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

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


if TYPE_CHECKING:
   from transformers.pipelines.conversational import Conversation

__lowerCamelCase							= logging.get_logger(__name__)

__lowerCamelCase							= {"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt"""}

__lowerCamelCase							= {
    """vocab_file""": {
        """microsoft/deberta-base""": """https://huggingface.co/microsoft/deberta-base/resolve/main/vocab.json""",
        """microsoft/deberta-large""": """https://huggingface.co/microsoft/deberta-large/resolve/main/vocab.json""",
        """microsoft/deberta-xlarge""": """https://huggingface.co/microsoft/deberta-xlarge/resolve/main/vocab.json""",
        """microsoft/deberta-base-mnli""": """https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/vocab.json""",
        """microsoft/deberta-large-mnli""": """https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/vocab.json""",
        """microsoft/deberta-xlarge-mnli""": (
            """https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/vocab.json"""
        ),
    },
    """merges_file""": {
        """microsoft/deberta-base""": """https://huggingface.co/microsoft/deberta-base/resolve/main/merges.txt""",
        """microsoft/deberta-large""": """https://huggingface.co/microsoft/deberta-large/resolve/main/merges.txt""",
        """microsoft/deberta-xlarge""": """https://huggingface.co/microsoft/deberta-xlarge/resolve/main/merges.txt""",
        """microsoft/deberta-base-mnli""": """https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/merges.txt""",
        """microsoft/deberta-large-mnli""": """https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/merges.txt""",
        """microsoft/deberta-xlarge-mnli""": (
            """https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/merges.txt"""
        ),
    },
}

__lowerCamelCase							= {
    """microsoft/deberta-base""": 5_12,
    """microsoft/deberta-large""": 5_12,
    """microsoft/deberta-xlarge""": 5_12,
    """microsoft/deberta-base-mnli""": 5_12,
    """microsoft/deberta-large-mnli""": 5_12,
    """microsoft/deberta-xlarge-mnli""": 5_12,
}

__lowerCamelCase							= {
    """microsoft/deberta-base""": {"""do_lower_case""": False},
    """microsoft/deberta-large""": {"""do_lower_case""": False},
}


def     UpperCamelCase      (					):
       snake_case :     List[str]           =   (
           list(range(ord("!"					)       ,      ord("~"					) + 1					)					) + list(range(ord("¡"					)       ,      ord("¬"					) + 1					)					) + list(range(ord("®"					)       ,      ord("ÿ"					) + 1					)					)
       )
       snake_case :     List[str]           =   bs[:]
       snake_case :     Dict           =   0
       for b in range(2**8					):
              if b not in bs:
                     bs.append(__lowerCamelCase					)
                     cs.append(2**8 + n					)
                     n += 1
       snake_case :     List[str]           =   [chr(__lowerCamelCase					) for n in cs]
       return dict(zip(__lowerCamelCase       ,      __lowerCamelCase					)					)


def     UpperCamelCase      (					__lowerCamelCase  :				Dict					):
       snake_case :     Dict           =   set()
       snake_case :     List[str]           =   word[0]
       for char in word[1:]:
              pairs.add((prev_char, char)					)
              snake_case :     Dict           =   char
       return pairs






class 						UpperCAmelCase	(		A_				):
   A__      :	Any		  =  VOCAB_FILES_NAMES
   A__      :	Dict		  =  PRETRAINED_VOCAB_FILES_MAP
   A__      :	Tuple		  =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   A__      :	Tuple		  =  ["input_ids", "attention_mask", "token_type_ids"]



   def __init__(self	:      List[str]					,		snake_case__	:      Optional[int]					,		snake_case__	:      Tuple					,		snake_case__	:      int="replace"					,		snake_case__	:      Any="[CLS]"					,		snake_case__	:      Dict="[SEP]"					,		snake_case__	:      Any="[SEP]"					,		snake_case__	:      Union[str, Any]="[CLS]"					,		snake_case__	:      Dict="[UNK]"					,		snake_case__	:      Optional[Any]="[PAD]"					,		snake_case__	:      int="[MASK]"					,		snake_case__	:      Optional[Any]=False					,		snake_case__	:      List[Any]=False					,		**snake_case__	:      str					,		)	->			Tuple:


