code: 
  
  
  """simple docstring"""
  
  
  
  
  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,
  )
  
  
  __magic_name__	:   Union[str, Any]          =							{
      'configuration_big_bird': ['BIG_BIRD_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BigBirdConfig', 'BigBirdOnnxConfig'],
  }
  
  try:
  					if not is_sentencepiece_available():
  										raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  					pass
  else:
  					__magic_name__	:   Optional[Any]          =							['BigBirdTokenizer']
  
  try:
  					if not is_tokenizers_available():
  										raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  					pass
  else:
  					__magic_name__	:   str          =							['BigBirdTokenizerFast']
  
  try:
  					if not is_torch_available():
  										raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  					pass
  else:
  					__magic_name__	:   str          =							[
  					    'BIG_BIRD_PRETRAINED_MODEL_ARCHIVE_LIST',
  					    'BigBirdForCausalLM',
  					    'BigBirdForMaskedLM',
  					    'BigBirdForMultipleChoice',
  					    'BigBirdForPreTraining',
  					    'BigBirdForQuestionAnswering',
  					    'BigBirdForSequenceClassification',
  					    'BigBirdForTokenClassification',
  					    'BigBirdLayer',
  					    'BigBirdModel',
  					    'BigBirdPreTrainedModel',
  					    'load_tf_weights_in_big_bird',
  					]
  
  try:
  					if not is_flax_available():
  										raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  					pass
  else:
  					__magic_name__	:   Dict          =							[
  					    'FlaxBigBirdForCausalLM',
  					    'FlaxBigBirdForMaskedLM',
  					    'FlaxBigBirdForMultipleChoice',
  					    'FlaxBigBirdForPreTraining',
  					    'FlaxBigBirdForQuestionAnswering',
  					    'FlaxBigBirdForSequenceClassification',
  					    'FlaxBigBirdForTokenClassification',
  					    'FlaxBigBirdModel',
  					    'FlaxBigBirdPreTrainedModel',
  					]
  
  if TYPE_CHECKING:
  					from .configuration_big_bird import BIG_BIRD_PRETRAINED_CONFIG_ARCHIVE_MAP, BigBirdConfig, BigBirdOnnxConfig
  
  					try:
  										if not is_sentencepiece_available():
  															raise OptionalDependencyNotAvailable()
  					except OptionalDependencyNotAvailable:
  										pass
  					else:
  										from .tokenization_big_bird import BigBirdTokenizer
  
  					try:
  										if not is_tokenizers_available():
  															raise OptionalDependencyNotAvailable()
  					except OptionalDependencyNotAvailable:
  										pass
  					else:
  										from .tokenization_big_bird_fast import BigBirdTokenizerFast
  
  					try:
  										if not is_torch_available():
  															raise OptionalDependencyNotAvailable()
  					except OptionalDependencyNotAvailable:
  										pass
  					else:
  										from .modeling_big_bird import (
  										    BIG_BIRD_PRETRAINED_MODEL_ARCHIVE_LIST,
  										    BigBirdForCausalLM,
  										    BigBirdForMaskedLM,
  										    BigBirdForMultipleChoice,
  										    BigBirdForPreTraining,
  										    BigBirdForQuestionAnswering,
  										    BigBirdForSequenceClassification,
  										    BigBirdForTokenClassification,
  										    BigBirdLayer,
  										    BigBirdModel,
  										    BigBirdPreTrainedModel,
  										    load_tf_weights_in_big_bird,
  										)
  
  					try:
  										if not is_flax_available():
  															raise OptionalDependencyNotAvailable()
  					except OptionalDependencyNotAvailable:
  										pass
  					else:
  										from .modeling_flax_big_bird import (
  										    FlaxBigBirdForCausalLM,
  										    FlaxBigBirdForMaskedLM,
  										    FlaxBigBirdForMultipleChoice,
  										    FlaxBigBirdForPreTraining,
  										    FlaxBigBirdForQuestionAnswering,
  										    FlaxBigBirdForSequenceClassification,
  										    FlaxBigBirdForTokenClassification,
  										    FlaxBigBirdModel,
  										    FlaxBigBirdPreTrainedModel,
  										)
  
  else:
  					import sys
  
  					__magic_name__	:   Any          =							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
  
  
  
  
  
style_context: 
  
  
  """simple docstring"""
  
  
  
  
  from __future__ import annotations
  
  import re
  
  
  
  
  
  def 			a_   (  lowercase__   :list[str]    ):
  
  			def alphanum_key(lowercase__   :int    ):
  						return [int(lowercase__    ) if s.isdigit() else s.lower() for s in re.split("""([0-9]+)""", lowercase__    )]
  
  			return sorted(lowercase__, key=lowercase__    )
  
  
  if __name__ == "__main__":
  					import doctest
  
  					doctest.testmod()
  
  
  
  
  