





from math import factorial, pi



def 	A_       (  _lowerCAmelCase							,     _lowerCAmelCase = 30  )		->				float:

 if not isinstance(_lowerCAmelCase							,     (int, float)  ):
  raise ValueError("maclaurin_sin() requires either an int or float for theta"  )

 if not isinstance(_lowerCAmelCase							,     _lowerCAmelCase  ) or accuracy <= 0:
  raise ValueError("maclaurin_sin() requires a positive int for accuracy"  )

 UpperCamelCase			:      str 			=     float(_lowerCAmelCase  )
 UpperCamelCase			:      Optional[Any] 			=     theta // (2 * pi)
 theta -= 2 * div * pi
 return sum(
     (-1) ** r * theta ** (2 * r + 1) / factorial(2 * r + 1  ) for r in range(_lowerCAmelCase  )  )



def 	A_       (  _lowerCAmelCase							,     _lowerCAmelCase = 30  )		->				float:

 if not isinstance(_lowerCAmelCase							,     (int, float)  ):
  raise ValueError("maclaurin_cos() requires either an int or float for theta"  )

 if not isinstance(_lowerCAmelCase							,     _lowerCAmelCase  ) or accuracy <= 0:
  raise ValueError("maclaurin_cos() requires a positive int for accuracy"  )

 UpperCamelCase			:      Dict 			=     float(_lowerCAmelCase  )
 UpperCamelCase			:      int 			=     theta // (2 * pi)
 theta -= 2 * div * pi
 return sum((-1) ** r * theta ** (2 * r) / factorial(2 * r  ) for r in range(_lowerCAmelCase  )  )


if __name__ == "__main__":
      import doctest

      doctest.testmod()

      print(maclaurin_sin(10))
      print(maclaurin_sin(-10))
      print(maclaurin_sin(10, 15))
      print(maclaurin_sin(-10, 15))

      print(maclaurin_cos(5))
      print(maclaurin_cos(-5))
      print(maclaurin_cos(10, 15))
      print(maclaurin_cos(-10, 15))







from typing import List, Optional

from tokenizers import ByteLevelBPETokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer


__lowerCamelCase :  Dict										=  logging.get_logger(__name__)

__lowerCamelCase :  Union[str, Any]										=  {
    """vocab_file""": """vocab.json""",
    """merges_file""": """merges.txt""",
    """tokenizer_config_file""": """tokenizer_config.json""",
}

__lowerCamelCase :  Dict										=  {
    """vocab_file""": {
        """facebook/blenderbot_small-90M""": """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json"""
    },
    """merges_file""": {
        """facebook/blenderbot_small-90M""": """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt"""
    },
    """tokenizer_config_file""": {
        """facebook/blenderbot_small-90M""": (
            """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json"""
        )
    },
}

__lowerCamelCase :  Tuple										=  {
    """facebook/blenderbot_small-90M""": 512,
}



class       A__     ( __snake_case    ):
      _UpperCAmelCase			:Union[str, Any]							=     VOCAB_FILES_NAMES
      _UpperCAmelCase			:Dict							=     PRETRAINED_VOCAB_FILES_MAP
      _UpperCAmelCase			:List[Any]							=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      _UpperCAmelCase			:Optional[Any]							=     BlenderbotSmallTokenizer





      def __init__(				self ,							A_=None ,							A_=None ,							A_="<|endoftext|>" ,							A_="<|endoftext|>" ,							A_="<|endoftext|>" ,							A_=False ,							A_=True ,							**A_ ,							):
       '''simple docstring'''




       super().__init__(
           ByteLevelBPETokenizer(
               vocab=A_ ,							merges=A_ ,							add_prefix_space=A_ ,							trim_offsets=A_ ,							) ,							bos_token=A_ ,							eos_token=A_ ,							unk_token=A_ ,							**A_ ,							)
       UpperCamelCase			:      Union[str, Any] 			=     add_prefix_space





      def  __UpperCamelCase(				self ,							A_ ,							A_=None     ):
       '''simple docstring'''




       UpperCamelCase			:      Dict 			=     [self.bos_token_id] + token_ids_a + [self.eos_token_id]
       if token_ids_a is None:
        return output

       return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]





      def  __UpperCamelCase(				self ,							A_ ,							A_ = None     ):
       '''simple docstring'''




       UpperCamelCase			:      Tuple 			=     [self.sep_token_id]
       UpperCamelCase			:      int 			=     [self.cls_token_id]

       if token_ids_a is None:
        return len(cls + token_ids_a + sep     ) * [0]
       return len(cls + token_ids_a + sep + sep + token_ids_a + sep     ) * [0]
