



'''simple docstring'''






from __future__ import annotations

# Define the Gravitational Constant G and the function
A_				:					Union[str, Any]							=      6.6743e-11  # unit of G : m^3 * kg^-1 * s^-2




def        snake_case_   (	lowerCAmelCase_			,  lowerCAmelCase_			,  lowerCAmelCase_			,  lowerCAmelCase_						)->						dict[str, float]:





       '''simple docstring'''


       _UpperCAmelCase    :		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:
              _UpperCAmelCase    :		Dict     	=					GRAVITATIONAL_CONSTANT * product_of_mass / (distance**2)
              return {"force": force}
       elif mass_a == 0:
              _UpperCAmelCase    :		Tuple     	=					(force) * (distance**2) / (GRAVITATIONAL_CONSTANT * mass_a)
              return {"mass_1": mass_a}
       elif mass_a == 0:
              _UpperCAmelCase    :		Dict     	=					(force) * (distance**2) / (GRAVITATIONAL_CONSTANT * mass_a)
              return {"mass_2": mass_a}
       elif distance == 0:
              _UpperCAmelCase    :		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_tf_available, is_torch_available


__A	:       Dict        =						{'configuration_cvt': ['CVT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CvtConfig']}


try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__A	:       Any        =						[
	    'CVT_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'CvtForImageClassification',
	    'CvtModel',
	    'CvtPreTrainedModel',
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__A	:       List[str]        =						[
	    'TF_CVT_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'TFCvtForImageClassification',
	    'TFCvtModel',
	    'TFCvtPreTrainedModel',
	]

if TYPE_CHECKING:
	from .configuration_cvt import CVT_PRETRAINED_CONFIG_ARCHIVE_MAP, CvtConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_cvt import (
		    CVT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    CvtForImageClassification,
		    CvtModel,
		    CvtPreTrainedModel,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_cvt import (
		    TF_CVT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFCvtForImageClassification,
		    TFCvtModel,
		    TFCvtPreTrainedModel,
		)


else:
	import sys

	__A	:       str        =						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





