






"""simple docstring"""




from itertools import combinations, product

def     lowerCAmelCase__  (  UpperCamelCase__  ,     UpperCamelCase__  ,     UpperCamelCase__  ,     UpperCamelCase__       ):



		'''simple docstring'''
		if xa == ya == 0 or xa == ya == 0:
				return False
		_a						: str    =			xa * xa + ya * ya
		_a						: Any    =			xa * xa + ya * ya
		_a						: Optional[Any]    =			(xa - xa) * (xa - xa) + (ya - ya) * (ya - ya)
		return (
		    a_square + b_square == c_square
		    or a_square + c_square == b_square
		    or b_square + c_square == a_square
		)

def     lowerCAmelCase__  (  UpperCamelCase__ = 5_0       ):



		'''simple docstring'''
		return sum(
		    1
		    for pta, pta in combinations(product(range(limit + 1       )  ,     repeat=2       )  ,     2       )
		    if is_right(*UpperCamelCase__  ,     *UpperCamelCase__       )       )


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









"""simple docstring"""




import os
from shutil import copyfile
from typing import TYPE_CHECKING, Optional, Tuple

from tokenizers import processors

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
from ...utils.versions import require_version


if TYPE_CHECKING:
 from transformers.pipelines.conversational import Conversation

require_version('tokenizers>=0.13.3')

if is_sentencepiece_available():
 from .tokenization_llama import LlamaTokenizer
else:
 _snake_case					   =     None

_snake_case					   =     logging.get_logger(__name__)
_snake_case					   =     {'vocab_file': 'tokenizer.model', 'tokenizer_file': 'tokenizer.json'}

_snake_case   ,				_snake_case					   =     '[INST]', '[/INST]'
_snake_case   ,				_snake_case					   =     '<<SYS>>\n', '\n<</SYS>>\n\n'

# fmt: off
_snake_case					   =     'You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your\\nanswers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure\\nthat your responses are socially unbiased and positive in nature.\n\nIf a question does not make any sense, or is not factually coherent, explain why instead of answering something not\\ncorrect. If you don\'t know the answer to a question, please don\'t share false information.'






class  UpperCamelCase    (			snake_case_   ):
 UpperCamelCase      : Any    =      VOCAB_FILES_NAMES
 UpperCamelCase      : Tuple    =      LlamaTokenizer
 UpperCamelCase      : Union[str, Any]    =      '''left'''
 UpperCamelCase      : str    =      ['''input_ids''', '''attention_mask''']


 def __init__(  self	:		Union[str, Any]							,		UpperCAmelCase__	:		Optional[int]=None							,		UpperCAmelCase__	:		Dict=None							,		UpperCAmelCase__	:		Optional[int]=False							,		UpperCAmelCase__	:		Optional[Any]="<unk>"							,		UpperCAmelCase__	:		str="<s>"							,		UpperCAmelCase__	:		List[Any]="</s>"							,		UpperCAmelCase__	:		Tuple=True							,		UpperCAmelCase__	:		int=False							,		**UpperCAmelCase__	:		Tuple							,		)      -> Dict:
   super().__init__(
       vocab_file=UpperCAmelCase__							,		tokenizer_file=UpperCAmelCase__							,		clean_up_tokenization_spaces=UpperCAmelCase__							,		unk_token=UpperCAmelCase__							,		bos_token=UpperCAmelCase__							,		eos_token=UpperCAmelCase__							,		**UpperCAmelCase__							,		)
   _a						: List[str]    =			add_bos_token
   _a						: Union[str, Any]    =			add_eos_token
   self.update_post_processor()

   _a						: List[str]    =			vocab_file
   _a						: Union[str, Any]    =			False if not self.vocab_file else True


 def _lowercase			(  self	:		List[str]							)      -> int:
   _a						: Dict    =			self.bos_token
   _a						: Union[str, Any]    =			self.bos_token_id

