


from __future__ import annotations

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







def 						_lowercase       (     __lowerCamelCase			:					Optional[int]		,__lowerCamelCase			:					List[Any]		,__lowerCamelCase			:					Any		,__lowerCamelCase			:					str			)  ->   str:





     '''simple docstring'''





     UpperCamelCase__							:  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:
          UpperCamelCase__							:  Union[str, Any]								=     GRAVITATIONAL_CONSTANT * product_of_mass / (distance**2)
          return {"force": force}
     elif mass_a == 0:
          UpperCamelCase__							:  Optional[int]								=     (force) * (distance**2) / (GRAVITATIONAL_CONSTANT * mass_a)
          return {"mass_1": mass_a}
     elif mass_a == 0:
          UpperCamelCase__							:  Any								=     (force) * (distance**2) / (GRAVITATIONAL_CONSTANT * mass_a)
          return {"mass_2": mass_a}
     elif distance == 0:
          UpperCamelCase__							:  Tuple								=     (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()








from typing import TYPE_CHECKING

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


_SCREAMING_SNAKE_CASE :					Tuple			=	{
    """configuration_marian""": ["""MARIAN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MarianConfig""", """MarianOnnxConfig"""],
}

try:
   if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _SCREAMING_SNAKE_CASE :					Any			=	["""MarianTokenizer"""]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _SCREAMING_SNAKE_CASE :					List[Any]			=	[
       """MARIAN_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """MarianForCausalLM""",
       """MarianModel""",
       """MarianMTModel""",
       """MarianPreTrainedModel""",
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _SCREAMING_SNAKE_CASE :					Dict			=	["""TFMarianModel""", """TFMarianMTModel""", """TFMarianPreTrainedModel"""]

try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _SCREAMING_SNAKE_CASE :					Optional[Any]			=	["""FlaxMarianModel""", """FlaxMarianMTModel""", """FlaxMarianPreTrainedModel"""]

if TYPE_CHECKING:
   from .configuration_marian import MARIAN_PRETRAINED_CONFIG_ARCHIVE_MAP, MarianConfig, MarianOnnxConfig

   try:
      if not is_sentencepiece_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_marian import MarianTokenizer

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_marian import (
          MARIAN_PRETRAINED_MODEL_ARCHIVE_LIST,
          MarianForCausalLM,
          MarianModel,
          MarianMTModel,
          MarianPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_marian import TFMarianModel, TFMarianMTModel, TFMarianPreTrainedModel

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_marian import FlaxMarianModel, FlaxMarianMTModel, FlaxMarianPreTrainedModel

else:
   import sys

   _SCREAMING_SNAKE_CASE :					List[Any]			=	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




