




'''simple docstring'''



from math import pi, sqrt
def 			SCREAMING_SNAKE_CASE_			(							__A    :			float  )			->			Union[str, Any]:
   if num <= 0:
      raise ValueError("math domain error"  )
   if num > 1_71.5:
      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 			SCREAMING_SNAKE_CASE_			(							)			->			Any:
   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()
 lowerCamelCase_			=						1.0
 while num:
  lowerCamelCase_			=						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_tf_available, is_torch_available


lowerCamelCase_			=						{
    'configuration_ctrl': ['CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CTRLConfig'],
    'tokenization_ctrl': ['CTRLTokenizer'],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase_			=						[
     'CTRL_PRETRAINED_MODEL_ARCHIVE_LIST',
     'CTRLForSequenceClassification',
     'CTRLLMHeadModel',
     'CTRLModel',
     'CTRLPreTrainedModel',
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase_			=						[
     'TF_CTRL_PRETRAINED_MODEL_ARCHIVE_LIST',
     'TFCTRLForSequenceClassification',
     'TFCTRLLMHeadModel',
     'TFCTRLModel',
     'TFCTRLPreTrainedModel',
 ]


if TYPE_CHECKING:
 from .configuration_ctrl import CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP, CTRLConfig
 from .tokenization_ctrl import CTRLTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_ctrl import (
      CTRL_PRETRAINED_MODEL_ARCHIVE_LIST,
      CTRLForSequenceClassification,
      CTRLLMHeadModel,
      CTRLModel,
      CTRLPreTrainedModel,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_ctrl import (
      TF_CTRL_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFCTRLForSequenceClassification,
      TFCTRLLMHeadModel,
      TFCTRLModel,
      TFCTRLPreTrainedModel,
  )

else:
 import sys

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

