





'''simple docstring'''

from math import factorial




def    _a    (							lowerCAmelCase_			,      lowerCAmelCase_	):





      """simple docstring"""



      if n < k or k < 0:
            raise ValueError('''Please enter positive integers for n and k where n >= k'''	)
      return factorial(lowerCAmelCase_	) // (factorial(lowerCAmelCase_	) * factorial(n - k	))


if __name__ == "__main__":
   print(
       'The number of five-card hands possible from a standard',
       F"""fifty-two card deck is: {combinations(5_2, 5)}\n""",
   )

   print(
       'If a class of 40 students must be arranged into groups of',
       F"""4 for group projects, there are {combinations(4_0, 4)} ways""",
       'to arrange them.\n',
   )

   print(
       'If 10 teams are competing in a Formula One race, there',
       F"""are {combinations(1_0, 3)} ways that first, second and""",
       'third place can be awarded.',
   )









'''simple docstring'''

import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if TYPE_CHECKING:
   from transformers.pipelines.conversational import Conversation


UpperCAmelCase					:		Optional[int]		=							logging.get_logger(__name__)

UpperCAmelCase					:		List[Any]		=							{'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

UpperCAmelCase					:		Any		=							{
    'tokenizer_file': {
        'EleutherAI/gpt-neox-20b': 'https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/tokenizer.json',
    },
}

UpperCAmelCase					:		Optional[Any]		=							{
    'gpt-neox-20b': 2_0_4_8,
}





class lowerCamelCase						(a__					):
  _lowercase  :	Optional[int]       					=				VOCAB_FILES_NAMES
  _lowercase  :	str       					=				PRETRAINED_VOCAB_FILES_MAP
  _lowercase  :	Dict       					=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  _lowercase  :	Optional[int]       					=				["""input_ids""", """attention_mask"""]







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






        """simple docstring"""





        super().__init__(
            lowercase__     ,     lowercase__     ,     tokenizer_file=lowercase__     ,     unk_token=lowercase__     ,     bos_token=lowercase__     ,     eos_token=lowercase__     ,     add_prefix_space=lowercase__     ,     **lowercase__     ,     )

        _snake_case		:	Optional[int]					     =     json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()		)
        if pre_tok_state.get('''add_prefix_space'''     ,     lowercase__		) != add_prefix_space:
              _snake_case		:	int					     =     getattr(lowercase__     ,     pre_tok_state.pop('''type'''		)		)
              _snake_case		:	int					     =     add_prefix_space
              _snake_case		:	Optional[Any]					     =     pre_tok_class(**lowercase__		)

        _snake_case		:	List[str]					     =     add_prefix_space







  def 				UpperCAmelCase_				(		self     ,     lowercase__     ,     lowercase__ = None		)		->						Tuple[str]:






        """simple docstring"""





        _snake_case		:	Optional[int]					     =     self._tokenizer.model.save(lowercase__     ,     name=lowercase__		)
        return tuple(lowercase__		)







  def 				UpperCAmelCase_				(		self     ,     lowercase__		)		->						List[int]:






        """simple docstring"""





        _snake_case		:	List[str]					     =     []
        for is_user, text in conversation.iter_texts():
              input_ids.extend(self.encode(lowercase__     ,     add_special_tokens=lowercase__		) + [self.eos_token_id]		)

        if len(lowercase__		) > self.model_max_length:
              _snake_case		:	Dict					     =     input_ids[-self.model_max_length :]
        return input_ids


