



from math import pi, sqrt






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






def  UpperCAmelCase__    (    ) ->      None:
						assert gamma(0.5   ) == sqrt(lowercase__   )
						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...")










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


UpperCamelCase__ =						{
    "configuration_ctrl": ["CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP", "CTRLConfig"],
    "tokenization_ctrl": ["CTRLTokenizer"],
}

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

try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			UpperCamelCase__ =						[
			    "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

			UpperCamelCase__ =						_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





