






"""simple docstring"""
import json
import os
from typing import Dict, List, Optional, Tuple

import regex as re

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


A:     List[str]										=	logging.get_logger(__name__)


A:     Tuple										=	{
    "vocab_file": "vocab.json",
    "merges_file": "merges.txt",
    "tokenizer_config_file": "tokenizer_config.json",
}

A:     str										=	{
    "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"
        )
    },
}

A:     Dict										=	{"facebook/blenderbot_small-90M": 5_1_2}

def    _snake_case		(		UpperCamelCase		:	List[str]		):
 UpperCAmelCase			:      List[Any]			=			set()
 UpperCAmelCase			:      str			=			word[0]
 for char in word[1:]:
  pairs.add((prev_char, char)		)
  UpperCAmelCase			:      Dict			=			char

 UpperCAmelCase			:      Optional[int]			=			set(UpperCamelCase		)
 return pairs



class    SCREAMING_SNAKE_CASE__						(      UpperCAmelCase__				):
   __lowerCAmelCase						:     Any		=		VOCAB_FILES_NAMES
   __lowerCAmelCase						:     Optional[int]		=		PRETRAINED_VOCAB_FILES_MAP
   __lowerCAmelCase						:     Any		=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __lowerCAmelCase						:     List[Any]		=		['input_ids', 'attention_mask']

   def __init__(     self   ,  _SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE="__start__"   ,  _SCREAMING_SNAKE_CASE="__end__"   ,  _SCREAMING_SNAKE_CASE="__unk__"   ,  _SCREAMING_SNAKE_CASE="__null__"   ,  **_SCREAMING_SNAKE_CASE   ,  )						->   Any:





    '''simple docstring'''




    super().__init__(unk_token=_SCREAMING_SNAKE_CASE   ,  bos_token=_SCREAMING_SNAKE_CASE   ,  eos_token=_SCREAMING_SNAKE_CASE   ,  pad_token=_SCREAMING_SNAKE_CASE   ,  **_SCREAMING_SNAKE_CASE		)

    with open(_SCREAMING_SNAKE_CASE   ,  encoding="""utf-8"""		) as vocab_handle:
     UpperCAmelCase			:      str			=			json.load(_SCREAMING_SNAKE_CASE		)
    UpperCAmelCase			:      Union[str, Any]			=			{v: k for k, v in self.encoder.items()}
    with open(_SCREAMING_SNAKE_CASE   ,  encoding="""utf-8"""		) as merges_handle:
     UpperCAmelCase			:      Optional[int]			=			merges_handle.read().split("""\n"""		)[1:-1]
    UpperCAmelCase			:      Optional[Any]			=			[tuple(merge.split()		) for merge in merges]
    UpperCAmelCase			:      List[str]			=			dict(zip(_SCREAMING_SNAKE_CASE   ,  range(len(_SCREAMING_SNAKE_CASE		)		)		)		)
    UpperCAmelCase			:      str			=			{}

   @property
   def 			SCREAMING_SNAKE_CASE  (     self		)						->   int:





    '''simple docstring'''




    return len(self.encoder		)

   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Dict:





    '''simple docstring'''




    return dict(self.encoder   ,  **self.added_tokens_encoder		)

   def 			SCREAMING_SNAKE_CASE  (     self   ,  _SCREAMING_SNAKE_CASE		)						->   str:





    '''simple docstring'''




    if token in self.cache:
     return self.cache[token]
    UpperCAmelCase			:      Tuple			=			re.sub("""([.,!?()])"""   ,  r""" \1"""   ,  _SCREAMING_SNAKE_CASE		)
    UpperCAmelCase			:      str			=			re.sub("""(')"""   ,  r""" \1 """   ,  _SCREAMING_SNAKE_CASE		)
    UpperCAmelCase			:      List[str]			=			re.sub(r"""\s{2,}"""   ,  """ """   ,  _SCREAMING_SNAKE_CASE		)
    if "\n" in token:
     UpperCAmelCase			:      List[Any]			=			token.replace("""\n"""   ,  """ __newln__"""		)

    UpperCAmelCase			:      Union[str, Any]			=			token.split(""" """		)
    UpperCAmelCase			:      Optional[Any]			=			[]
    for token in tokens:
     if not len(_SCREAMING_SNAKE_CASE		):
      continue

     UpperCAmelCase			:      Optional[int]			=			token.lower()
     UpperCAmelCase			:      int			=			tuple(_SCREAMING_SNAKE_CASE		)
     UpperCAmelCase			:      Dict			=			tuple(list(word[:-1]		) + [word[-1] + """</w>"""]		)
     UpperCAmelCase			:      List[Any]			=			get_pairs(_SCREAMING_SNAKE_CASE		)

     if not pairs:
      words.append(_SCREAMING_SNAKE_CASE		)
      continue

     while True:
      UpperCAmelCase			:      Dict			=			min(_SCREAMING_SNAKE_CASE   ,  key=lambda _SCREAMING_SNAKE_CASE		: self.bpe_ranks.get(_SCREAMING_SNAKE_CASE   ,  float("""inf"""		)		)		)
      if bigram not in self.bpe_ranks:
       break
      UpperCAmelCase			:      Dict			=			bigram
      UpperCAmelCase			:      int			=			[]
      UpperCAmelCase			:      Tuple			=			0