          '''simple docstring'''


          snake_case :     str           =   AddedToken(snake_case__					,		lstrip=snake_case__					,		rstrip=snake_case__				) if isinstance(snake_case__					,		snake_case__				) else bos_token
          snake_case :     Optional[Any]           =   AddedToken(snake_case__					,		lstrip=snake_case__					,		rstrip=snake_case__				) if isinstance(snake_case__					,		snake_case__				) else eos_token
          snake_case :     Tuple           =   AddedToken(snake_case__					,		lstrip=snake_case__					,		rstrip=snake_case__				) if isinstance(snake_case__					,		snake_case__				) else sep_token
          snake_case :     Any           =   AddedToken(snake_case__					,		lstrip=snake_case__					,		rstrip=snake_case__				) if isinstance(snake_case__					,		snake_case__				) else cls_token
          snake_case :     List[Any]           =   AddedToken(snake_case__					,		lstrip=snake_case__					,		rstrip=snake_case__				) if isinstance(snake_case__					,		snake_case__				) else unk_token
          snake_case :     Optional[int]           =   AddedToken(snake_case__					,		lstrip=snake_case__					,		rstrip=snake_case__				) if isinstance(snake_case__					,		snake_case__				) else pad_token

          # Mask token behave like a normal word, i.e. include the space before it
          snake_case :     Union[str, Any]           =   AddedToken(snake_case__					,		lstrip=snake_case__					,		rstrip=snake_case__				) if isinstance(snake_case__					,		snake_case__				) else mask_token

          super().__init__(
              errors=snake_case__					,		bos_token=snake_case__					,		eos_token=snake_case__					,		unk_token=snake_case__					,		sep_token=snake_case__					,		cls_token=snake_case__					,		pad_token=snake_case__					,		mask_token=snake_case__					,		add_prefix_space=snake_case__					,		add_bos_token=snake_case__					,		**snake_case__					,		)
          snake_case :     Any           =   add_bos_token

          with open(snake_case__					,		encoding="utf-8"				) as vocab_handle:
                 snake_case :     Optional[int]           =   json.load(snake_case__				)
          snake_case :     Optional[int]           =   {v: k for k, v in self.encoder.items()}
          snake_case :     Optional[Any]           =   errors  # how to handle errors in decoding
          snake_case :     int           =   bytes_to_unicode()
          snake_case :     Union[str, Any]           =   {v: k for k, v in self.byte_encoder.items()}
          with open(snake_case__					,		encoding="utf-8"				) as merges_handle:
                 snake_case :     Tuple           =   merges_handle.read().split("\n"				)[1:-1]
          snake_case :     str           =   [tuple(merge.split()				) for merge in bpe_merges]
          snake_case :     Tuple           =   dict(zip(snake_case__					,		range(len(snake_case__				)				)				)				)
          snake_case :     Union[str, Any]           =   {}
          snake_case :     str           =   add_prefix_space

          # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
          snake_case :     Tuple           =   re.compile(R"'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"				)



   @property
   # Copied from transformers.models.gpt2.tokenization_gpt2.GPT2Tokenizer.vocab_size
   def        _SCREAMING_SNAKE_CASE     (self	:      List[str]				)	->			Union[str, Any]:


          '''simple docstring'''


          return len(self.encoder				)



   def        _SCREAMING_SNAKE_CASE     (self	:      Tuple				)	->			Dict:


          '''simple docstring'''


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



   def        _SCREAMING_SNAKE_CASE     (self	:      Dict					,		snake_case__	:      Union[str, Any]				)	->			List[str]:


          '''simple docstring'''


          if token in self.cache:
                 return self.cache[token]
          snake_case :     Dict           =   tuple(snake_case__				)
          snake_case :     Union[str, Any]           =   get_pairs(snake_case__				)

          if not pairs:
                 return token

          while True:
                 snake_case :     Tuple           =   min(snake_case__					,		key=lambda snake_case__				: self.bpe_ranks.get(snake_case__					,		float("inf"				)				)				)
                 if bigram not in self.bpe_ranks:
                        break
                 snake_case       ,      snake_case :     Optional[int]           =   bigram
                 snake_case :     Optional[Any]           =   []
                 snake_case :     List[str]           =   0
                 while i < len(snake_case__				):
                        try:
                               snake_case :     Optional[Any]           =   word.index(snake_case__					,		snake_case__				)
                        except ValueError:
                               new_word.extend(word[i:]				)
                               break
                        else:
                               new_word.extend(word[i:j]				)
                               snake_case :     Optional[int]           =   j

