


"""simple docstring"""







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


__a      			= {
    "configuration_led": ["LED_PRETRAINED_CONFIG_ARCHIVE_MAP", "LEDConfig"],
    "tokenization_led": ["LEDTokenizer"],
}

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a      			= ["LEDTokenizerFast"]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a      			= [
						    "LED_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "LEDForConditionalGeneration",
						    "LEDForQuestionAnswering",
						    "LEDForSequenceClassification",
						    "LEDModel",
						    "LEDPreTrainedModel",
						]


try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a      			= ["TFLEDForConditionalGeneration", "TFLEDModel", "TFLEDPreTrainedModel"]


if TYPE_CHECKING:
						from .configuration_led import LED_PRETRAINED_CONFIG_ARCHIVE_MAP, LEDConfig
						from .tokenization_led import LEDTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_led_fast import LEDTokenizerFast

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_led import (
												    LED_PRETRAINED_MODEL_ARCHIVE_LIST,
												    LEDForConditionalGeneration,
												    LEDForQuestionAnswering,
												    LEDForSequenceClassification,
												    LEDModel,
												    LEDPreTrainedModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_led import TFLEDForConditionalGeneration, TFLEDModel, TFLEDPreTrainedModel

else:
						import sys

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



"""simple docstring"""







def        a__			(							_UpperCamelCase						,      _UpperCamelCase = 2			):





						"""simple docstring"""

						return round((float(_UpperCamelCase			) * 9 / 5) + 32						,      _UpperCamelCase			)






def        a__			(							_UpperCamelCase						,      _UpperCamelCase = 2			):





						"""simple docstring"""

						return round(float(_UpperCamelCase			) + 273.15						,      _UpperCamelCase			)






def        a__			(							_UpperCamelCase						,      _UpperCamelCase = 2			):





						"""simple docstring"""

						return round((float(_UpperCamelCase			) * 9 / 5) + 491.67						,      _UpperCamelCase			)






def        a__			(							_UpperCamelCase						,      _UpperCamelCase = 2			):





						"""simple docstring"""

						return round((float(_UpperCamelCase			) - 32) * 5 / 9						,      _UpperCamelCase			)






def        a__			(							_UpperCamelCase						,      _UpperCamelCase = 2			):





						"""simple docstring"""

						return round(((float(_UpperCamelCase			) - 32) * 5 / 9) + 273.15						,      _UpperCamelCase			)






def        a__			(							_UpperCamelCase						,      _UpperCamelCase = 2			):





						"""simple docstring"""

						return round(float(_UpperCamelCase			) + 459.67						,      _UpperCamelCase			)






def        a__			(							_UpperCamelCase						,      _UpperCamelCase = 2			):





						"""simple docstring"""

						return round(float(_UpperCamelCase			) - 273.15						,      _UpperCamelCase			)






def        a__			(							_UpperCamelCase						,      _UpperCamelCase = 2			):





						"""simple docstring"""

						return round(((float(_UpperCamelCase			) - 273.15) * 9 / 5) + 32						,      _UpperCamelCase			)






def        a__			(							_UpperCamelCase						,      _UpperCamelCase = 2			):





						"""simple docstring"""

						return round((float(_UpperCamelCase			) * 9 / 5)						,      _UpperCamelCase			)






def        a__			(							_UpperCamelCase						,      _UpperCamelCase = 2			):





						"""simple docstring"""

						return round((float(_UpperCamelCase			) - 491.67) * 5 / 9						,      _UpperCamelCase			)






def        a__			(							_UpperCamelCase						,      _UpperCamelCase = 2			):





						"""simple docstring"""

						return round(float(_UpperCamelCase			) - 459.67						,      _UpperCamelCase			)






def        a__			(							_UpperCamelCase						,      _UpperCamelCase = 2			):





						"""simple docstring"""

						return round((float(_UpperCamelCase			) * 5 / 9)						,      _UpperCamelCase			)






def        a__			(							_UpperCamelCase						,      _UpperCamelCase = 2			):





						"""simple docstring"""

						return round((float(_UpperCamelCase			) * 1.25 + 273.15)						,      _UpperCamelCase			)






def        a__			(							_UpperCamelCase						,      _UpperCamelCase = 2			):





						"""simple docstring"""

						return round((float(_UpperCamelCase			) * 2.25 + 32)						,      _UpperCamelCase			)






def        a__			(							_UpperCamelCase						,      _UpperCamelCase = 2			):





						"""simple docstring"""

						return round((float(_UpperCamelCase			) * 1.25)						,      _UpperCamelCase			)






def        a__			(							_UpperCamelCase						,      _UpperCamelCase = 2			):





						"""simple docstring"""

						return round((float(_UpperCamelCase			) * 2.25 + 32 + 459.67)						,      _UpperCamelCase			)


if __name__ == "__main__":
						import doctest

						doctest.testmod()