



'''simple docstring'''





from math import pi, sqrt

def 			a_	(				_lowerCAmelCase			) -> float:
  if num <= 0:
    raise ValueError('math domain error'			)
  if num > 171.5:
    raise OverflowError('math range error'			)
  elif num - int(_lowerCAmelCase			) not in (0, 0.5):
    raise NotImplementedError('num must be an integer or a half-integer'			)
  elif num == 0.5:
    return sqrt(_lowerCAmelCase			)
  else:
    return 1.0 if num == 1 else (num - 1) * gamma(num - 1			)

def 			a_	(				) -> None:
  assert gamma(0.5			) == sqrt(_lowerCAmelCase			)
  assert gamma(1			) == 1.0
  assert gamma(2			) == 1.0


if __name__ == "__main__":
   from doctest import testmod

   testmod()
   _UpperCamelCase											=		1.0
   while num:
      _UpperCamelCase											=		float(input('Gamma of: '))
      print(f'''gamma({num}) = {gamma(num)}''')
      print('\nEnter 0 to exit...')











'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_UpperCamelCase											=		{'configuration_ibert': ['IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'IBertConfig', 'IBertOnnxConfig']}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _UpperCamelCase											=		[
       'IBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
       'IBertForMaskedLM',
       'IBertForMultipleChoice',
       'IBertForQuestionAnswering',
       'IBertForSequenceClassification',
       'IBertForTokenClassification',
       'IBertModel',
       'IBertPreTrainedModel',
   ]

if TYPE_CHECKING:
   from .configuration_ibert import IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, IBertConfig, IBertOnnxConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_ibert import (
          IBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
          IBertForMaskedLM,
          IBertForMultipleChoice,
          IBertForQuestionAnswering,
          IBertForSequenceClassification,
          IBertForTokenClassification,
          IBertModel,
          IBertPreTrainedModel,
      )

else:
   import sys

   _UpperCamelCase											=		_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






