'''simple docstring'''




from math import pi, sqrt

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

def _UpperCamelCase   (       ):
     assert gamma(0.5							) == sqrt(SCREAMING_SNAKE_CASE_							)
     assert gamma(1							) == 1.0
     assert gamma(2							) == 1.0


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

 testmod()
 _A								=   1.0
 while num:
  _A								=   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


_A								=   {
    'configuration_bigbird_pegasus': [
        'BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'BigBirdPegasusConfig',
        'BigBirdPegasusOnnxConfig',
    ],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _A								=   [
     'BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST',
     'BigBirdPegasusForCausalLM',
     'BigBirdPegasusForConditionalGeneration',
     'BigBirdPegasusForQuestionAnswering',
     'BigBirdPegasusForSequenceClassification',
     'BigBirdPegasusModel',
     'BigBirdPegasusPreTrainedModel',
 ]


if TYPE_CHECKING:
 from .configuration_bigbird_pegasus import (
     BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP,
     BigBirdPegasusConfig,
     BigBirdPegasusOnnxConfig,
 )

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_bigbird_pegasus import (
      BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST,
      BigBirdPegasusForCausalLM,
      BigBirdPegasusForConditionalGeneration,
      BigBirdPegasusForQuestionAnswering,
      BigBirdPegasusForSequenceClassification,
      BigBirdPegasusModel,
      BigBirdPegasusPreTrainedModel,
  )


else:
 import sys

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




