
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		( lowerCamelCase__	,  unittest.TestCase		):
							lowercase_	:	Union[str, Any]	 =BarthezTokenizer
							lowercase_	:	Optional[int]	 =BarthezTokenizerFast
							lowercase_	:	Tuple	 =True
							lowercase_	:	List[str]	 =True




							def 			A__				(    self):
												super().setUp()

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




							def 			A__				(    self):
												lowercase						     =						"<pad>"
												lowercase						     =						1

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




							def 			A__				(    self):
												lowercase						     =						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(A__)       ,1_0_1_1_2_2)




							def 			A__				(    self):
												self.assertEqual(self.get_tokenizer().vocab_size       ,1_0_1_1_2_2)




							@require_torch
							def 			A__				(    self):
												lowercase						     =						["A long paragraph for summarization.", "Another paragraph for summarization."]
												lowercase						     =						[0, 5_7, 3_0_1_8, 7_0_3_0_7, 9_1, 2]

												lowercase						     =						self.tokenizer(
												    A__       ,max_length=len(A__)       ,padding=A__       ,truncation=A__       ,return_tensors='''pt''')
												self.assertIsInstance(A__       ,A__)

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




							def 			A__				(    self):




												if not self.test_rust_tokenizer:
																	return

												lowercase						     =						self.get_tokenizer()
												lowercase						     =						self.get_rust_tokenizer()

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

												lowercase						     =						tokenizer.tokenize(A__)
												lowercase						     =						rust_tokenizer.tokenize(A__)
												self.assertListEqual(A__       ,A__)

												lowercase						     =						tokenizer.encode(A__       ,add_special_tokens=A__)
												lowercase						     =						rust_tokenizer.encode(A__       ,add_special_tokens=A__)
												self.assertListEqual(A__       ,A__)

												lowercase						     =						self.get_rust_tokenizer()
												lowercase						     =						tokenizer.encode(A__)
												lowercase						     =						rust_tokenizer.encode(A__)
												self.assertListEqual(A__       ,A__)





							@slow
							def 			A__				(    self):
												lowercase						     =						{"input_ids": [[0, 4_9_0, 1_4_3_2_8, 4_5_0_7, 3_5_4, 4_7, 4_3_6_6_9, 9_5, 2_5, 7_8_1_1_7, 2_0_2_1_5, 1_9_7_7_9, 1_9_0, 2_2, 4_0_0, 4, 3_5_3_4_3, 8_0_3_1_0, 6_0_3, 8_6, 2_4_9_3_7, 1_0_5, 3_3_4_3_8, 9_4_7_6_2, 1_9_6, 3_9_6_4_2, 7, 1_5, 1_5_9_3_3, 1_7_3, 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_0_5_3_4, 8_7, 2_5, 6_6, 3_3_5_8, 1_9_6, 5_5_2_8_9, 8, 8_2_9_6_1, 8_1, 2_2_0_4, 7_5_2_0_3, 7, 1_5, 7_6_3, 1_2_9_5_6, 2_1_6, 1_7_8, 1_4_3_2_8, 9_5_9_5, 1_3_7_7, 6_9_6_9_3, 7, 4_4_8, 7_1_0_2_1, 1_9_6, 1_8_1_0_6, 1_4_3_7, 1_3_9_7_4, 1_0_8, 9_0_8_3, 4, 4_9_3_1_5, 7, 3_9, 8_6, 1_3_2_6, 2_7_9_3, 4_6_3_3_3, 4, 4_4_8, 1_9_6, 7_4_5_8_8, 7, 4_9_3_1_5, 7, 3_9, 2_1, 8_2_2, 3_8_4_7_0, 7_4, 2_1, 6_6_7_2_3, 6_2_4_8_0, 8, 2_2_0_5_0, 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.
												lowercase						     =						[
												    "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=A__       ,model_name='''moussaKam/mbarthez'''       ,revision='''c2e4ecbca5e3cd2c37fe1ac285ca4fbdf1366fb6'''       ,sequences=A__       ,)





lowercase__		:List[str]			  =   6_5521



def 	UpperCamelCase   (							lowerCAmelCase__		):
					'''simple docstring'''
					lowercase						     =						1
					lowercase						     =						0
					for plain_chr in plain_text:
										lowercase						     =						(a + ord(lowerCAmelCase__		)) % MOD_ADLER
										lowercase						     =						(b + a) % MOD_ADLER
					return (b << 16) | a




