




'''simple docstring'''


import json
import os
from functools import lru_cache
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

UpperCAmelCase_ 		=      logging.get_logger(__name__)


UpperCAmelCase_ 		=      {
    'vocab_file': 'vocab.json',
    'merges_file': 'merges.txt',
    'tokenizer_config_file': 'tokenizer_config.json',
}

UpperCAmelCase_ 		=      {
    'vocab_file': {'facebook/blenderbot-3B': 'https://huggingface.co/facebook/blenderbot-3B/resolve/main/vocab.json'},
    'merges_file': {'facebook/blenderbot-3B': 'https://huggingface.co/facebook/blenderbot-3B/resolve/main/merges.txt'},
    'tokenizer_config_file': {
        'facebook/blenderbot-3B': 'https://huggingface.co/facebook/blenderbot-3B/resolve/main/tokenizer_config.json'
    },
}

UpperCAmelCase_ 		=      {'facebook/blenderbot-3B': 1_28}


@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def 						SCREAMING_SNAKE_CASE       (      ):
  __a			=					(
      list(range(ord('!'			)				,					ord('~'			) + 1			)			) + list(range(ord('¡'			)				,					ord('¬'			) + 1			)			) + list(range(ord('®'			)				,					ord('ÿ'			) + 1			)			)
  )
  __a			=					bs[:]
  __a			=					0
  for b in range(2**8			):
    if b not in bs:
      bs.append(_lowercase			)
      cs.append(2**8 + n			)
      n += 1
  __a			=					[chr(_lowercase			) for n in cs]
  return dict(zip(_lowercase				,					_lowercase			)			)


def 						SCREAMING_SNAKE_CASE       (      a_	:							Optional[int]			):
  __a			=					set()
  __a			=					word[0]
  for char in word[1:]:
    pairs.add((prev_char, char)			)
    __a			=					char
  return pairs





class     __lowercase						(  UpperCamelCase_ ):
   _a							=      VOCAB_FILES_NAMES
   _a							=      PRETRAINED_VOCAB_FILES_MAP
   _a							=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   _a							=      ["""input_ids""", """attention_mask"""]







   def __init__(	self      ,							UpperCamelCase      ,							UpperCamelCase      ,							UpperCamelCase="replace"      ,							UpperCamelCase="<s>"      ,							UpperCamelCase="</s>"      ,							UpperCamelCase="</s>"      ,							UpperCamelCase="<s>"      ,							UpperCamelCase="<unk>"      ,							UpperCamelCase="<pad>"      ,							UpperCamelCase="<mask>"      ,							UpperCamelCase=False      ,							**UpperCamelCase      ,							)				->    Optional[Any]:
     __a			=					AddedToken(UpperCamelCase__      ,							lstrip=UpperCamelCase__      ,							rstrip=UpperCamelCase__      ) if isinstance(UpperCamelCase__      ,							UpperCamelCase__      ) else bos_token
     __a			=					AddedToken(UpperCamelCase__      ,							lstrip=UpperCamelCase__      ,							rstrip=UpperCamelCase__      ) if isinstance(UpperCamelCase__      ,							UpperCamelCase__      ) else eos_token
     __a			=					AddedToken(UpperCamelCase__      ,							lstrip=UpperCamelCase__      ,							rstrip=UpperCamelCase__      ) if isinstance(UpperCamelCase__      ,							UpperCamelCase__      ) else sep_token
     __a			=					AddedToken(UpperCamelCase__      ,							lstrip=UpperCamelCase__      ,							rstrip=UpperCamelCase__      ) if isinstance(UpperCamelCase__      ,							UpperCamelCase__      ) else cls_token
     __a			=					AddedToken(UpperCamelCase__      ,							lstrip=UpperCamelCase__      ,							rstrip=UpperCamelCase__      ) if isinstance(UpperCamelCase__      ,							UpperCamelCase__      ) else unk_token
     __a			=					AddedToken(UpperCamelCase__      ,							lstrip=UpperCamelCase__      ,							rstrip=UpperCamelCase__      ) if isinstance(UpperCamelCase__      ,							UpperCamelCase__      ) else pad_token

     # Mask token behave like a normal word, i.e. include the space before it
     __a			=					AddedToken(UpperCamelCase__      ,							lstrip=UpperCamelCase__      ,							rstrip=UpperCamelCase__      ) if isinstance(UpperCamelCase__      ,							UpperCamelCase__      ) else mask_token

     super().__init__(
         errors=UpperCamelCase__      ,							bos_token=UpperCamelCase__      ,							eos_token=UpperCamelCase__      ,							unk_token=UpperCamelCase__      ,							sep_token=UpperCamelCase__      ,							cls_token=UpperCamelCase__      ,							pad_token=UpperCamelCase__      ,							mask_token=UpperCamelCase__      ,							add_prefix_space=UpperCamelCase__      ,							**UpperCamelCase__      ,							)