   _a						: int    =			self.eos_token
   _a						: str    =			self.eos_token_id

   _a						: Optional[Any]    =			f"""{(bos+':0 ') * self.add_bos_token}$A:0{(' '+eos+':0') * self.add_eos_token}"""
   _a						: str    =			f"""{single}{(' '+bos+':1') * self.add_bos_token} $B:1{(' '+eos+':1') * self.add_eos_token}"""

   _a						: Optional[int]    =			[]
   if self.add_bos_token:
     special_tokens.append((bos, bos_token_id)							)
   if self.add_eos_token:
     special_tokens.append((eos, eos_token_id)							)
   _a						: str    =			processors.TemplateProcessing(
       single=UpperCAmelCase__							,		pair=UpperCAmelCase__							,		special_tokens=UpperCAmelCase__							)


 @property
 def _lowercase			(  self	:		Optional[int]							)      -> Optional[Any]:
   return self._add_eos_token


 @property
 def _lowercase			(  self	:		Dict							)      -> str:
   return self._add_bos_token


 @add_eos_token.setter
 def _lowercase			(  self	:		Any							,		UpperCAmelCase__	:		int							)      -> List[str]:
   _a						: Any    =			value
   self.update_post_processor()


 @add_bos_token.setter
 def _lowercase			(  self	:		Any							,		UpperCAmelCase__	:		int							)      -> List[str]:
   _a						: Optional[Any]    =			value
   self.update_post_processor()


 def _lowercase			(  self	:		Dict							,		UpperCAmelCase__	:		str							,		UpperCAmelCase__	:		Optional[str] = None							)      -> Tuple[str]:
   if not self.can_save_slow_tokenizer:
     raise ValueError(
         """Your fast tokenizer does not have the necessary information to save the vocabulary for a slow """
         """tokenizer."""							)

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

   if os.path.abspath(self.vocab_file							) != os.path.abspath(UpperCAmelCase__							):
     copyfile(self.vocab_file							,		UpperCAmelCase__							)

   return (out_vocab_file,)







 def _lowercase			(  self	:		Tuple							,		UpperCAmelCase__	:		"Conversation"							)      -> Optional[Any]:
   _a						: str    =			list(conversation.iter_texts()							)
   if not all([is_user for is_user, msg in dialogue[::2]]							) or not all(
       [not is_user for is_user, msg in dialogue[1::2]]							):
     raise ValueError(
         """The model only supports 'user' and 'assistant' roles, starting with user and alternating (u/a/u/a/u...)"""							)

   _a						: Tuple    =			[]
   if len(conversation.past_user_inputs							) > 0:
     if not conversation.past_user_inputs[0].startswith(UpperCAmelCase__							) or E_SYS not in conversation.past_user_inputs[0]:
       _a						: Union[str, Any]    =			(
           B_SYS + DEFAULT_SYSTEM_PROMPT + E_SYS + conversation.past_user_inputs[0]
       )
   elif not dialogue[0][1].startswith(UpperCAmelCase__							) or E_SYS not in dialogue[0][1]:
     _a						: str    =			(dialogue[0][0], B_SYS + DEFAULT_SYSTEM_PROMPT + E_SYS + dialogue[0][1])

   dialog_tokens += sum(
       [
           [self.bos_token_id]
           + self.encode(
               f"""{B_INST} {(prompt[1]).strip()} {E_INST} {(answer[1]).strip()} """							,		add_special_tokens=UpperCAmelCase__							)
           + [self.eos_token_id]
           for prompt, answer in zip(dialogue[::2]							,		dialogue[1::2]							)
       ]							,		[]							,		)
   if not (dialogue[-1][0]):
     raise ValueError(f"""Last message must be from user, got {dialogue[-1]['role']}"""							)
   dialog_tokens += [self.bos_token_id] + self.encode(
       f"""{B_INST} {(dialogue[-1][1]).strip()} {E_INST}"""							,		add_special_tokens=UpperCAmelCase__							)
   return dialog_tokens

