

'''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   _SCREAMING_SNAKE_CASE   (   unittest.TestCase     ):



 def 			snake_case__  (   self		:   Tuple      ):
      __magic_name__						       =    logging.get_logger()

      # the current default level is logging.WARNING
      __magic_name__						       =    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(lowerCAmelCase__      )



 def 			snake_case__  (   self		:   Optional[Any]      ):
      __magic_name__						       =    logging.get_verbosity()

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

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

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



 @mockenv(TRANSFORMERS_VERBOSITY='''error'''      )
 def 			snake_case__  (   self		:   int      ):
      transformers.utils.logging._reset_library_root_logger()
      # this action activates the env var
      __magic_name__						       =    logging.get_logger('''transformers.models.bart.tokenization_bart'''      )

      __magic_name__						       =    os.getenv('''TRANSFORMERS_VERBOSITY'''			,				lowerCAmelCase__      )
      __magic_name__						       =    logging.log_levels[env_level_str]

      __magic_name__						       =    logging.get_verbosity()
      self.assertEqual(
          lowerCAmelCase__			,				lowerCAmelCase__			,				F'''TRANSFORMERS_VERBOSITY={env_level_str}/{env_level}, but internal verbosity is {current_level}'''			,				)

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



 @mockenv(TRANSFORMERS_VERBOSITY='''super-error'''      )
 def 			snake_case__  (   self		:   int      ):
      transformers.utils.logging._reset_library_root_logger()
      __magic_name__						       =    logging.logging.getLogger()
      with CaptureLogger(lowerCAmelCase__      ) 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 			snake_case__  (   self		:   str      ):
      transformers.utils.logging._reset_library_root_logger()

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

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

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




def 						UpperCamelCase	(			)				->     Optional[Any]:






     '''simple docstring'''
     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, is_vision_available


_lowerCAmelCase         =						{"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      _lowerCAmelCase         =						["GLPNFeatureExtractor"]
      _lowerCAmelCase         =						["GLPNImageProcessor"]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      _lowerCAmelCase         =						[
          "GLPN_PRETRAINED_MODEL_ARCHIVE_LIST",
          "GLPNForDepthEstimation",
          "GLPNLayer",
          "GLPNModel",
          "GLPNPreTrainedModel",
      ]


if TYPE_CHECKING:
      from .configuration_glpn import GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP, GLPNConfig

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_glpn import GLPNFeatureExtractor
            from .image_processing_glpn import GLPNImageProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_glpn import (
                GLPN_PRETRAINED_MODEL_ARCHIVE_LIST,
                GLPNForDepthEstimation,
                GLPNLayer,
                GLPNModel,
                GLPNPreTrainedModel,
            )


else:
      import sys

      _lowerCAmelCase         =						_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)






