

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_		(	SCREAMING_SNAKE_CASE      ,							unittest.TestCase    ):
							_UpperCAmelCase   :  List[str]										=				BarthezTokenizer
							_UpperCAmelCase   :  Dict										=				BarthezTokenizerFast
							_UpperCAmelCase   :  Optional[int]										=				True
							_UpperCAmelCase   :  int										=				True
							def    lowerCAmelCase					(		self		:      List[str]):
								super().setUp()

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

								self.assertEqual(self.get_tokenizer()._convert_token_to_id(SCREAMING_SNAKE_CASE__)       ,SCREAMING_SNAKE_CASE__)
								self.assertEqual(self.get_tokenizer()._convert_id_to_token(SCREAMING_SNAKE_CASE__)       ,SCREAMING_SNAKE_CASE__)
							def    lowerCAmelCase					(		self		:      Optional[int]):
								__lowerCamelCase    :    Optional[int] 	=			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(SCREAMING_SNAKE_CASE__)       ,1_0_1_1_2_2)
							def    lowerCAmelCase					(		self		:      Optional[int]):
								self.assertEqual(self.get_tokenizer().vocab_size       ,1_0_1_1_2_2)
							@require_torch
							def    lowerCAmelCase					(		self		:      Optional[Any]):
								__lowerCamelCase    :    int 	=			['A long paragraph for summarization.', 'Another paragraph for summarization.']
								__lowerCamelCase    :    Optional[int] 	=			[0, 5_7, 3_0_1_8, 7_0_3_0_7, 9_1, 2]

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

								self.assertEqual((2, 6)       ,batch.input_ids.shape)
								self.assertEqual((2, 6)       ,batch.attention_mask.shape)
								__lowerCamelCase    :    List[str] 	=			batch.input_ids.tolist()[0]
								self.assertListEqual(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)
							def    lowerCAmelCase					(		self		:      Optional[int]):
								if not self.test_rust_tokenizer:
									return

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

								__lowerCamelCase    :    Optional[int] 	=			'I was born in 92000, and this is falsé.'

								__lowerCamelCase    :    Union[str, Any] 	=			tokenizer.tokenize(SCREAMING_SNAKE_CASE__)
								__lowerCamelCase    :    int 	=			rust_tokenizer.tokenize(SCREAMING_SNAKE_CASE__)
								self.assertListEqual(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)

								__lowerCamelCase    :    Optional[Any] 	=			tokenizer.encode(SCREAMING_SNAKE_CASE__       ,add_special_tokens=SCREAMING_SNAKE_CASE__)
								__lowerCamelCase    :    Tuple 	=			rust_tokenizer.encode(SCREAMING_SNAKE_CASE__       ,add_special_tokens=SCREAMING_SNAKE_CASE__)
								self.assertListEqual(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)

								__lowerCamelCase    :    int 	=			self.get_rust_tokenizer()
								__lowerCamelCase    :    str 	=			tokenizer.encode(SCREAMING_SNAKE_CASE__)
								__lowerCamelCase    :    Any 	=			rust_tokenizer.encode(SCREAMING_SNAKE_CASE__)
								self.assertListEqual(SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__)


							@slow
							def    lowerCAmelCase					(		self		:      int):
								# fmt: off
								__lowerCamelCase    :    List[str] 	=			{'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.
								__lowerCamelCase    :    int 	=			[
								    '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=SCREAMING_SNAKE_CASE__       ,model_name='moussaKam/mbarthez'       ,revision='c2e4ecbca5e3cd2c37fe1ac285ca4fbdf1366fb6'       ,sequences=SCREAMING_SNAKE_CASE__       ,)







import os
import unittest

from huggingface_hub.utils import are_progress_bars_disabled

import transformers.models.bart.tokenization_bart
from transformers import logging
from transformers.testing_utils import CaptureLogger, mockenv, mockenv_context
from transformers.utils.logging import disable_progress_bar, enable_progress_bar






class 	A_		(	unittest.TestCase    ):
							def    lowerCAmelCase					(		self		:      Optional[int]):
								__lowerCamelCase    :    List[Any] 	=			logging.get_logger()

								# the current default level is logging.WARNING
								__lowerCamelCase    :    Dict 	=			logging.get_verbosity()

								logging.set_verbosity_error()
								self.assertEqual(logger.getEffectiveLevel()       ,logging.get_verbosity())

								logging.set_verbosity_warning()
								self.assertEqual(logger.getEffectiveLevel()       ,logging.get_verbosity())

								logging.set_verbosity_info()
								self.assertEqual(logger.getEffectiveLevel()       ,logging.get_verbosity())

								logging.set_verbosity_debug()
								self.assertEqual(logger.getEffectiveLevel()       ,logging.get_verbosity())

