

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

snake_case_							=			logging.get_logger(__name__)


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

snake_case_							=			{
    '''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'''
    },
}

snake_case_							=			{'''facebook/blenderbot-3B''': 1_2_8}


@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def 					A__	(       )   ->     List[str]:
		lowerCamelCase   : Any								=(
		    list(range(ord('''!'''		)							,       ord('''~'''		) + 1		)		) + list(range(ord('''¡'''		)							,       ord('''¬'''		) + 1		)		) + list(range(ord('''®'''		)							,       ord('''ÿ'''		) + 1		)		)
		)
		lowerCamelCase   : Dict								=bs[:]
		lowerCamelCase   : Tuple								=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   : Dict								=[chr(SCREAMING_SNAKE_CASE_		) for n in cs]
		return dict(zip(SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		)		)


def 					A__	(       SCREAMING_SNAKE_CASE_		)   ->     List[Any]:
		lowerCamelCase   : Optional[Any]								=set()
		lowerCamelCase   : List[Any]								=word[0]
		for char in word[1:]:
				pairs.add((prev_char, char)		)
				lowerCamelCase   : Any								=char
		return pairs



class        snake_case_		(			_A):
		lowerCamelCase    :str						=     VOCAB_FILES_NAMES
		lowerCamelCase    :List[str]						=     PRETRAINED_VOCAB_FILES_MAP
		lowerCamelCase    :Optional[int]						=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		lowerCamelCase    :Union[str, Any]						=     ["input_ids", "attention_mask"]







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

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

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

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

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







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







		def 			__lowercase   (		self			,     __lowercase   )				->   Dict:
				if token in self.cache:
						return self.cache[token]
				lowerCamelCase   : Tuple								=tuple(__lowercase   )
				lowerCamelCase   : List[Any]								=get_pairs(__lowercase   )

				if not pairs:
						return token

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

								if word[i] == first and i < len(__lowercase   ) - 1 and word[i + 1] == second:
										new_word.append(first + second   )
										i += 2
								else:
										new_word.append(word[i]   )
										i += 1
						lowerCamelCase   : Tuple								=tuple(__lowercase   )
						lowerCamelCase   : Any								=new_word
						if len(__lowercase   ) == 1:
								break
						else:
								lowerCamelCase   : Dict								=get_pairs(__lowercase   )
				lowerCamelCase   : Optional[int]								=''' '''.join(__lowercase   )
				lowerCamelCase   : Union[str, Any]								=word
				return word







		def 			__lowercase   (		self			,     __lowercase   )				->   Dict:
				lowerCamelCase   : Dict								=[]
				for token in re.findall(self.pat			,     __lowercase   ):
						lowerCamelCase   : Union[str, 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(__lowercase   ).split(''' '''   )   )
				return bpe_tokens







		def 			__lowercase   (		self			,     __lowercase   )				->   Any:
				return self.encoder.get(__lowercase			,     self.encoder.get(self.unk_token   )   )







		def 			__lowercase   (		self			,     __lowercase   )				->   List[str]:
				return self.decoder.get(__lowercase   )







		def 			__lowercase   (		self			,     __lowercase   )				->   Any:
				lowerCamelCase   : Tuple								=''''''.join(__lowercase   )
				lowerCamelCase   : str								=bytearray([self.byte_decoder[c] for c in text]   ).decode('''utf-8'''			,     errors=self.errors   )
				return text







		def 			__lowercase   (		self			,     __lowercase			,     __lowercase = None   )				->   Tuple[str]:
				if not os.path.isdir(__lowercase   ):
						logger.error(F"Vocabulary path ({save_directory}) should be a directory"   )
						return
				lowerCamelCase   : Tuple								=os.path.join(
				    __lowercase			,     (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']   )
				lowerCamelCase   : int								=os.path.join(
				    __lowercase			,     (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file''']   )

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

				lowerCamelCase   : Dict								=0
				with open(__lowercase			,     '''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 __lowercase   : 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   : Optional[Any]								=token_index
								writer.write(''' '''.join(__lowercase   ) + '''\n'''   )
								index += 1

				return vocab_file, merge_file







		def 			__lowercase   (		self			,     __lowercase			,     __lowercase = None			,     __lowercase = False   )				->   List[int]:
				if already_has_special_tokens:
						return super().get_special_tokens_mask(
						    token_ids_a=__lowercase			,     token_ids_a=__lowercase			,     already_has_special_tokens=__lowercase   )

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







		def 			__lowercase   (		self			,     __lowercase			,     __lowercase = None   )				->   List[int]:
				lowerCamelCase   : List[str]								=[self.sep_token_id]
				lowerCamelCase   : List[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 			__lowercase   (		self			,     __lowercase			,     __lowercase=False			,     **__lowercase   )				->   List[Any]:
				lowerCamelCase   : List[Any]								=kwargs.pop('''add_prefix_space'''			,     self.add_prefix_space   )
				if (is_split_into_words or add_prefix_space) and (len(__lowercase   ) > 0 and not text[0].isspace()):
						lowerCamelCase   : int								=''' ''' + text
				return (text, kwargs)







		def 			__lowercase   (		self			,     __lowercase			,     __lowercase = None   )				->   str:
				return token_ids_a + [self.eos_token_id]







		def 			__lowercase   (		self			,     __lowercase   )				->   List[int]:
				lowerCamelCase   : Tuple								=[]
				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(__lowercase   )

				lowerCamelCase   : Optional[Any]								='''  '''.join(__lowercase   )
				lowerCamelCase   : Optional[int]								=self.encode(__lowercase   )
				if len(__lowercase   ) > self.model_max_length:
						lowerCamelCase   : Any								=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








from collections import defaultdict
from math import ceil, sqrt


def 					A__	(       SCREAMING_SNAKE_CASE_ = 1_0_0_0_0_0_0							,       SCREAMING_SNAKE_CASE_ = 1_0		)   ->     int:
		lowerCamelCase   : defaultdict								=defaultdict(SCREAMING_SNAKE_CASE_		)

		for outer_width in range(3							,       (t_limit // 4) + 2		):
				if outer_width * outer_width > t_limit:
						lowerCamelCase   : Any								=max(
						    ceil(sqrt(outer_width * outer_width - t_limit		)		)							,       1		)
				else:
						lowerCamelCase   : str								=1

				hole_width_lower_bound += (outer_width - hole_width_lower_bound) % 2

				for hole_width in range(SCREAMING_SNAKE_CASE_							,       outer_width - 1							,       2		):
						count[outer_width * outer_width - hole_width * hole_width] += 1

		return sum(1 for n in count.values() if 1 <= n <= 1_0		)


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

