


from __future__ import annotations







def SCREAMING_SNAKE_CASE	(			__lowerCAmelCase							,   __lowerCAmelCase = None							,   __lowerCAmelCase = None				)    ->				None:
  if start is None:
    snake_case__						= 0

  if end is None:
    snake_case__						= len(__lowerCAmelCase				) - 1

  if start >= end:
    return

  snake_case__						= (start + end) // 2

  slowsort(__lowerCAmelCase							,   __lowerCAmelCase							,   __lowerCAmelCase				)
  slowsort(__lowerCAmelCase							,   mid + 1							,   __lowerCAmelCase				)

  if sequence[end] < sequence[mid]:
    snake_case__				,				snake_case__						= sequence[mid], sequence[end]

  slowsort(__lowerCAmelCase							,   __lowerCAmelCase							,   end - 1				)


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

   testmod()




'''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					 =	logging.get_logger(__name__)

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

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

UpperCAmelCase					 =	{
    '''gpt-neox-20b''': 2048,
}


class 	lowerCAmelCase  (   A ):
       lowerCAmelCase_												=			VOCAB_FILES_NAMES
       lowerCAmelCase_												=			PRETRAINED_VOCAB_FILES_MAP
       lowerCAmelCase_												=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       lowerCAmelCase_												=			["input_ids", "attention_mask"]







       def __init__(				self      :			Tuple    ,   __lowercase      :			Union[str, Any]=None    ,   __lowercase      :			Union[str, Any]=None    ,   __lowercase      :			str=None    ,   __lowercase      :			Optional[int]="<|endoftext|>"    ,   __lowercase      :			List[Any]="<|endoftext|>"    ,   __lowercase      :			Tuple="<|endoftext|>"    ,   __lowercase      :			Optional[int]=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    ,   )

            __lowercase      		=json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()   )
            if pre_tok_state.get('add_prefix_space'    ,   __lowercase   ) != add_prefix_space:
                 __lowercase      		=getattr(__lowercase    ,   pre_tok_state.pop('type'   )   )
                 __lowercase      		=add_prefix_space
                 __lowercase      		=pre_tok_class(**__lowercase   )

            __lowercase      		=add_prefix_space







       def       snake_case (				self      :			Optional[Any]    ,   __lowercase      :			str    ,   __lowercase      :			Optional[str] = None   ):







            """simple docstring"""







            __lowercase      		=self._tokenizer.model.save(__lowercase    ,   name=__lowercase   )
            return tuple(__lowercase   )







       def       snake_case (				self      :			Optional[Any]    ,   __lowercase      :			"Conversation"   ):







            """simple docstring"""







            __lowercase      		=[]
            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:
                 __lowercase      		=input_ids[-self.model_max_length :]
            return input_ids