								# restore to the original level
								logging.set_verbosity(SCREAMING_SNAKE_CASE__)
							def    lowerCAmelCase					(		self		:      Optional[Any]):
								__lowerCamelCase    :    Optional[int] 	=			logging.get_verbosity()

								__lowerCamelCase    :    str 	=			logging.get_logger('transformers.models.bart.tokenization_bart')
								__lowerCamelCase    :    Tuple 	=			'Testing 1, 2, 3'

								# should be able to log warnings (if default settings weren't overridden by `pytest --log-level-all`)
								if level_origin <= logging.WARNING:
									with CaptureLogger(SCREAMING_SNAKE_CASE__) as cl:
										logger.warning(SCREAMING_SNAKE_CASE__)
									self.assertEqual(cl.out       ,msg + '\n')

								# this is setting the level for all of `transformers.*` loggers
								logging.set_verbosity_error()

								# should not be able to log warnings
								with CaptureLogger(SCREAMING_SNAKE_CASE__) as cl:
									logger.warning(SCREAMING_SNAKE_CASE__)
								self.assertEqual(cl.out       ,'')

								# should be able to log warnings again
								logging.set_verbosity_warning()
								with CaptureLogger(SCREAMING_SNAKE_CASE__) as cl:
									logger.warning(SCREAMING_SNAKE_CASE__)
								self.assertEqual(cl.out       ,msg + '\n')

								# restore to the original level
								logging.set_verbosity(SCREAMING_SNAKE_CASE__)
							@mockenv(TRANSFORMERS_VERBOSITY='error')
							def    lowerCAmelCase					(		self		:      Tuple):
								# reset for the env var to take effect, next time some logger call is made
								transformers.utils.logging._reset_library_root_logger()
								# this action activates the env var
								__lowerCamelCase    :    int 	=			logging.get_logger('transformers.models.bart.tokenization_bart')

								__lowerCamelCase    :    int 	=			os.getenv('TRANSFORMERS_VERBOSITY'       ,SCREAMING_SNAKE_CASE__)
								__lowerCamelCase    :    Optional[Any] 	=			logging.log_levels[env_level_str]

								__lowerCamelCase    :    Tuple 	=			logging.get_verbosity()
								self.assertEqual(
								    SCREAMING_SNAKE_CASE__       ,SCREAMING_SNAKE_CASE__       ,F"TRANSFORMERS_VERBOSITY={env_level_str}/{env_level}, but internal verbosity is {current_level}"       ,)

								# restore to the original level
								__lowerCamelCase    :    List[str] 	=			''
								transformers.utils.logging._reset_library_root_logger()
							@mockenv(TRANSFORMERS_VERBOSITY='super-error')
							def    lowerCAmelCase					(		self		:      List[Any]):
								# reset for the env var to take effect, next time some logger call is made
								transformers.utils.logging._reset_library_root_logger()
								__lowerCamelCase    :    List[str] 	=			logging.logging.getLogger()
								with CaptureLogger(SCREAMING_SNAKE_CASE__) as cl:
									# this action activates the env var
									logging.get_logger('transformers.models.bart.tokenization_bart')
								self.assertIn('Unknown option TRANSFORMERS_VERBOSITY=super-error'       ,cl.out)

								# no need to restore as nothing was changed


							def    lowerCAmelCase					(		self		:      Any):
								# testing `logger.warning_advice()`
								transformers.utils.logging._reset_library_root_logger()

								__lowerCamelCase    :    Tuple 	=			logging.get_logger('transformers.models.bart.tokenization_bart')
								__lowerCamelCase    :    Optional[int] 	=			'Testing 1, 2, 3'

								with mockenv_context(TRANSFORMERS_NO_ADVISORY_WARNINGS='1'):
									# nothing should be logged as env var disables this method
									with CaptureLogger(SCREAMING_SNAKE_CASE__) as cl:
										logger.warning_advice(SCREAMING_SNAKE_CASE__)
									self.assertEqual(cl.out       ,'')

								with mockenv_context(TRANSFORMERS_NO_ADVISORY_WARNINGS=''):
									# should log normally as TRANSFORMERS_NO_ADVISORY_WARNINGS is unset
									with CaptureLogger(SCREAMING_SNAKE_CASE__) as cl:
										logger.warning_advice(SCREAMING_SNAKE_CASE__)
									self.assertEqual(cl.out       ,msg + '\n')






def        SCREAMING_SNAKE_CASE__	(  )  ->					Any:
	disable_progress_bar()
	assert are_progress_bars_disabled()

	enable_progress_bar()
	assert not are_progress_bars_disabled()




