
"""simple docstring"""

from __future__ import annotations

# Define the Gravitational Constant G and the function
_A				=					6.6_743E-11  # unit of G : m^3 * kg^-1 * s^-2
def 						UpperCAmelCase   (						a_,		a_,		a_,		a_     ):





		'''simple docstring'''


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










"""simple docstring"""






import unittest

from transformers import BlenderbotTokenizer, BlenderbotTokenizerFast
from transformers.utils import cached_property


class 	A_       (     unittest.TestCase   ):





  """simple docstring"""

  @cached_property
  def 							lowercase_     (						self						)				->					Optional[Any]:
     return BlenderbotTokenizer.from_pretrained('facebook/blenderbot-3B'						)
  @cached_property
  def 							lowercase_     (						self						)				->					Optional[int]:
     return BlenderbotTokenizerFast.from_pretrained('facebook/blenderbot-3B'						)
  def 							lowercase_     (						self						)				->					Union[str, Any]:
     a   :	List[Any]						=    self.tokenizer_ab
     a   :	int						=    ' I am a small frog.'
     a   :	Any						=    tok([src_text]  ,					padding=__UpperCAmelCase  ,					truncation=__UpperCAmelCase						)['input_ids']
     a   :	List[str]						=    tok.batch_decode(__UpperCAmelCase  ,					skip_special_tokens=__UpperCAmelCase  ,					clean_up_tokenization_spaces=__UpperCAmelCase						)[0]
     assert src_text == decoded
  def 							lowercase_     (						self						)				->					Optional[Any]:
     a   :	Optional[int]						=    self.rust_tokenizer_ab
     a   :	List[Any]						=    ' I am a small frog.'
     a   :	Union[str, Any]						=    tok([src_text]  ,					padding=__UpperCAmelCase  ,					truncation=__UpperCAmelCase						)['input_ids']
     a   :	Optional[Any]						=    tok.batch_decode(__UpperCAmelCase  ,					skip_special_tokens=__UpperCAmelCase  ,					clean_up_tokenization_spaces=__UpperCAmelCase						)[0]
     assert src_text == decoded
  def 							lowercase_     (						self						)				->					Tuple:
     assert self.tokenizer_ab.add_prefix_space
     assert self.tokenizer_ab([' Sam', 'Sam']						).input_ids == [[55_02, 2], [55_02, 2]]






  def 							lowercase_     (						self						)				->					Tuple:
     assert self.rust_tokenizer_ab.add_prefix_space
     assert self.rust_tokenizer_ab([' Sam', 'Sam']						).input_ids == [[55_02, 2], [55_02, 2]]





