


"""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 _lowerCAmelCase				(      unittest.TestCase	):







   def  lowerCamelCase		(	self						)	->		Tuple:

       '''simple docstring'''




       snake_case    :      List[str]      					=    logging.get_logger()

       # the current default level is logging.WARNING
       snake_case    :      str      					=    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						)	->		Dict:

       '''simple docstring'''




       snake_case    :      Dict      					=    logging.get_verbosity()

       snake_case    :      List[str]      					=    logging.get_logger("transformers.models.bart.tokenization_bart"						)
       snake_case    :      Dict      					=    '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						)	->		Union[str, Any]:

       '''simple docstring'''




       transformers.utils.logging._reset_library_root_logger()
       # this action activates the env var
       snake_case    :      List[str]      					=    logging.get_logger("transformers.models.bart.tokenization_bart"						)

       snake_case    :      Tuple      					=    os.getenv("TRANSFORMERS_VERBOSITY"						,	_UpperCamelCase						)
       snake_case    :      List[str]      					=    logging.log_levels[env_level_str]

       snake_case    :      Dict      					=    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
       snake_case    :      Tuple      					=    ''
       transformers.utils.logging._reset_library_root_logger()







   @mockenv(TRANSFORMERS_VERBOSITY="super-error"						)
   def  lowerCamelCase		(	self						)	->		List[Any]:

       '''simple docstring'''




       transformers.utils.logging._reset_library_root_logger()
       snake_case    :      Any      					=    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						)	->		Union[str, Any]:

       '''simple docstring'''




       transformers.utils.logging._reset_library_root_logger()

       snake_case    :      Optional[Any]      					=    logging.get_logger("transformers.models.bart.tokenization_bart"						)
       snake_case    :      Dict      					=    '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   __lowerCAmelCase						(						)	->						List[Any]:


    """simple docstring"""





    disable_progress_bar()
    assert are_progress_bars_disabled()

    enable_progress_bar()
    assert not are_progress_bars_disabled()













from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__UpperCAmelCase								=						{
    'configuration_time_series_transformer': [
        'TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'TimeSeriesTransformerConfig',
    ],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__UpperCAmelCase								=						[
		    'TIME_SERIES_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'TimeSeriesTransformerForPrediction',
		    'TimeSeriesTransformerModel',
		    'TimeSeriesTransformerPreTrainedModel',
		]


if TYPE_CHECKING:
		from .configuration_time_series_transformer import (
		    TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    TimeSeriesTransformerConfig,
		)

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_time_series_transformer import (
				    TIME_SERIES_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TimeSeriesTransformerForPrediction,
				    TimeSeriesTransformerModel,
				    TimeSeriesTransformerPreTrainedModel,
				)

else:
		import sys

		__UpperCAmelCase								=						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






