



"""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

lowerCAmelCase__              =							logging.get_logger(__name__)


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

lowerCAmelCase__              =							{
    '''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'''
    },
}

lowerCAmelCase__              =							{'''facebook/blenderbot-3B''': 128}






@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def 			snake_case_    ( ):


       '''simple docstring'''





       _lowerCamelCase		:							Dict            =					(
           list(range(ord('''!'''		),							ord('''~'''		) + 1		)		) + list(range(ord('''¡'''		),							ord('''¬'''		) + 1		)		) + list(range(ord('''®'''		),							ord('''ÿ'''		) + 1		)		)
       )
       _lowerCamelCase		:							str            =					bs[:]
       _lowerCamelCase		:							Optional[Any]            =					0
       for b in range(2**8		):
              if b not in bs:
                     bs.append(SCREAMING_SNAKE_CASE_		)
                     cs.append(2**8 + n		)
                     n += 1
       _lowerCamelCase		:							Any            =					[chr(SCREAMING_SNAKE_CASE_		) for n in cs]
       return dict(zip(SCREAMING_SNAKE_CASE_,							SCREAMING_SNAKE_CASE_		)		)






def 			snake_case_    ( A_   :						Dict		):


       '''simple docstring'''





       _lowerCamelCase		:							Dict            =					set()
       _lowerCamelCase		:							Optional[int]            =					word[0]
       for char in word[1:]:
              pairs.add((prev_char, char)		)
              _lowerCamelCase		:							Optional[Any]            =					char
       return pairs







class 			__snake_case			(      _a):
  snake_case__							:  int         =		VOCAB_FILES_NAMES
  snake_case__							:  int         =		PRETRAINED_VOCAB_FILES_MAP
  snake_case__							:  Union[str, Any]         =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  snake_case__							:  Optional[int]         =		['''input_ids''', '''attention_mask''']




  def __init__(					self	:		Union[str, Any]		,   __lowerCAmelCase	:		str		,   __lowerCAmelCase	:		Any		,   __lowerCAmelCase	:		List[Any]="replace"		,   __lowerCAmelCase	:		Tuple="<s>"		,   __lowerCAmelCase	:		int="</s>"		,   __lowerCAmelCase	:		Optional[int]="</s>"		,   __lowerCAmelCase	:		str="<s>"		,   __lowerCAmelCase	:		Dict="<unk>"		,   __lowerCAmelCase	:		Tuple="<pad>"		,   __lowerCAmelCase	:		Tuple="<mask>"		,   __lowerCAmelCase	:		Optional[int]=False		,   **__lowerCAmelCase	:		List[Any]		,   ):






         """simple docstring"""






         _lowerCamelCase		:							Optional[Any]            =					AddedToken(__UpperCamelCase		,   lstrip=__UpperCamelCase		,   rstrip=__UpperCamelCase						) if isinstance(__UpperCamelCase		,   __UpperCamelCase						) else bos_token
         _lowerCamelCase		:							Optional[int]            =					AddedToken(__UpperCamelCase		,   lstrip=__UpperCamelCase		,   rstrip=__UpperCamelCase						) if isinstance(__UpperCamelCase		,   __UpperCamelCase						) else eos_token
         _lowerCamelCase		:							Tuple            =					AddedToken(__UpperCamelCase		,   lstrip=__UpperCamelCase		,   rstrip=__UpperCamelCase						) if isinstance(__UpperCamelCase		,   __UpperCamelCase						) else sep_token
         _lowerCamelCase		:							str            =					AddedToken(__UpperCamelCase		,   lstrip=__UpperCamelCase		,   rstrip=__UpperCamelCase						) if isinstance(__UpperCamelCase		,   __UpperCamelCase						) else cls_token
         _lowerCamelCase		:							List[Any]            =					AddedToken(__UpperCamelCase		,   lstrip=__UpperCamelCase		,   rstrip=__UpperCamelCase						) if isinstance(__UpperCamelCase		,   __UpperCamelCase						) else unk_token
         _lowerCamelCase		:							Union[str, Any]            =					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
         _lowerCamelCase		:							Dict            =					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:
                _lowerCamelCase		:							List[Any]            =					json.load(__UpperCamelCase						)
         _lowerCamelCase		:							Tuple            =					{v: k for k, v in self.encoder.items()}
         _lowerCamelCase		:							Union[str, Any]            =					errors  # how to handle errors in decoding
         _lowerCamelCase		:							List[Any]            =					bytes_to_unicode()
         _lowerCamelCase		:							Optional[Any]            =					{v: k for k, v in self.byte_encoder.items()}
         with open(__UpperCamelCase		,   encoding='''utf-8'''						) as merges_handle:
                _lowerCamelCase		:							List[Any]            =					merges_handle.read().split('''\n'''						)[1:-1]
         _lowerCamelCase		:							Any            =					[tuple(merge.split()						) for merge in bpe_merges]
         _lowerCamelCase		:							int            =					dict(zip(__UpperCamelCase		,   range(len(__UpperCamelCase						)						)						)						)
         _lowerCamelCase		:							Dict            =					{}
         _lowerCamelCase		:							str            =					add_prefix_space

         # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
         _lowerCamelCase		:							List[Any]            =					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 		SCREAMING_SNAKE_CASE							(					self	:		List[str]						):






         """simple docstring"""






         return len(self.encoder						)




  def 		SCREAMING_SNAKE_CASE							(					self	:		Tuple						):






         """simple docstring"""






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




  def 		SCREAMING_SNAKE_CASE							(					self	:		Any		,   __lowerCAmelCase	:		Union[str, Any]						):






         """simple docstring"""






         if token in self.cache:
                return self.cache[token]
         _lowerCamelCase		:							Any            =					tuple(__UpperCamelCase						)
         _lowerCamelCase		:							Union[str, Any]            =					get_pairs(__UpperCamelCase						)

         if not pairs:
                return token

         while True:
                _lowerCamelCase		:							Optional[Any]            =					min(__UpperCamelCase		,   key=lambda __lowerCAmelCase						: self.bpe_ranks.get(__UpperCamelCase		,   float('''inf'''						)						)						)
                if bigram not in self.bpe_ranks:
                       break
                _lowerCamelCase     ,       _lowerCamelCase		:							Optional[Any]            =					bigram
                _lowerCamelCase		:							int            =					[]
                _lowerCamelCase		:							Union[str, Any]            =					0
                while i < len(__UpperCamelCase						):
                       try:
                              _lowerCamelCase		:							Union[str, Any]            =					word.index(__UpperCamelCase		,   __UpperCamelCase						)
                       except ValueError:
                              new_word.extend(word[i:]						)
                              break
                       else:
                              new_word.extend(word[i:j]						)
                              _lowerCamelCase		:							Any            =					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
                _lowerCamelCase		:							List[str]            =					tuple(__UpperCamelCase						)
                _lowerCamelCase		:							Optional[Any]            =					new_word
                if len(__UpperCamelCase						) == 1:
                       break
                else:
                       _lowerCamelCase		:							Tuple            =					get_pairs(__UpperCamelCase						)
         _lowerCamelCase		:							int            =					''' '''.join(__UpperCamelCase						)
         _lowerCamelCase		:							int            =					word
         return word




  def 		SCREAMING_SNAKE_CASE							(					self	:		str		,   __lowerCAmelCase	:		str						):






         """simple docstring"""






         _lowerCamelCase		:							Dict            =					[]
         for token in re.findall(self.pat		,   __UpperCamelCase						):
                _lowerCamelCase		:							Tuple            =					''''''.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 		SCREAMING_SNAKE_CASE							(					self	:		Optional[int]		,   __lowerCAmelCase	:		List[Any]						):






         """simple docstring"""






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




  def 		SCREAMING_SNAKE_CASE							(					self	:		int		,   __lowerCAmelCase	:		Union[str, Any]						):






         """simple docstring"""






         return self.decoder.get(__UpperCamelCase						)




  def 		SCREAMING_SNAKE_CASE							(					self	:		Optional[Any]		,   __lowerCAmelCase	:		Optional[Any]						):






