'''simple docstring'''

from __future__ import annotations

# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
lowerCAmelCase_ : Union[str, Any]						  =      10


def __a (	__lowerCamelCase			:						str ,		__lowerCamelCase			:						Optional[int] ,		__lowerCamelCase			:						Union[str, Any] ,		__lowerCamelCase			:						Union[str, Any]				)	->							int:
      '''simple docstring'''


      for i in range(lowerCamelCase__ ,		lowerCamelCase__				):
            if array[i] == target:
                  return i
      return -1


def __a (	__lowerCamelCase			:						Union[str, Any] ,		__lowerCamelCase			:						Any				)	->							int:
      '''simple docstring'''


      lowercase_     =      0
      lowercase_     =      len(lowerCamelCase__				)
      while left <= right:
            if right - left < precision:
                  return lin_search(lowerCamelCase__ ,		lowerCamelCase__ ,		lowerCamelCase__ ,		lowerCamelCase__				)

            lowercase_     =      (left + right) // 3 + 1
            lowercase_     =      2 * (left + right) // 3 + 1

            if array[one_third] == target:
                  return one_third
            elif array[two_third] == target:
                  return two_third

            elif target < array[one_third]:
                  lowercase_     =      one_third - 1
            elif array[two_third] < target:
                  lowercase_     =      two_third + 1

            else:
                  lowercase_     =      one_third + 1
                  lowercase_     =      two_third - 1
      else:
            return -1


def __a (	__lowerCamelCase			:						Tuple ,		__lowerCamelCase			:						int ,		__lowerCamelCase			:						List[str] ,		__lowerCamelCase			:						Any				)	->							int:
      '''simple docstring'''


      if left < right:
            if right - left < precision:
                  return lin_search(lowerCamelCase__ ,		lowerCamelCase__ ,		lowerCamelCase__ ,		lowerCamelCase__				)
            lowercase_     =      (left + right) // 3 + 1
            lowercase_     =      2 * (left + right) // 3 + 1

            if array[one_third] == target:
                  return one_third
            elif array[two_third] == target:
                  return two_third

            elif target < array[one_third]:
                  return rec_ternary_search(lowerCamelCase__ ,		one_third - 1 ,		lowerCamelCase__ ,		lowerCamelCase__				)
            elif array[two_third] < target:
                  return rec_ternary_search(two_third + 1 ,		lowerCamelCase__ ,		lowerCamelCase__ ,		lowerCamelCase__				)
            else:
                  return rec_ternary_search(one_third + 1 ,		two_third - 1 ,		lowerCamelCase__ ,		lowerCamelCase__				)
      else:
            return -1


if __name__ == "__main__":
       import doctest

       doctest.testmod()

       lowerCAmelCase_ : Any						  =      input("Enter numbers separated by comma:\n").strip()
       lowerCAmelCase_ : Optional[Any]						  =      [int(item.strip()) for item in user_input.split(",")]
       assert collection == sorted(collection), F"List must be ordered.\n{collection}."
       lowerCAmelCase_ : int						  =      int(input("Enter the number to be found in the list:\n").strip())
       lowerCAmelCase_ : Dict						  =      ite_ternary_search(collection, target)
       lowerCAmelCase_ : int						  =      rec_ternary_search(0, len(collection) - 1, collection, target)
       if resulta != -1:
              print(F'''Iterative search: {target} found at positions: {resulta}''')
              print(F'''Recursive search: {target} found at positions: {resulta}''')
       else:
              print("Not found")







'''simple docstring'''

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

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaTokenizer


if TYPE_CHECKING:
       from transformers.pipelines.conversational import Conversation


lowerCAmelCase_ : Optional[Any]						  =      logging.get_logger(__name__)

lowerCAmelCase_ : Any						  =      {"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

lowerCAmelCase_ : Tuple						  =      {
    "vocab_file": {
        "gpt2": "https://huggingface.co/gpt2/resolve/main/vocab.json",
        "gpt2-medium": "https://huggingface.co/gpt2-medium/resolve/main/vocab.json",
        "gpt2-large": "https://huggingface.co/gpt2-large/resolve/main/vocab.json",
        "gpt2-xl": "https://huggingface.co/gpt2-xl/resolve/main/vocab.json",
        "distilgpt2": "https://huggingface.co/distilgpt2/resolve/main/vocab.json",
    },
    "merges_file": {
        "gpt2": "https://huggingface.co/gpt2/resolve/main/merges.txt",
        "gpt2-medium": "https://huggingface.co/gpt2-medium/resolve/main/merges.txt",
        "gpt2-large": "https://huggingface.co/gpt2-large/resolve/main/merges.txt",
        "gpt2-xl": "https://huggingface.co/gpt2-xl/resolve/main/merges.txt",
        "distilgpt2": "https://huggingface.co/distilgpt2/resolve/main/merges.txt",
    },
    "tokenizer_file": {
        "gpt2": "https://huggingface.co/gpt2/resolve/main/tokenizer.json",
        "gpt2-medium": "https://huggingface.co/gpt2-medium/resolve/main/tokenizer.json",
        "gpt2-large": "https://huggingface.co/gpt2-large/resolve/main/tokenizer.json",
        "gpt2-xl": "https://huggingface.co/gpt2-xl/resolve/main/tokenizer.json",
        "distilgpt2": "https://huggingface.co/distilgpt2/resolve/main/tokenizer.json",
    },
}

