




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 (       __magic_name__			,				unittest.TestCase ):

			"""simple docstring"""







			snake_case_   		=       BarthezTokenizer
			snake_case_   		=       BarthezTokenizerFast
			snake_case_   		=       True
			snake_case_   		=       True


			def       lowercase_    (      self							)    ->      int:



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

							__lowerCamelCase		       =    BarthezTokenizerFast.from_pretrained('moussaKam/mbarthez'							)
							tokenizer.save_pretrained(self.tmpdirname							)
							tokenizer.save_pretrained(self.tmpdirname			,						legacy_format=lowerCamelCase__							)
							__lowerCamelCase		       =    tokenizer


			def       lowercase_    (      self							)    ->      Union[str, Any]:



							'''simple docstring'''
							__lowerCamelCase		       =    '<pad>'
							__lowerCamelCase		       =    1

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


			def       lowercase_    (      self							)    ->      str:



							'''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(lowerCamelCase__							)			,						101_122							)


			def       lowercase_    (      self							)    ->      Union[str, Any]:



							'''simple docstring'''
							self.assertEqual(self.get_tokenizer().vocab_size			,						101_122							)


			@require_torch
			def       lowercase_    (      self							)    ->      str:



							'''simple docstring'''
							__lowerCamelCase		       =    ['A long paragraph for summarization.', 'Another paragraph for summarization.']
							__lowerCamelCase		       =    [0, 57, 3_018, 70_307, 91, 2]

							__lowerCamelCase		       =    self.tokenizer(
							    lowerCamelCase__			,						max_length=len(lowerCamelCase__							)			,						padding=lowerCamelCase__			,						truncation=lowerCamelCase__			,						return_tensors='pt'							)
							self.assertIsInstance(lowerCamelCase__			,						lowerCamelCase__							)

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


			def       lowercase_    (      self							)    ->      Union[str, Any]:



							'''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(lowerCamelCase__							)
							__lowerCamelCase		       =    rust_tokenizer.tokenize(lowerCamelCase__							)
							self.assertListEqual(lowerCamelCase__			,						lowerCamelCase__							)

							__lowerCamelCase		       =    tokenizer.encode(lowerCamelCase__			,						add_special_tokens=lowerCamelCase__							)
							__lowerCamelCase		       =    rust_tokenizer.encode(lowerCamelCase__			,						add_special_tokens=lowerCamelCase__							)
							self.assertListEqual(lowerCamelCase__			,						lowerCamelCase__							)

							__lowerCamelCase		       =    self.get_rust_tokenizer()
							__lowerCamelCase		       =    tokenizer.encode(lowerCamelCase__							)
							__lowerCamelCase		       =    rust_tokenizer.encode(lowerCamelCase__							)
							self.assertListEqual(lowerCamelCase__			,						lowerCamelCase__							)






			@slow
			def       lowercase_    (      self							)    ->      Union[str, Any]:



							'''simple docstring'''
							# fmt: off
							__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=lowerCamelCase__			,						model_name='moussaKam/mbarthez'			,						revision='c2e4ecbca5e3cd2c37fe1ac285ca4fbdf1366fb6'			,						sequences=lowerCamelCase__			,						)








def 			lowerCamelCase_		(       UpperCamelCase__				:      int      )     ->       bool:





				"""simple docstring"""


				return number & 1 == 0


if __name__ == "__main__":
					import doctest

					doctest.testmod()