                        if word[i] == first and i < len(snake_case__				) - 1 and word[i + 1] == second:
                               new_word.append(first + second				)
                               i += 2
                        else:
                               new_word.append(word[i]				)
                               i += 1
                 snake_case :     str           =   tuple(snake_case__				)
                 snake_case :     Optional[Any]           =   new_word
                 if len(snake_case__				) == 1:
                        break
                 else:
                        snake_case :     str           =   get_pairs(snake_case__				)
          snake_case :     Tuple           =   " ".join(snake_case__				)
          snake_case :     List[Any]           =   word
          return word



   def        _SCREAMING_SNAKE_CASE     (self	:      Any					,		snake_case__	:      List[int]					,		snake_case__	:      Optional[List[int]] = None				)	->			List[int]:


          '''simple docstring'''


          if token_ids_a is None:
                 return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
          snake_case :     Dict           =   [self.cls_token_id]
          snake_case :     Optional[Any]           =   [self.sep_token_id]
          return cls + token_ids_a + sep + token_ids_a + sep



   def        _SCREAMING_SNAKE_CASE     (self	:      Union[str, Any]					,		snake_case__	:      List[int]					,		snake_case__	:      Optional[List[int]] = None					,		snake_case__	:      bool = False				)	->			List[int]:


          '''simple docstring'''


          if already_has_special_tokens:
                 return super().get_special_tokens_mask(
                     token_ids_a=snake_case__					,		token_ids_a=snake_case__					,		already_has_special_tokens=snake_case__				)

          if token_ids_a is None:
                 return [1] + ([0] * len(snake_case__				)) + [1]
          return [1] + ([0] * len(snake_case__				)) + [1] + ([0] * len(snake_case__				)) + [1]



   def        _SCREAMING_SNAKE_CASE     (self	:      Optional[int]					,		snake_case__	:      List[int]					,		snake_case__	:      Optional[List[int]] = None				)	->			List[int]:


          '''simple docstring'''


          snake_case :     Any           =   [self.sep_token_id]
          snake_case :     Dict           =   [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				) * [0] + len(token_ids_a + sep				) * [1]



   def        _SCREAMING_SNAKE_CASE     (self	:      Union[str, Any]					,		snake_case__	:      Dict				)	->			Optional[Any]:


          '''simple docstring'''


          snake_case :     List[str]           =   []
          for token in re.findall(self.pat					,		snake_case__				):
                 snake_case :     str           =   "".join(
                     self.byte_encoder[b] for b in token.encode("utf-8"				)				)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
                 bpe_tokens.extend(bpe_token for bpe_token in self.bpe(snake_case__				).split(" "				)				)
          return bpe_tokens



   def        _SCREAMING_SNAKE_CASE     (self	:      Tuple					,		snake_case__	:      Union[str, Any]				)	->			Optional[Any]:


          '''simple docstring'''


          return self.encoder.get(snake_case__					,		self.encoder.get(self.unk_token				)				)



   def        _SCREAMING_SNAKE_CASE     (self	:      List[str]					,		snake_case__	:      Optional[int]				)	->			int:


          '''simple docstring'''


          return self.decoder.get(snake_case__				)



   def        _SCREAMING_SNAKE_CASE     (self	:      List[Any]					,		snake_case__	:      int				)	->			Optional[int]:


          '''simple docstring'''


          snake_case :     List[str]           =   "".join(snake_case__				)
          snake_case :     Tuple           =   bytearray([self.byte_decoder[c] for c in text]				).decode("utf-8"					,		errors=self.errors				)
          return text



   def        _SCREAMING_SNAKE_CASE     (self	:      Any					,		snake_case__	:      str					,		snake_case__	:      Optional[str] = None				)	->			Tuple[str]:


