code: 
  
  """simple docstring"""
  
  
  
  
  def      __SCREAMING_SNAKE_CASE		(		lowercase__   ):
  					"""simple docstring"""
  
  
  
  
  
  
  
  					if not isinstance(lowercase__    ,							lowercase__   ):
  										raise ValueError("double_factorial() only accepts integral values"   )
  					if n < 0:
  										raise ValueError("double_factorial() not defined for negative values"   )
  					return 1 if n <= 1 else n * double_factorial(n - 2   )
  
  
  if __name__ == "__main__":
  	import doctest
  
  	doctest.testmod()
  
  
  
  
  
  
style_context: 
  
  """simple docstring"""
  
  
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
  
  
  __A  :					int												=	{
      'configuration_nystromformer': ['NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'NystromformerConfig'],
  }
  
  try:
  	if not is_torch_available():
  		raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  	pass
  else:
  	__A  :					Any												=	[
  	    'NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
  	    'NystromformerForMaskedLM',
  	    'NystromformerForMultipleChoice',
  	    'NystromformerForQuestionAnswering',
  	    'NystromformerForSequenceClassification',
  	    'NystromformerForTokenClassification',
  	    'NystromformerLayer',
  	    'NystromformerModel',
  	    'NystromformerPreTrainedModel',
  	]
  
  
  if TYPE_CHECKING:
  	from .configuration_nystromformer import NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, NystromformerConfig
  
  	try:
  		if not is_torch_available():
  			raise OptionalDependencyNotAvailable()
  	except OptionalDependencyNotAvailable:
  		pass
  	else:
  		from .modeling_nystromformer import (
  		    NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
  		    NystromformerForMaskedLM,
  		    NystromformerForMultipleChoice,
  		    NystromformerForQuestionAnswering,
  		    NystromformerForSequenceClassification,
  		    NystromformerForTokenClassification,
  		    NystromformerLayer,
  		    NystromformerModel,
  		    NystromformerPreTrainedModel,
  		)
  
  
  else:
  	import sys
  
  	__A  :					Optional[Any]												=	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
  
  
  
  
  
  