


'''simple docstring'''





import unittest

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




class 							UpperCAmelCase ( unittest.TestCase	):


 @cached_property
 def 					__SCREAMING_SNAKE_CASE				(			self       :  List[str]   ):
    return BlenderbotTokenizer.from_pretrained('''facebook/blenderbot-3B'''   )


 @cached_property
 def 					__SCREAMING_SNAKE_CASE				(			self       :  Optional[int]   ):
    return BlenderbotTokenizerFast.from_pretrained('''facebook/blenderbot-3B'''   )


 def 					__SCREAMING_SNAKE_CASE				(			self       :  Optional[Any]   ):
    UpperCAmelCase__  :Dict            =			self.tokenizer_ab
    UpperCAmelCase__  :Optional[int]            =			''' I am a small frog.'''
    UpperCAmelCase__  :Any            =			tok([src_text] ,					padding=__lowerCamelCase ,					truncation=__lowerCamelCase   )['''input_ids''']
    UpperCAmelCase__  :str            =			tok.batch_decode(__lowerCamelCase ,					skip_special_tokens=__lowerCamelCase ,					clean_up_tokenization_spaces=__lowerCamelCase   )[0]
    assert src_text == decoded


 def 					__SCREAMING_SNAKE_CASE				(			self       :  str   ):
    UpperCAmelCase__  :List[str]            =			self.rust_tokenizer_ab
    UpperCAmelCase__  :int            =			''' I am a small frog.'''
    UpperCAmelCase__  :str            =			tok([src_text] ,					padding=__lowerCamelCase ,					truncation=__lowerCamelCase   )['''input_ids''']
    UpperCAmelCase__  :str            =			tok.batch_decode(__lowerCamelCase ,					skip_special_tokens=__lowerCamelCase ,					clean_up_tokenization_spaces=__lowerCamelCase   )[0]
    assert src_text == decoded


 def 					__SCREAMING_SNAKE_CASE				(			self       :  Union[str, Any]   ):
    assert self.tokenizer_ab.add_prefix_space
    assert self.tokenizer_ab([''' Sam''', '''Sam''']   ).input_ids == [[5_5_0_2, 2], [5_5_0_2, 2]]





 def 					__SCREAMING_SNAKE_CASE				(			self       :  Union[str, Any]   ):
    assert self.rust_tokenizer_ab.add_prefix_space
    assert self.rust_tokenizer_ab([''' Sam''', '''Sam''']   ).input_ids == [[5_5_0_2, 2], [5_5_0_2, 2]]







'''simple docstring'''





from scipy.constants import g


def 					a__    (				UpperCamelCase_	:			float,      UpperCamelCase_	:			float	):
   if mass < 0:
      # handling of negative values of mass
      raise ValueError('''The mass of a body cannot be negative'''	)
   if height < 0:
      # handling of negative values of height
      raise ValueError('''The height above the ground cannot be negative'''	)
   return mass * g * height


if __name__ == "__main__":
    from doctest import testmod

    testmod(name='''potential_energy''')



