





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				:       Optional[int]	   =				logging.get_logger(__name__)


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

_UpperCAmelCase				:       Any	   =				{
    """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				:       str	   =				{"""facebook/blenderbot-3B""": 1_28}


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


def        SCREAMING_SNAKE_CASE      (       _UpperCAmelCase )			->     Optional[int]:
    lowerCamelCase__    :      Union[str, Any]					 =		set()
    lowerCamelCase__    :      List[Any]					 =		word[0]
    for char in word[1:]:
        pairs.add((prev_char, char) )
        lowerCamelCase__    :      Dict					 =		char
    return pairs


class    lowerCAmelCase							(					__UpperCamelCase			):
 UpperCAmelCase__													=		VOCAB_FILES_NAMES
 UpperCAmelCase__													=		PRETRAINED_VOCAB_FILES_MAP
 UpperCAmelCase__													=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 UpperCAmelCase__													=		["""input_ids""", """attention_mask"""]
 def __init__(      self  :      Optional[Any]			,     UpperCAmelCase  :      List[str]			,     UpperCAmelCase  :      Dict			,     UpperCAmelCase  :      Optional[Any]="replace"			,     UpperCAmelCase  :      str="<s>"			,     UpperCAmelCase  :      Tuple="</s>"			,     UpperCAmelCase  :      Dict="</s>"			,     UpperCAmelCase  :      Union[str, Any]="<s>"			,     UpperCAmelCase  :      int="<unk>"			,     UpperCAmelCase  :      Optional[Any]="<pad>"			,     UpperCAmelCase  :      int="<mask>"			,     UpperCAmelCase  :      str=False			,     **UpperCAmelCase  :      Any			,     )			->	Optional[Any]:
     lowerCamelCase__    :      List[str]					 =		AddedToken(UpperCAmelCase			,     lstrip=UpperCAmelCase			,     rstrip=UpperCAmelCase	) if isinstance(UpperCAmelCase			,     UpperCAmelCase	) else bos_token
     lowerCamelCase__    :      Tuple					 =		AddedToken(UpperCAmelCase			,     lstrip=UpperCAmelCase			,     rstrip=UpperCAmelCase	) if isinstance(UpperCAmelCase			,     UpperCAmelCase	) else eos_token
     lowerCamelCase__    :      Dict					 =		AddedToken(UpperCAmelCase			,     lstrip=UpperCAmelCase			,     rstrip=UpperCAmelCase	) if isinstance(UpperCAmelCase			,     UpperCAmelCase	) else sep_token
     lowerCamelCase__    :      Union[str, Any]					 =		AddedToken(UpperCAmelCase			,     lstrip=UpperCAmelCase			,     rstrip=UpperCAmelCase	) if isinstance(UpperCAmelCase			,     UpperCAmelCase	) else cls_token
     lowerCamelCase__    :      Any					 =		AddedToken(UpperCAmelCase			,     lstrip=UpperCAmelCase			,     rstrip=UpperCAmelCase	) if isinstance(UpperCAmelCase			,     UpperCAmelCase	) else unk_token
     lowerCamelCase__    :      List[str]					 =		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__    :      str					 =		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__    :      int					 =		json.load(UpperCAmelCase	)
     lowerCamelCase__    :      List[Any]					 =		{v: k for k, v in self.encoder.items()}
     lowerCamelCase__    :      Tuple					 =		errors  # how to handle errors in decoding
     lowerCamelCase__    :      List[str]					 =		bytes_to_unicode()
     lowerCamelCase__    :      Union[str, Any]					 =		{v: k for k, v in self.byte_encoder.items()}
     with open(UpperCAmelCase			,     encoding='utf-8'	) as merges_handle:
         lowerCamelCase__    :      Any					 =		merges_handle.read().split('\n'	)[1:-1]
     lowerCamelCase__    :      Union[str, Any]					 =		[tuple(merge.split()	) for merge in bpe_merges]
     lowerCamelCase__    :      Tuple					 =		dict(zip(UpperCAmelCase			,     range(len(UpperCAmelCase	)	)	)	)
     lowerCamelCase__    :      Dict					 =		{}
     lowerCamelCase__    :      Optional[Any]					 =		add_prefix_space

     # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
     lowerCamelCase__    :      Optional[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      A_	(      self  :      Any	)			->	Optional[Any]:
     return len(self.encoder	)
 def      A_	(      self  :      Optional[int]	)			->	Optional[Any]:
     return dict(self.encoder			,     **self.added_tokens_encoder	)
 def      A_	(      self  :      Optional[int]			,     UpperCAmelCase  :      Optional[int]	)			->	Optional[Any]:
     if token in self.cache:
         return self.cache[token]
     lowerCamelCase__    :      Union[str, Any]					 =		tuple(UpperCAmelCase	)
     lowerCamelCase__    :      int					 =		get_pairs(UpperCAmelCase	)