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

     # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
     __a			=					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.roberta.tokenization_roberta.RobertaTokenizer.vocab_size with Roberta->Blenderbot, RoBERTa->Blenderbot
   def 		UpperCamelCase__			(	self      )				->    Any:
     return len(self.encoder      )







   def 		UpperCamelCase__			(	self      )				->    Tuple:
     return dict(self.encoder      ,							**self.added_tokens_encoder      )







   def 		UpperCamelCase__			(	self      ,							UpperCamelCase      )				->    Tuple:





     if token in self.cache:
       return self.cache[token]
     __a			=					tuple(UpperCamelCase__      )
     __a			=					get_pairs(UpperCamelCase__      )

     if not pairs:
       return token

     while True:
       __a			=					min(UpperCamelCase__      ,							key=lambda UpperCamelCase      : self.bpe_ranks.get(UpperCamelCase__      ,							float('inf'      )      )      )
       if bigram not in self.bpe_ranks:
         break
       __a			=					bigram
       __a			=					[]
       __a			=					0
       while i < len(UpperCamelCase__      ):
         try:
           __a			=					word.index(UpperCamelCase__      ,							UpperCamelCase__      )
         except ValueError:
           new_word.extend(word[i:]      )
           break
         else:
           new_word.extend(word[i:j]      )
           __a			=					j

         if word[i] == first and i < len(UpperCamelCase__      ) - 1 and word[i + 1] == second:
           new_word.append(first + second      )
           i += 2
         else:
           new_word.append(word[i]      )
           i += 1
       __a			=					tuple(UpperCamelCase__      )
       __a			=					new_word
       if len(UpperCamelCase__      ) == 1:
         break
       else:
         __a			=					get_pairs(UpperCamelCase__      )
     __a			=					''' '''.join(UpperCamelCase__      )
     __a			=					word
     return word







   def 		UpperCamelCase__			(	self      ,							UpperCamelCase      )				->    Optional[Any]:
     __a			=					[]
     for token in re.findall(self.pat      ,							UpperCamelCase__      ):
       __a			=					''''''.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(UpperCamelCase__      ).split(' '      )      )
     return bpe_tokens







   def 		UpperCamelCase__			(	self      ,							UpperCamelCase      )				->    int:
     return self.encoder.get(UpperCamelCase__      ,							self.encoder.get(self.unk_token      )      )







   def 		UpperCamelCase__			(	self      ,							UpperCamelCase      )				->    Optional[int]:
     return self.decoder.get(UpperCamelCase__      )







   def 		UpperCamelCase__			(	self      ,							UpperCamelCase      )				->    Any:
     __a			=					''''''.join(UpperCamelCase__      )
     __a			=					bytearray([self.byte_decoder[c] for c in text]      ).decode('utf-8'      ,							errors=self.errors      )
     return text







   def 		UpperCamelCase__			(	self      ,							UpperCamelCase      ,							UpperCamelCase = None      )				->    Union[str, Any]:





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

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

     __a			=					0
     with open(UpperCamelCase__      ,							'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 UpperCamelCase      : 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!'      )
           __a			=					token_index
         writer.write(' '.join(UpperCamelCase__      ) + '\n'      )
         index += 1

     return vocab_file, merge_file







   def 		UpperCamelCase__			(	self      ,							UpperCamelCase      ,							UpperCamelCase = None      ,							UpperCamelCase = False      )				->    List[Any]:





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

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







   def 		UpperCamelCase__			(	self      ,							UpperCamelCase      ,							UpperCamelCase = None      )				->    Any:
     __a			=					[self.sep_token_id]
     __a			=					[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 + sep + token_ids_a + sep      ) * [0]







   def 		UpperCamelCase__			(	self      ,							UpperCamelCase      ,							UpperCamelCase=False      ,							**UpperCamelCase      )				->    str:
     __a			=					kwargs.pop('add_prefix_space'      ,							self.add_prefix_space      )
     if (is_split_into_words or add_prefix_space) and (len(UpperCamelCase__      ) > 0 and not text[0].isspace()):
       __a			=					''' ''' + text
     return (text, kwargs)







   def 		UpperCamelCase__			(	self      ,							UpperCamelCase      ,							UpperCamelCase = None      )				->    Union[str, Any]:
     return token_ids_a + [self.eos_token_id]







   def 		UpperCamelCase__			(	self      ,							UpperCamelCase      )				->    str:
     __a			=					[]
     for is_user, text in conversation.iter_texts():
       if is_user:
         # We need to space prefix as it's being done within blenderbot
         inputs.append(' ' + text      )
       else:
         # Generated responses should contain them already.
         inputs.append(UpperCamelCase__      )

     __a			=					'''  '''.join(UpperCamelCase__      )
     __a			=					self.encode(UpperCamelCase__      )
     if len(UpperCamelCase__      ) > self.model_max_length:
       __a			=					input_ids[-self.model_max_length :]
       logger.warning(f"Trimmed input from conversation as it was longer than {self.model_max_length} tokens."      )
     return input_ids









'''simple docstring'''


def 						SCREAMING_SNAKE_CASE       (      a_	:							int			):
  __a			=					0
  while num > 0:
    digit_sum += num % 10
    num //= 10
  return digit_sum


def 						SCREAMING_SNAKE_CASE       (      a_	:							int = 100			):
  __a			=					1
  __a			=					2

  for i in range(2				,					max_n + 1			):
    __a			=					pre_numerator
    __a			=					2 * i // 3 if i % 3 == 0 else 1
    __a			=					cur_numerator
    __a			=					e_cont * pre_numerator + temp

  return sum_digits(a_			)


if __name__ == "__main__":
  print(f"""{solution() = }""")



