer.encode(_lowercase       ,  add_special_tokens=_lowercase )
												self.assertListEqual(_lowercase       ,  _lowercase )

												_lowerCAmelCase    		=					self.get_rust_tokenizer()
												_lowerCAmelCase    		=					tokenizer.encode(_lowercase )
												_lowerCAmelCase    		=					rust_tokenizer.encode(_lowercase )
												self.assertListEqual(_lowercase       ,  _lowercase )




						@slow
						def    _lowercase      (   self ):

												"""simple docstring"""



												_lowerCAmelCase    		=					{"""input_ids""": [[0, 490, 14_328, 4_507, 354, 47, 43_669, 95, 25, 78_117, 20_215, 19_779, 190, 22, 400, 4, 35_343, 80_310, 603, 86, 24_937, 105, 33_438, 94_762, 196, 39_642, 7, 15, 15_933, 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, 10_534, 87, 25, 66, 3_358, 196, 55_289, 8, 82_961, 81, 2_204, 75_203, 7, 15, 763, 12_956, 216, 178, 14_328, 9_595, 1_377, 69_693, 7, 448, 71_021, 196, 18_106, 1_437, 13_974, 108, 9_083, 4, 49_315, 7, 39, 86, 1_326, 2_793, 46_333, 4, 448, 196, 74_588, 7, 49_315, 7, 39, 21, 822, 38_470, 74, 21, 66_723, 62_480, 8, 22_050, 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    		=					[
												    """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="""moussaKam/mbarthez"""       ,  revision="""c2e4ecbca5e3cd2c37fe1ac285ca4fbdf1366fb6"""       ,  sequences=_lowercase       ,  )







"""simple docstring"""






import functools






def      lowercase__ (					lowerCAmelCase__   :			str							,			lowerCAmelCase__   :			str			)    ->			int:



			'''simple docstring'''
			a__  :	Any		 =			len(lowerCAmelCase__			)
			a__  :	Optional[int]		 =			len(lowerCAmelCase__			)

			@functools.cache
			def min_distance(lowerCAmelCase__   :			int							,			lowerCAmelCase__   :			int			) -> int:
						# if first word index is overflow - delete all from the second word
						if indexa >= len_worda:
									return len_worda - indexa
						# if second word index is overflow - delete all from the first word
						if indexa >= len_worda:
									return len_worda - indexa
						a__  :	List[Any]		 =			int(worda[indexa] != worda[indexa]			)  # current letters not identical
						return min(
						    1 + min_distance(indexa + 1							,			lowerCAmelCase__			)							,			1 + min_distance(lowerCAmelCase__							,			indexa + 1			)							,			diff + min_distance(indexa + 1							,			indexa + 1			)							,			)

			return min_distance(0							,			0			)


if __name__ == "__main__":
		import doctest

		doctest.testmod()