


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


SCREAMING_SNAKE_CASE			: Any				   =					{
    "configuration_xlm_roberta_xl": [
        "XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "XLMRobertaXLConfig",
        "XLMRobertaXLOnnxConfig",
    ],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE			: List[str]				   =					[
     "XLM_ROBERTA_XL_PRETRAINED_MODEL_ARCHIVE_LIST",
     "XLMRobertaXLForCausalLM",
     "XLMRobertaXLForMaskedLM",
     "XLMRobertaXLForMultipleChoice",
     "XLMRobertaXLForQuestionAnswering",
     "XLMRobertaXLForSequenceClassification",
     "XLMRobertaXLForTokenClassification",
     "XLMRobertaXLModel",
     "XLMRobertaXLPreTrainedModel",
 ]

if TYPE_CHECKING:
 from .configuration_xlm_roberta_xl import (
     XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP,
     XLMRobertaXLConfig,
     XLMRobertaXLOnnxConfig,
 )

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_xlm_roberta_xl import (
      XLM_ROBERTA_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
      XLMRobertaXLForCausalLM,
      XLMRobertaXLForMaskedLM,
      XLMRobertaXLForMultipleChoice,
      XLMRobertaXLForQuestionAnswering,
      XLMRobertaXLForSequenceClassification,
      XLMRobertaXLForTokenClassification,
      XLMRobertaXLModel,
      XLMRobertaXLPreTrainedModel,
  )

else:
 import sys

 SCREAMING_SNAKE_CASE			: Dict				   =					_LazyModule(__name__, globals()["__file__"], _import_structure)






from __future__ import annotations

from math import pi

# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
SCREAMING_SNAKE_CASE			: Union[str, Any]				   =					1.0_5457_1817E-34  # unit of ℏ : J * s

SCREAMING_SNAKE_CASE			: int				   =					3E8  # unit of c : m * s^-1



def 							UpperCamelCase_( lowerCamelCase_				,					lowerCamelCase_				,					lowerCamelCase_					)       ->		dict[str, float]:

    if (force, area, distance).count(0					) != 1:
        raise ValueError('One and only one argument must be 0'					)
    if force < 0:
        raise ValueError('Magnitude of force can not be negative'					)
    if distance < 0:
        raise ValueError('Distance can not be negative'					)
    if area < 0:
        raise ValueError('Area can not be negative'					)
    if force == 0:
        _lowercase			:				int 						=						(REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2 * area) / (
            240 * (distance) ** 4
        )
        return {"force": force}
    elif area == 0:
        _lowercase			:				List[Any] 						=						(240 * force * (distance) ** 4) / (
            REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2
        )
        return {"area": area}
    elif distance == 0:
        _lowercase			:				List[Any] 						=						(
            (REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2 * area) / (240 * force)
        ) ** (1 / 4)
        return {"distance": distance}
    raise ValueError('One and only one argument must be 0'					)


# Run doctest
if __name__ == "__main__":
 import doctest

 doctest.testmod()


