






"""simple docstring"""





from __future__ import annotations

# Define the Gravitational Constant G and the function
UpperCamelCase					=     6.67_43e-11  # unit of G : m^3 * kg^-1 * s^-2






def 							A(    snake_case_		,  snake_case_		,  snake_case_		,  snake_case_						):
       """simple docstring"""





       lowercase__:							List[Any]         =     mass_a * mass_a

       if (force, mass_a, mass_a, distance).count(0						) != 1:
              raise ValueError("One and only one argument must be 0"						)
       if force < 0:
              raise ValueError("Gravitational force can not be negative"						)
       if distance < 0:
              raise ValueError("Distance can not be negative"						)
       if mass_a < 0 or mass_a < 0:
              raise ValueError("Mass can not be negative"						)
       if force == 0:
              lowercase__:							Tuple         =     GRAVITATIONAL_CONSTANT * product_of_mass / (distance**2)
              return {"force": force}
       elif mass_a == 0:
              lowercase__:							Tuple         =     (force) * (distance**2) / (GRAVITATIONAL_CONSTANT * mass_a)
              return {"mass_1": mass_a}
       elif mass_a == 0:
              lowercase__:							Optional[Any]         =     (force) * (distance**2) / (GRAVITATIONAL_CONSTANT * mass_a)
              return {"mass_2": mass_a}
       elif distance == 0:
              lowercase__:							List[str]         =     (GRAVITATIONAL_CONSTANT * product_of_mass / (force)) ** 0.5
              return {"distance": distance}
       raise ValueError("One and only one argument must be 0"						)


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

  doctest.testmod()








"""simple docstring"""




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


snake_case					  =						{'configuration_qdqbert': ['QDQBERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'QDQBertConfig']}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	snake_case					  =						[
	    'QDQBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'QDQBertForMaskedLM',
	    'QDQBertForMultipleChoice',
	    'QDQBertForNextSentencePrediction',
	    'QDQBertForQuestionAnswering',
	    'QDQBertForSequenceClassification',
	    'QDQBertForTokenClassification',
	    'QDQBertLayer',
	    'QDQBertLMHeadModel',
	    'QDQBertModel',
	    'QDQBertPreTrainedModel',
	    'load_tf_weights_in_qdqbert',
	]


if TYPE_CHECKING:
	from .configuration_qdqbert import QDQBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, QDQBertConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_qdqbert import (
		    QDQBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    QDQBertForMaskedLM,
		    QDQBertForMultipleChoice,
		    QDQBertForNextSentencePrediction,
		    QDQBertForQuestionAnswering,
		    QDQBertForSequenceClassification,
		    QDQBertForTokenClassification,
		    QDQBertLayer,
		    QDQBertLMHeadModel,
		    QDQBertModel,
		    QDQBertPreTrainedModel,
		    load_tf_weights_in_qdqbert,
		)


else:
	import sys

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