      while i < len(_SCREAMING_SNAKE_CASE		):
       try:
        UpperCAmelCase			:      str			=			word.index(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE		)
        new_word.extend(word[i:j]		)
        UpperCAmelCase			:      Dict			=			j
       except ValueError:
        new_word.extend(word[i:]		)
        break

       if word[i] == first and i < len(_SCREAMING_SNAKE_CASE		) - 1 and word[i + 1] == second:
        new_word.append(first + second		)
        i += 2
       else:
        new_word.append(word[i]		)
        i += 1
      UpperCAmelCase			:      List[Any]			=			tuple(_SCREAMING_SNAKE_CASE		)
      UpperCAmelCase			:      Dict			=			new_word
      if len(_SCREAMING_SNAKE_CASE		) == 1:
       break
      else:
       UpperCAmelCase			:      int			=			get_pairs(_SCREAMING_SNAKE_CASE		)
     UpperCAmelCase			:      Tuple			=			"""@@ """.join(_SCREAMING_SNAKE_CASE		)
     UpperCAmelCase			:      int			=			word[:-4]

     UpperCAmelCase			:      Optional[int]			=			word
     words.append(_SCREAMING_SNAKE_CASE		)
    return " ".join(_SCREAMING_SNAKE_CASE		)

   def 			SCREAMING_SNAKE_CASE  (     self   ,  _SCREAMING_SNAKE_CASE		)						->   List[str]:





    '''simple docstring'''




    UpperCAmelCase			:      Dict			=			[]

    UpperCAmelCase			:      List[Any]			=			re.findall(r"""\S+\n?"""   ,  _SCREAMING_SNAKE_CASE		)

    for token in words:
     split_tokens.extend(list(self.bpe(_SCREAMING_SNAKE_CASE		).split(""" """		)		)		)
    return split_tokens

   def 			SCREAMING_SNAKE_CASE  (     self   ,  _SCREAMING_SNAKE_CASE		)						->   int:





    '''simple docstring'''




    UpperCAmelCase			:      Any			=			token.lower()
    return self.encoder.get(_SCREAMING_SNAKE_CASE   ,  self.encoder.get(self.unk_token		)		)

   def 			SCREAMING_SNAKE_CASE  (     self   ,  _SCREAMING_SNAKE_CASE		)						->   str:





    '''simple docstring'''




    return self.decoder.get(_SCREAMING_SNAKE_CASE   ,  self.unk_token		)

   def 			SCREAMING_SNAKE_CASE  (     self   ,  _SCREAMING_SNAKE_CASE		)						->   str:





    '''simple docstring'''




    UpperCAmelCase			:      List[Any]			=			""" """.join(_SCREAMING_SNAKE_CASE		).replace("""@@ """   ,  """"""		).strip()
    return out_string




   def 			SCREAMING_SNAKE_CASE  (     self   ,  _SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE = None		)						->   Tuple[str]:





    '''simple docstring'''




    if not os.path.isdir(_SCREAMING_SNAKE_CASE		):
     logger.error(F"Vocabulary path ({save_directory}) should be a directory"		)
     return
    UpperCAmelCase			:      Dict			=			os.path.join(
        _SCREAMING_SNAKE_CASE   ,  (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]		)
    UpperCAmelCase			:      Union[str, Any]			=			os.path.join(
        _SCREAMING_SNAKE_CASE   ,  (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""merges_file"""]		)

    with open(_SCREAMING_SNAKE_CASE   ,  """w"""   ,  encoding="""utf-8"""		) as f:
     f.write(json.dumps(self.encoder   ,  indent=2   ,  sort_keys=_SCREAMING_SNAKE_CASE   ,  ensure_ascii=_SCREAMING_SNAKE_CASE		) + """\n"""		)

    UpperCAmelCase			:      Dict			=			0
    with open(_SCREAMING_SNAKE_CASE   ,  """w"""   ,  encoding="""utf-8"""		) as writer:
     writer.write("""#version: 0.2\n"""		)
     for bpe_tokens, token_index in sorted(self.bpe_ranks.items()   ,  key=lambda _SCREAMING_SNAKE_CASE		: kv[1]		):
      if index != token_index:
       logger.warning(
           F"Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."
           """ Please check that the tokenizer is not corrupted!"""		)
       UpperCAmelCase			:      List[Any]			=			token_index
      writer.write(""" """.join(_SCREAMING_SNAKE_CASE		) + """\n"""		)
      index += 1

    return vocab_file, merge_file





"""simple docstring"""
from __future__ import annotations

from collections.abc import Generator

def    _snake_case		(		):
 UpperCAmelCase			:      dict[int, int]			=			{}
 UpperCAmelCase			:      str			=			2
 while True:
  UpperCAmelCase			:      List[str]			=			factor_map.pop(UpperCamelCase    ,	UpperCamelCase		)
  if factor:
   UpperCAmelCase			:      Dict			=			factor + prime
   while x in factor_map:
    x += factor
   UpperCAmelCase			:      Tuple			=			factor
  else:
   UpperCAmelCase			:      Optional[int]			=			prime
   yield prime
  prime += 1

def    _snake_case		(		UpperCamelCase		:	float = 1e1_0		):
 UpperCAmelCase			:      Tuple			=			sieve()

 UpperCAmelCase			:      Optional[Any]			=			1
 while True:
  UpperCAmelCase			:      List[str]			=			next(UpperCamelCase		)
  if (2 * prime * n) > limit:
   return n
  # Ignore the next prime as the reminder will be 2.
  next(UpperCamelCase		)
  n += 2


if __name__ == "__main__":
      print(solution())
