






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 				__A     (			a      ,     unittest.TestCase ):





				"""simple docstring"""







				UpperCamelCase__ :      int			 =BarthezTokenizer
				UpperCamelCase__ :      Union[str, Any]			 =BarthezTokenizerFast
				UpperCamelCase__ :      List[str]			 =True
				UpperCamelCase__ :      int			 =True


				def       __lowercase							( self    ):




									"""simple docstring"""

									super().setUp()

									__UpperCamelCase      :					Any       		=BarthezTokenizerFast.from_pretrained('moussaKam/mbarthez'    )
									tokenizer.save_pretrained(self.tmpdirname    )
									tokenizer.save_pretrained(self.tmpdirname							,  legacy_format=lowerCamelCase__    )
									__UpperCamelCase      :					str       		=tokenizer


				def       __lowercase							( self    ):




									"""simple docstring"""

									__UpperCamelCase      :					Union[str, Any]       		='<pad>'
									__UpperCamelCase      :					Dict       		=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    ):




									"""simple docstring"""

									__UpperCamelCase      :					List[str]       		=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__    )							,  101122    )


				def       __lowercase							( self    ):




									"""simple docstring"""

									self.assertEqual(self.get_tokenizer().vocab_size							,  101122    )


				@require_torch
				def       __lowercase							( self    ):




									"""simple docstring"""

									__UpperCamelCase      :					Tuple       		=['A long paragraph for summarization.', 'Another paragraph for summarization.']
									__UpperCamelCase      :					int       		=[0, 57, 3018, 70307, 91, 2]

									__UpperCamelCase      :					Union[str, Any]       		=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    )
									__UpperCamelCase      :					List[str]       		=batch.input_ids.tolist()[0]
									self.assertListEqual(lowerCamelCase__							,  lowerCamelCase__    )


				def       __lowercase							( self    ):




									"""simple docstring"""

									if not self.test_rust_tokenizer:
														return

									__UpperCamelCase      :					Union[str, Any]       		=self.get_tokenizer()
									__UpperCamelCase      :					int       		=self.get_rust_tokenizer()

									__UpperCamelCase      :					str       		='I was born in 92000, and this is falsé.'

									__UpperCamelCase      :					Tuple       		=tokenizer.tokenize(lowerCamelCase__    )
									__UpperCamelCase      :					List[str]       		=rust_tokenizer.tokenize(lowerCamelCase__    )
									self.assertListEqual(lowerCamelCase__							,  lowerCamelCase__    )

									__UpperCamelCase      :					List[Any]       		=tokenizer.encode(lowerCamelCase__							,  add_special_tokens=lowerCamelCase__    )
									__UpperCamelCase      :					Union[str, Any]       		=rust_tokenizer.encode(lowerCamelCase__							,  add_special_tokens=lowerCamelCase__    )
									self.assertListEqual(lowerCamelCase__							,  lowerCamelCase__    )

									__UpperCamelCase      :					List[Any]       		=self.get_rust_tokenizer()
									__UpperCamelCase      :					Tuple       		=tokenizer.encode(lowerCamelCase__    )
									__UpperCamelCase      :					List[str]       		=rust_tokenizer.encode(lowerCamelCase__    )
									self.assertListEqual(lowerCamelCase__							,  lowerCamelCase__    )







				@slow
				def       __lowercase							( self    ):




									"""simple docstring"""

									__UpperCamelCase      :					Dict       		={'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.
									__UpperCamelCase      :					str       		=[
									    '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__							,  )





import os
import unittest

from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow

from ...test_tokenization_common import TokenizerTesterMixin





@require_jieba
class   __a			(    __UpperCamelCase       ,       unittest.TestCase      ):
 __lowercase :							str        = CpmAntTokenizer
 __lowercase :							List[Any]        = False
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				str:




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

        lowercase__:   Any  			=   [
            '<d>',
            '</d>',
            '<s>',
            '</s>',
            '</_>',
            '<unk>',
            '<pad>',
            '</n>',
            '我',
            '是',
            'C',
            'P',
            'M',
            'A',
            'n',
            't',
        ]
        lowercase__:   List[Any]  			=   os.path.join(self.tmpdirname				, VOCAB_FILES_NAMES['vocab_file'] )
        with open(self.vocab_file				, 'w'				, encoding='utf-8' ) as vocab_writer:
               vocab_writer.write(''.join([x + '\n' for x in vocab_tokens] ) )
 @tooslow
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				Tuple:




        '''simple docstring'''
        lowercase__:   Optional[int]  			=   CpmAntTokenizer.from_pretrained('openbmb/cpm-ant-10b' )
        lowercase__:   Optional[Any]  			=   '今天天气真好！'
        lowercase__:   str  			=   ['今天', '天气', '真', '好', '！']
        lowercase__:   Optional[Any]  			=   tokenizer.tokenize(lowerCAmelCase__ )
        self.assertListEqual(lowerCAmelCase__				, lowerCAmelCase__ )
        lowercase__:   List[str]  			=   '今天天气真好！'
        lowercase__:   List[str]  			=   [tokenizer.bos_token] + tokens

        lowercase__:   Tuple  			=   [6, 9_802, 14_962, 2_082, 831, 244]
        self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCAmelCase__ )				, lowerCAmelCase__ )

        lowercase__:   Any  			=   tokenizer.decode(lowerCAmelCase__ )
        self.assertEqual(lowerCAmelCase__				, lowerCAmelCase__ )