     if not pairs:
         return token

     while True:
         lowerCamelCase__    :      List[str]					 =		min(UpperCAmelCase			,     key=lambda UpperCAmelCase	: self.bpe_ranks.get(UpperCAmelCase			,     float('inf'	)	)	)
         if bigram not in self.bpe_ranks:
             break
         lowerCamelCase__ ,							lowerCamelCase__    :      int					 =		bigram
         lowerCamelCase__    :      Optional[Any]					 =		[]
         lowerCamelCase__    :      Union[str, Any]					 =		0
         while i < len(UpperCAmelCase	):
             try:
                 lowerCamelCase__    :      int					 =		word.index(UpperCAmelCase			,     UpperCAmelCase	)
             except ValueError:
                 new_word.extend(word[i:]	)
                 break
             else:
                 new_word.extend(word[i:j]	)
                 lowerCamelCase__    :      Optional[int]					 =		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__    :      str					 =		tuple(UpperCAmelCase	)
         lowerCamelCase__    :      Union[str, Any]					 =		new_word
         if len(UpperCAmelCase	) == 1:
             break
         else:
             lowerCamelCase__    :      Optional[Any]					 =		get_pairs(UpperCAmelCase	)
     lowerCamelCase__    :      int					 =		' '.join(UpperCAmelCase	)
     lowerCamelCase__    :      Tuple					 =		word
     return word
 def      A_	(      self  :      int			,     UpperCAmelCase  :      List[Any]	)			->	Union[str, Any]:
     lowerCamelCase__    :      int					 =		[]
     for token in re.findall(self.pat			,     UpperCAmelCase	):
         lowerCamelCase__    :      List[Any]					 =		''.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      A_	(      self  :      Any			,     UpperCAmelCase  :      List[Any]	)			->	List[Any]:
     return self.encoder.get(UpperCAmelCase			,     self.encoder.get(self.unk_token	)	)
 def      A_	(      self  :      Union[str, Any]			,     UpperCAmelCase  :      Any	)			->	str:
     return self.decoder.get(UpperCAmelCase	)
 def      A_	(      self  :      Optional[Any]			,     UpperCAmelCase  :      int	)			->	int:
     lowerCamelCase__    :      str					 =		''.join(UpperCAmelCase	)
     lowerCamelCase__    :      int					 =		bytearray([self.byte_decoder[c] for c in text]	).decode('utf-8'			,     errors=self.errors	)
     return text
 def      A_	(      self  :      str			,     UpperCAmelCase  :      str			,     UpperCAmelCase  :      Optional[str] = None	)			->	Tuple[str]:
     if not os.path.isdir(UpperCAmelCase	):
         logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""	)
         return
     lowerCamelCase__    :      List[str]					 =		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 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!'	)
                 lowerCamelCase__    :      Union[str, Any]					 =		token_index
             writer.write(' '.join(UpperCAmelCase	) + '\n'	)
             index += 1

     return vocab_file, merge_file
 def      A_	(      self  :      Union[str, Any]			,     UpperCAmelCase  :      List[int]			,     UpperCAmelCase  :      Optional[List[int]] = None			,     UpperCAmelCase  :      bool = False	)			->	List[int]:
     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      A_	(      self  :      str			,     UpperCAmelCase  :      List[int]			,     UpperCAmelCase  :      Optional[List[int]] = None	)			->	List[int]:
     lowerCamelCase__    :      Any					 =		[self.sep_token_id]
     lowerCamelCase__    :      Tuple					 =		[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      A_	(      self  :      int			,     UpperCAmelCase  :      str			,     UpperCAmelCase  :      Optional[Any]=False			,     **UpperCAmelCase  :      List[Any]	)			->	List[Any]:
     lowerCamelCase__    :      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__    :      str					 =		' ' + text
     return (text, kwargs)
 def      A_	(      self  :      List[Any]			,     UpperCAmelCase  :      List[int]			,     UpperCAmelCase  :      Optional[List[int]] = None	)			->	str:
     return token_ids_a + [self.eos_token_id]







 def      A_	(      self  :      Any			,     UpperCAmelCase  :      "Conversation"	)			->	List[int]:
     lowerCamelCase__    :      Union[str, Any]					 =		[]
     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__    :      Optional[Any]					 =		'  '.join(UpperCAmelCase	)
     lowerCamelCase__    :      Union[str, Any]					 =		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












def        SCREAMING_SNAKE_CASE      (       _UpperCAmelCase = 100_0000 )			->     int:
    lowerCamelCase__    :      int					 =		limit + 1
    lowerCamelCase__    :      Optional[Any]					 =		[0] * limit
    for first_term in range(1						,	_UpperCAmelCase ):
        for n in range(_UpperCAmelCase						,	_UpperCAmelCase						,	_UpperCAmelCase ):
            lowerCamelCase__    :      Optional[Any]					 =		first_term + n / first_term
            if common_difference % 4:  # d must be divisble by 4
                continue
            else:
                common_difference /= 4
                if (
                    first_term > common_difference
                    and first_term < 4 * common_difference
                ):  # since x,y,z are positive integers
                    frequency[n] += 1  # so z>0 and a>d ,also 4d<a

    lowerCamelCase__    :      List[str]					 =		sum(1 for x in frequency[1:limit] if x == 10 )

    return count


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





