




"""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 lowerCAmelCase__			(  lowercase,			unittest.TestCase		):






			'''simple docstring'''



			lowerCamelCase__   =    BarthezTokenizer
			lowerCamelCase__   =    BarthezTokenizerFast
			lowerCamelCase__   =    True
			lowerCamelCase__   =    True
			def       A_					(						self						):
							super().setUp()

							_lowerCamelCase  :    List[str]					=					BarthezTokenizerFast.from_pretrained('moussaKam/mbarthez'						)
							tokenizer.save_pretrained(self.tmpdirname						)
							tokenizer.save_pretrained(self.tmpdirname						,   legacy_format=lowercase						)
							_lowerCamelCase  :    int					=					tokenizer
			def       A_					(						self						):
							_lowerCamelCase  :    List[str]					=					'<pad>'
							_lowerCamelCase  :    Any					=					1

							self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowercase						)						,   lowercase						)
							self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowercase						)						,   lowercase						)
			def       A_					(						self						):
							_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(lowercase						)						,   101122						)
			def       A_					(						self						):
							self.assertEqual(self.get_tokenizer().vocab_size						,   101122						)
			@require_torch
			def       A_					(						self						):
							_lowerCamelCase  :    Any					=					['A long paragraph for summarization.', 'Another paragraph for summarization.']
							_lowerCamelCase  :    List[str]					=					[0, 57, 3018, 70307, 91, 2]

							_lowerCamelCase  :    Any					=					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  :    Any					=					batch.input_ids.tolist()[0]
							self.assertListEqual(lowercase						,   lowercase						)
			def       A_					(						self						):
							if not self.test_rust_tokenizer:
											return

							_lowerCamelCase  :    Optional[int]					=					self.get_tokenizer()
							_lowerCamelCase  :    Optional[int]					=					self.get_rust_tokenizer()

							_lowerCamelCase  :    Tuple					=					'I was born in 92000, and this is falsé.'

							_lowerCamelCase  :    List[Any]					=					tokenizer.tokenize(lowercase						)
							_lowerCamelCase  :    Tuple					=					rust_tokenizer.tokenize(lowercase						)
							self.assertListEqual(lowercase						,   lowercase						)

							_lowerCamelCase  :    Tuple					=					tokenizer.encode(lowercase						,   add_special_tokens=lowercase						)
							_lowerCamelCase  :    Union[str, Any]					=					rust_tokenizer.encode(lowercase						,   add_special_tokens=lowercase						)
							self.assertListEqual(lowercase						,   lowercase						)

							_lowerCamelCase  :    Union[str, Any]					=					self.get_rust_tokenizer()
							_lowerCamelCase  :    Dict					=					tokenizer.encode(lowercase						)
							_lowerCamelCase  :    Tuple					=					rust_tokenizer.encode(lowercase						)
							self.assertListEqual(lowercase						,   lowercase						)






			@slow
			def       A_					(						self						):
							# 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  :    List[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=lowercase						,   model_name='moussaKam/mbarthez'						,   revision='c2e4ecbca5e3cd2c37fe1ac285ca4fbdf1366fb6'						,   sequences=lowercase						,   )





"""simple docstring"""






def   _snake_case    (       lowercase__	):
				return "".join(chr(ord(lowercase__	) - 32	) if 'a' <= char <= 'z' else char for char in word	)


if __name__ == "__main__":
			from doctest import testmod

			testmod()