         """simple docstring"""






         _lowerCamelCase		:							int            =					''''''.join(__UpperCamelCase						)
         _lowerCamelCase		:							Union[str, Any]            =					bytearray([self.byte_decoder[c] for c in text]						).decode('''utf-8'''		,   errors=self.errors						)
         return text




  def 		SCREAMING_SNAKE_CASE							(					self	:		Optional[Any]		,   __lowerCAmelCase	:		List[str]		,   __lowerCAmelCase	:		str = None						):






         """simple docstring"""






         if not os.path.isdir(__UpperCamelCase						):
                logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''						)
                return
         _lowerCamelCase		:							Dict            =					os.path.join(
             __UpperCamelCase		,   (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']						)
         _lowerCamelCase		:							Union[str, Any]            =					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'''						)

         _lowerCamelCase		:							Any            =					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 __lowerCAmelCase						: 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!'''						)
                              _lowerCamelCase		:							Union[str, Any]            =					token_index
                       writer.write(''' '''.join(__UpperCamelCase						) + '''\n'''						)
                       index += 1

         return vocab_file, merge_file




  def 		SCREAMING_SNAKE_CASE							(					self	:		Any		,   __lowerCAmelCase	:		Union[str, Any]		,   __lowerCAmelCase	:		str = None		,   __lowerCAmelCase	:		Tuple = False						):






         """simple docstring"""






         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 		SCREAMING_SNAKE_CASE							(					self	:		str		,   __lowerCAmelCase	:		Optional[int]		,   __lowerCAmelCase	:		Dict = None						):






         """simple docstring"""






         _lowerCamelCase		:							Optional[int]            =					[self.sep_token_id]
         _lowerCamelCase		:							Any            =					[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 		SCREAMING_SNAKE_CASE							(					self	:		Union[str, Any]		,   __lowerCAmelCase	:		Optional[Any]		,   __lowerCAmelCase	:		List[Any]=False		,   **__lowerCAmelCase	:		Optional[int]						):






         """simple docstring"""






         _lowerCamelCase		:							Optional[Any]            =					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()):
                _lowerCamelCase		:							List[Any]            =					''' ''' + text
         return (text, kwargs)




  def 		SCREAMING_SNAKE_CASE							(					self	:		Any		,   __lowerCAmelCase	:		List[Any]		,   __lowerCAmelCase	:		Any = None						):






         """simple docstring"""






         return token_ids_a + [self.eos_token_id]




  def 		SCREAMING_SNAKE_CASE							(					self	:		Any		,   __lowerCAmelCase	:		Optional[int]						):






         """simple docstring"""






         _lowerCamelCase		:							Dict            =					[]
         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						)

         _lowerCamelCase		:							List[str]            =					'''  '''.join(__UpperCamelCase						)
         _lowerCamelCase		:							int            =					self.encode(__UpperCamelCase						)
         if len(__UpperCamelCase						) > self.model_max_length:
                _lowerCamelCase		:							List[str]            =					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




import os

# Precomputes a list of the 100 first triangular numbers
A		: List[Any]								=     [int(0.5 * n * (n + 1)) for n in range(1, 101)]




def 	UpperCamelCase__  (     )  ->     str:
						_lowercase					       =					os.path.dirname(os.path.realpath(SCREAMING_SNAKE_CASE_       )       )
						_lowercase					       =					os.path.join(SCREAMING_SNAKE_CASE_		,   """words.txt"""       )

						_lowercase					       =					""""""
						with open(SCREAMING_SNAKE_CASE_       ) as f:
												_lowercase					       =					f.readline()

						_lowercase					       =					[word.strip("""\""""       ) for word in words.strip("""\r\n"""       ).split(""","""       )]
						_lowercase					       =					[
						    word
						    for word in [sum(ord(SCREAMING_SNAKE_CASE_       ) - 64 for x in word       ) for word in words]
						    if word in TRIANGULAR_NUMBERS
						]
						return len(SCREAMING_SNAKE_CASE_       )


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