





"""simple docstring"""
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 					_UpperCAmelCase   (	unittest.TestCase ):


					def 	lowerCamelCase       (					self			:List[str]		):
												A		=  logging.get_logger()

												# the current default level is logging.WARNING
												A		=  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(__UpperCamelCase		)


					def 	lowerCamelCase       (					self			:int		):
												A		=  logging.get_verbosity()

												A		=  logging.get_logger("transformers.models.bart.tokenization_bart"		)
												A		=  "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(__UpperCamelCase		) as cl:
																										logger.warning(__UpperCamelCase		)
																			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(__UpperCamelCase		) as cl:
																			logger.warning(__UpperCamelCase		)
												self.assertEqual(cl.out     ,       ""		)

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

												# restore to the original level
												logging.set_verbosity(__UpperCamelCase		)


					@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
												A		=  logging.get_logger("transformers.models.bart.tokenization_bart"		)

												A		=  os.getenv("TRANSFORMERS_VERBOSITY"     ,       __UpperCamelCase		)
												A		=  logging.log_levels[env_level_str]

												A		=  logging.get_verbosity()
												self.assertEqual(
												    __UpperCamelCase     ,       __UpperCamelCase     ,       f"TRANSFORMERS_VERBOSITY={env_level_str}/{env_level}, but internal verbosity is {current_level}"     ,       )

												# restore to the original level
												A		=  ""
												transformers.utils.logging._reset_library_root_logger()


					@mockenv(TRANSFORMERS_VERBOSITY="super-error"		)
					def 	lowerCamelCase       (					self			:Union[str, Any]		):
												# reset for the env var to take effect, next time some logger call is made
												transformers.utils.logging._reset_library_root_logger()
												A		=  logging.logging.getLogger()
												with CaptureLogger(__UpperCamelCase		) 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			:Dict		):
												# testing `logger.warning_advice()`
												transformers.utils.logging._reset_library_root_logger()

												A		=  logging.get_logger("transformers.models.bart.tokenization_bart"		)
												A		=  "Testing 1, 2, 3"

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

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







def 					A__				(			):
							disable_progress_bar()
							assert are_progress_bars_disabled()

							enable_progress_bar()
							assert not are_progress_bars_disabled()









"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


_snake_case     :		Union[str, Any]       						= {
    'configuration_encodec': [
        'ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'EncodecConfig',
    ],
    'feature_extraction_encodec': ['EncodecFeatureExtractor'],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_snake_case     :		int       						= [
		    'ENCODEC_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'EncodecModel',
		    'EncodecPreTrainedModel',
		]

if TYPE_CHECKING:
		from .configuration_encodec import (
		    ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    EncodecConfig,
		)
		from .feature_extraction_encodec import EncodecFeatureExtractor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_encodec import (
				    ENCODEC_PRETRAINED_MODEL_ARCHIVE_LIST,
				    EncodecModel,
				    EncodecPreTrainedModel,
				)

else:
		import sys

		_snake_case     :		str       						= _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