          '''simple docstring'''


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

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

          snake_case :     Optional[int]           =   0
          with open(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 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!"				)
                               snake_case :     List[str]           =   token_index
                        writer.write(" ".join(snake_case__				) + "\n"				)
                        index += 1

          return vocab_file, merge_file



   def        _SCREAMING_SNAKE_CASE     (self	:      int					,		snake_case__	:      str					,		snake_case__	:      Dict=False					,		**snake_case__	:      Union[str, Any]				)	->			Dict:


          '''simple docstring'''


          snake_case :     Tuple           =   kwargs.pop("add_prefix_space"					,		self.add_prefix_space				)
          if (is_split_into_words or add_prefix_space) and (len(snake_case__				) > 0 and not text[0].isspace()):
                 snake_case :     str           =   " " + text
          return (text, kwargs)



   def        _SCREAMING_SNAKE_CASE     (self	:      int					,		snake_case__	:      "Conversation"				)	->			List[int]:


          '''simple docstring'''


          snake_case :     Optional[Any]           =   []
          for is_user, text in conversation.iter_texts():
                 input_ids.extend(self.encode(snake_case__					,		add_special_tokens=snake_case__				) + [self.eos_token_id]				)
          if len(snake_case__				) > self.model_max_length:
                 snake_case :     Dict           =   input_ids[-self.model_max_length :]
          return input_ids







import math
from itertools import permutations


def     UpperCamelCase      (					__lowerCamelCase  :				int					):

       if 1 < number < 4:
              # 2 and 3 are primes
              return True
       elif number < 2 or number % 2 == 0 or number % 3 == 0:
              # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
              return False

       # All primes number are in format of 6k +/- 1
       for i in range(5       ,      int(math.sqrt(__lowerCamelCase					) + 1					)       ,      6					):
              if number % i == 0 or number % (i + 2) == 0:
                     return False
       return True


def     UpperCamelCase      (					__lowerCamelCase  :				int       ,      __lowerCamelCase  :				list					):
       snake_case       ,      snake_case :     List[str]           =   0, len(__lowerCamelCase					) - 1
       while left <= right:
              snake_case :     int           =   (left + right) // 2
              if prime_list[middle] == target:
                     return True
              elif prime_list[middle] < target:
                     snake_case :     Dict           =   middle + 1
              else:
                     snake_case :     Optional[int]           =   middle - 1

       return False


def     UpperCamelCase      (					):
       snake_case :     List[Any]           =   [n for n in range(1001       ,      10000       ,      2					) if is_prime(__lowerCamelCase					)]
       snake_case :     Dict           =   []

       for number in prime_list:
              snake_case :     Dict           =   []

              for prime_member in permutations(list(str(__lowerCamelCase					)					)					):
                     snake_case :     Dict           =   int("".join(__lowerCamelCase					)					)

                     if prime % 2 == 0:
                            continue

                     if search(__lowerCamelCase       ,      __lowerCamelCase					):
                            tmp_numbers.append(__lowerCamelCase					)

              tmp_numbers.sort()
              if len(__lowerCamelCase					) >= 3:
                     candidates.append(__lowerCamelCase					)

       snake_case :     Union[str, Any]           =   []
       for candidate in candidates:
              snake_case :     Dict           =   len(__lowerCamelCase					)
              snake_case :     Any           =   False

              for i in range(__lowerCamelCase					):
                     for j in range(i + 1       ,      __lowerCamelCase					):
                            for k in range(j + 1       ,      __lowerCamelCase					):
                                   if (
                                       abs(candidate[i] - candidate[j]					)
                                       == abs(candidate[j] - candidate[k]					)
                                       and len({candidate[i], candidate[j], candidate[k]}					) == 3
                                   ):
                                          passed.append(
                                              sorted([candidate[i], candidate[j], candidate[k]]					)					)
                                          snake_case :     Optional[Any]           =   True

                                   if found:
                                          break
                            if found:
                                   break
                     if found:
                            break

       snake_case :     Tuple           =   set()
       for seq in passed:
              answer.add("".join([str(__lowerCamelCase					) for i in seq]					)					)

       return max(int(__lowerCamelCase					) for x in answer					)


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





