
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 				_SCREAMING_SNAKE_CASE   (self		:					Optional[int] )		->	Tuple:


          '''simple docstring'''


          snake_case       :   Tuple							=      logging.get_logger()

          # the current default level is logging.WARNING
          snake_case       :   Optional[int]							=      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(snake_case__ )



   def 				_SCREAMING_SNAKE_CASE   (self		:					Tuple )		->	Optional[Any]:


          '''simple docstring'''


          snake_case       :   List[Any]							=      logging.get_verbosity()

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

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

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



   @mockenv(TRANSFORMERS_VERBOSITY="error" )
   def 				_SCREAMING_SNAKE_CASE   (self		:					Dict )		->	Dict:


          '''simple docstring'''


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

          snake_case       :   Dict							=      os.getenv("TRANSFORMERS_VERBOSITY"    ,						snake_case__ )
          snake_case       :   Any							=      logging.log_levels[env_level_str]

          snake_case       :   List[str]							=      logging.get_verbosity()
          self.assertEqual(
              snake_case__    ,						snake_case__    ,						f"""TRANSFORMERS_VERBOSITY={env_level_str}/{env_level}, but internal verbosity is {current_level}"""    ,						)

          # restore to the original level
          snake_case       :   Union[str, Any]							=      ""
          transformers.utils.logging._reset_library_root_logger()



   @mockenv(TRANSFORMERS_VERBOSITY="super-error" )
   def 				_SCREAMING_SNAKE_CASE   (self		:					Dict )		->	Tuple:


          '''simple docstring'''


          transformers.utils.logging._reset_library_root_logger()
          snake_case       :   Union[str, Any]							=      logging.logging.getLogger()
          with CaptureLogger(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 				_SCREAMING_SNAKE_CASE   (self		:					Union[str, Any] )		->	Optional[int]:


          '''simple docstring'''


          transformers.utils.logging._reset_library_root_logger()

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

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



def 			UpperCamelCase					(    ):
       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_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


__lowerCamelCase							=       {"""configuration_xglm""": ["""XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """XGLMConfig"""]}

try:
   if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase							=       ["""XGLMTokenizer"""]

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase							=       ["""XGLMTokenizerFast"""]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase							=       [
       """XGLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """XGLMForCausalLM""",
       """XGLMModel""",
       """XGLMPreTrainedModel""",
   ]


try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase							=       [
       """FlaxXGLMForCausalLM""",
       """FlaxXGLMModel""",
       """FlaxXGLMPreTrainedModel""",
   ]


try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   __lowerCamelCase							=       [
       """TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """TFXGLMForCausalLM""",
       """TFXGLMModel""",
       """TFXGLMPreTrainedModel""",
   ]


if TYPE_CHECKING:
   from .configuration_xglm import XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP, XGLMConfig

   try:
      if not is_sentencepiece_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_xglm import XGLMTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_xglm_fast import XGLMTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_xglm import XGLM_PRETRAINED_MODEL_ARCHIVE_LIST, XGLMForCausalLM, XGLMModel, XGLMPreTrainedModel

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_xglm import FlaxXGLMForCausalLM, FlaxXGLMModel, FlaxXGLMPreTrainedModel

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_xglm import (
          TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFXGLMForCausalLM,
          TFXGLMModel,
          TFXGLMPreTrainedModel,
      )


else:
   import sys

   __lowerCamelCase							=       _LazyModule(__name__, globals()["""__file__"""], _import_structure)