lowerCAmelCase_ : Dict						  =      {
    "gpt2": 1_024,
    "gpt2-medium": 1_024,
    "gpt2-large": 1_024,
    "gpt2-xl": 1_024,
    "distilgpt2": 1_024,
}





class 							lowercase						(						__lowerCamelCase ):
   lowerCamelCase_    					=VOCAB_FILES_NAMES
   lowerCamelCase_    					=PRETRAINED_VOCAB_FILES_MAP
   lowerCamelCase_    					=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   lowerCamelCase_    					=['input_ids', 'attention_mask']
   lowerCamelCase_    					=GPTaTokenizer


   def __init__(   self				:	Dict   ,		__lowerCAmelCase				:	List[Any]=None   ,		__lowerCAmelCase				:	Optional[Any]=None   ,		__lowerCAmelCase				:	Optional[int]=None   ,		__lowerCAmelCase				:	Any="<|endoftext|>"   ,		__lowerCAmelCase				:	Union[str, Any]="<|endoftext|>"   ,		__lowerCAmelCase				:	List[Any]="<|endoftext|>"   ,		__lowerCAmelCase				:	Optional[Any]=False   ,		**__lowerCAmelCase				:	Dict   ,		)      ->					int:
         super().__init__(
             __lowerCAmelCase   ,		__lowerCAmelCase   ,		tokenizer_file=__lowerCAmelCase   ,		unk_token=__lowerCAmelCase   ,		bos_token=__lowerCAmelCase   ,		eos_token=__lowerCAmelCase   ,		add_prefix_space=__lowerCAmelCase   ,		**__lowerCAmelCase   ,		)

         lowercase_     =      kwargs.pop("add_bos_token"   ,		__lowerCAmelCase)

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

         lowercase_     =      add_prefix_space


   def __UpperCAmelCase       (   self				:	List[str]   ,		*__lowerCAmelCase				:	List[str]   ,		**__lowerCAmelCase				:	str)      ->					BatchEncoding:
         lowercase_     =      kwargs.get("is_split_into_words"   ,		__lowerCAmelCase)
         assert self.add_prefix_space or not is_split_into_words, (
             F'You need to instantiate {self.__class__.__name__} with add_prefix_space=True '
             "to use it with pretokenized inputs."
         )

         return super()._batch_encode_plus(*__lowerCAmelCase   ,		**__lowerCAmelCase)


   def __UpperCAmelCase       (   self				:	List[Any]   ,		*__lowerCAmelCase				:	Union[str, Any]   ,		**__lowerCAmelCase				:	Union[str, Any])      ->					BatchEncoding:
         lowercase_     =      kwargs.get("is_split_into_words"   ,		__lowerCAmelCase)

         assert self.add_prefix_space or not is_split_into_words, (
             F'You need to instantiate {self.__class__.__name__} with add_prefix_space=True '
             "to use it with pretokenized inputs."
         )

         return super()._encode_plus(*__lowerCAmelCase   ,		**__lowerCAmelCase)


   def __UpperCAmelCase       (   self				:	Optional[int]   ,		__lowerCAmelCase				:	str   ,		__lowerCAmelCase				:	Optional[str] = None)      ->					Tuple[str]:
         lowercase_     =      self._tokenizer.model.save(__lowerCAmelCase   ,		name=__lowerCAmelCase)
         return tuple(__lowerCAmelCase)


   def __UpperCAmelCase       (   self				:	Tuple   ,		__lowerCAmelCase				:	"Conversation")      ->					List[int]:
         lowercase_     =      []
         for is_user, text in conversation.iter_texts():
               input_ids.extend(self.encode(__lowerCAmelCase   ,		add_special_tokens=__lowerCAmelCase) + [self.eos_token_id])

         if len(__lowerCAmelCase) > self.model_max_length:
               lowercase_     =      input_ids[-self.model_max_length :]
         return input_ids






