

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    ):


     '''simple docstring'''






     def   __A      (			self      ):
      A__							:   Optional[int]					       =		logging.get_logger()

      # the current default level is logging.WARNING
      A__							:   List[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(A__      )






     def   __A      (			self      ):
      A__							:   List[Any]					       =		logging.get_verbosity()

      A__							:   List[Any]					       =		logging.get_logger("""transformers.models.bart.tokenization_bart"""      )
      A__							:   Optional[Any]					       =		"""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(A__      ) as cl:
        logger.warning(A__      )
       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(A__      ) as cl:
       logger.warning(A__      )
      self.assertEqual(cl.out   ,	""""""      )

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

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






     @mockenv(TRANSFORMERS_VERBOSITY="""error"""      )
     def   __A      (			self      ):
      # 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__							:   Optional[Any]					       =		logging.get_logger("""transformers.models.bart.tokenization_bart"""      )

      A__							:   List[Any]					       =		os.getenv("""TRANSFORMERS_VERBOSITY"""   ,	A__      )
      A__							:   Optional[Any]					       =		logging.log_levels[env_level_str]

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

      # restore to the original level
      A__							:   Any					       =		""""""
      transformers.utils.logging._reset_library_root_logger()






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

      A__							:   Union[str, Any]					       =		logging.get_logger("""transformers.models.bart.tokenization_bart"""      )
      A__							:   Optional[Any]					       =		"""Testing 1, 2, 3"""

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

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



def 						UpperCamelCase ()					->				Union[str, Any]:
 disable_progress_bar()
 assert are_progress_bars_disabled()

 enable_progress_bar()
 assert not are_progress_bars_disabled()






from argparse import ArgumentParser

from . import BaseTransformersCLICommand

def 						UpperCamelCase (lowercase_:			int )					->				str:
	return DownloadCommand(args.model   ,				args.cache_dir   ,				args.force   ,				args.trust_remote_code )



class    _a						(__magic_name__    ):


					'''simple docstring'''






					@staticmethod
					def   __A      (			A__      ):
						A__							:   Any					       =		parser.add_parser("""download"""      )
						download_parser.add_argument(
						    """--cache-dir"""   ,	type=A__   ,	default=A__   ,	help="""Path to location to store the models"""      )
						download_parser.add_argument(
						    """--force"""   ,	action="""store_true"""   ,	help="""Force the model to be download even if already in cache-dir"""      )
						download_parser.add_argument(
						    """--trust-remote-code"""   ,	action="""store_true"""   ,	help="""Whether or not to allow for custom models defined on the Hub in their own modeling files. Use only if you've reviewed the code as it will execute on your local machine"""   ,	)
						download_parser.add_argument("""model"""   ,	type=A__   ,	help="""Name of the model to download"""      )
						download_parser.set_defaults(func=A__      )






					def __init__(			self   ,	A__   ,	A__   ,	A__   ,	A__      ):
						A__							:   Union[str, Any]					       =		model
						A__							:   Dict					       =		cache
						A__							:   str					       =		force
						A__							:   Tuple					       =		trust_remote_code






					def   __A      (			self      ):
						from ..models.auto import AutoModel, AutoTokenizer

						AutoModel.from_pretrained(
						    self._model   ,	cache_dir=self._cache   ,	force_download=self._force   ,	trust_remote_code=self._trust_remote_code      )
						AutoTokenizer.from_pretrained(
						    self._model   ,	cache_dir=self._cache   ,	force_download=self._force   ,	trust_remote_code=self._trust_remote_code      )



