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,
  )
  
  
  _a	 =							{
      'configuration_big_bird': ['BIG_BIRD_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BigBirdConfig', 'BigBirdOnnxConfig'],
  }
  
  try:
  				if not is_sentencepiece_available():
  								raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  				pass
  else:
  				_a	 =							['BigBirdTokenizer']
  
  try:
  				if not is_tokenizers_available():
  								raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  				pass
  else:
  				_a	 =							['BigBirdTokenizerFast']
  
  try:
  				if not is_torch_available():
  								raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  				pass
  else:
  				_a	 =							[
  				    '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:
  				_a	 =							[
  				    '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
  
  				_a	 =							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
  
  
  
style_context: 
  """simple docstring"""
  
  
  
  
  
  from .hash_table import HashTable
  
  
  class A_			(lowercase__   ):
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    def __init__(	self       ,     *lowercase_       ,     **lowercase_						):
  
       """simple docstring"""
       super().__init__(*lowercase_       ,     **lowercase_						)
  
  
  
  
  
  
  
    def  UpperCamelCase__      (	self       ,     lowercase_       ,     lowercase_=None						):
  
       """simple docstring"""
       UpperCAmelCase_      :      Tuple      =					1
       UpperCAmelCase_      :      List[str]      =					self.hash_function(key + i * i						)
  
       while self.values[new_key] is not None and self.values[new_key] != key:
          i += 1
          UpperCAmelCase_      :      List[Any]      =					(
              self.hash_function(key + i * i						)
              if not self.balanced_factor() >= self.lim_charge
              else None
          )
  
          if new_key is None:
             break
  
       return new_key
  
  
  