





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


UpperCAmelCase_     							= logging.get_logger(__name__)

UpperCAmelCase_     							= {
    'vocab_file': 'vocab.json',
    'merges_file': 'merges.txt',
    'tokenizer_config_file': 'tokenizer_config.json',
}

UpperCAmelCase_     							= {
    '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'
        )
    },
}

UpperCAmelCase_     							= {
    'facebook/blenderbot_small-90M': 512,
}






class     lowercase__       (	__lowerCamelCase				):

   '''simple docstring'''


   a						:							Dict   		=		VOCAB_FILES_NAMES
   a						:							str   		=		PRETRAINED_VOCAB_FILES_MAP
   a						:							Union[str, Any]   		=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   a						:							Optional[int]   		=		BlenderbotSmallTokenizer




   def __init__(    self,		__magic_name__=None,		__magic_name__=None,		__magic_name__="<|endoftext|>",		__magic_name__="<|endoftext|>",		__magic_name__="<|endoftext|>",		__magic_name__=False,		__magic_name__=True,		**__magic_name__,		) ->      Optional[Any]:






       """simple docstring"""
       super().__init__(
           ByteLevelBPETokenizer(
               vocab=__magic_name__,		merges=__magic_name__,		add_prefix_space=__magic_name__,		trim_offsets=__magic_name__,		),		bos_token=__magic_name__,		eos_token=__magic_name__,		unk_token=__magic_name__,		**__magic_name__,		)
       UpperCamelCase__							:				Optional[Any]          =      add_prefix_space




   def       UpperCamelCase__  (    self,		__magic_name__,		__magic_name__=None							) ->      Dict:






       """simple docstring"""
       UpperCamelCase__							:				str          =      [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,		__magic_name__,		__magic_name__ = None							) ->      List[int]:






       """simple docstring"""
       UpperCamelCase__							:				Optional[int]          =      [self.sep_token_id]
       UpperCamelCase__							:				Optional[Any]          =      [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]








from math import factorial




def 		lowerCAmelCase_    (  __UpperCAmelCase:			int		,   __UpperCAmelCase:			int      )      ->	int:

    # If either of the conditions are true, the function is being asked
    # to calculate a factorial of a negative number, which is not possible
    if n < k or k < 0:
        raise ValueError('''Please enter positive integers for n and k where n >= k'''      )
    return factorial(__UpperCAmelCase      ) // (factorial(__UpperCAmelCase      ) * factorial(n - k      ))


if __name__ == "__main__":
  print(
      'The number of five-card hands possible from a standard',
      F'''fifty-two card deck is: {combinations(52, 5)}\n''',
  )

  print(
      'If a class of 40 students must be arranged into groups of',
      F'''4 for group projects, there are {combinations(40, 4)} ways''',
      'to arrange them.\n',
  )

  print(
      'If 10 teams are competing in a Formula One race, there',
      F'''are {combinations(10, 3)} ways that first, second and''',
      'third place can be awarded.',
  )

