


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:
		lowerCamelCase		=						None

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

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

# fmt: off
lowerCamelCase		=						'''You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your\
answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure\
that your responses are socially unbiased and positive in nature.

If a question does not make any sense, or is not factually coherent, explain why instead of answering something not\
correct. If you don\'t know the answer to a question, please don\'t share false information.'''





class    _a				(							_lowercase):
	_a    :    int        =				VOCAB_FILES_NAMES
	_a    :    Union[str, Any]        =				LlamaTokenizer
	_a    :    List[Any]        =				'''left'''
	_a    :    List[Any]        =				['''input_ids''', '''attention_mask''']




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

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




	def 				UpperCAmelCase__(   self		:						str						)->			List[Any]:
			lowerCAmelCase__  :     Optional[int]       	=   self.bos_token
			lowerCAmelCase__  :     Optional[Any]       	=   self.bos_token_id

			lowerCAmelCase__  :     Optional[int]       	=   self.eos_token
			lowerCAmelCase__  :     Optional[Any]       	=   self.eos_token_id

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

			lowerCAmelCase__  :     str       	=   []
			if self.add_bos_token:
					special_tokens.append((bos, bos_token_id)						)
			if self.add_eos_token:
					special_tokens.append((eos, eos_token_id)						)
			lowerCAmelCase__  :     Union[str, Any]       	=   processors.TemplateProcessing(
			    single=_SCREAMING_SNAKE_CASE						,   pair=_SCREAMING_SNAKE_CASE						,   special_tokens=_SCREAMING_SNAKE_CASE						)




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




	@property
	def 				UpperCAmelCase__(   self		:						Optional[Any]						)->			Tuple:
			return self._add_bos_token




	@add_eos_token.setter
	def 				UpperCAmelCase__(   self		:						List[Any]						,   _SCREAMING_SNAKE_CASE		:						Optional[Any]						)->			List[str]:
			lowerCAmelCase__  :     Tuple       	=   value
			self.update_post_processor()




	@add_bos_token.setter
	def 				UpperCAmelCase__(   self		:						Dict						,   _SCREAMING_SNAKE_CASE		:						List[str]						)->			Any:
			lowerCAmelCase__  :     List[Any]       	=   value
			self.update_post_processor()




	def 				UpperCAmelCase__(   self		:						int						,   _SCREAMING_SNAKE_CASE		:						str						,   _SCREAMING_SNAKE_CASE		:						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(_SCREAMING_SNAKE_CASE						):
					logger.error(F'Vocabulary path ({save_directory}) should be a directory'						)
					return
			lowerCAmelCase__  :     Any       	=   os.path.join(
			    _SCREAMING_SNAKE_CASE						,   (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']						)

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

			return (out_vocab_file,)




	def 				UpperCAmelCase__(   self		:						List[Any]						,   _SCREAMING_SNAKE_CASE		:						"Conversation"						)->			Any:
			lowerCAmelCase__  :     List[Any]       	=   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...)'''						)

			lowerCAmelCase__  :     List[Any]       	=   []
			if len(conversation.past_user_inputs						) > 0:
					if not conversation.past_user_inputs[0].startswith(_SCREAMING_SNAKE_CASE						) or E_SYS not in conversation.past_user_inputs[0]:
							lowerCAmelCase__  :     str       	=   (
							    B_SYS + DEFAULT_SYSTEM_PROMPT + E_SYS + conversation.past_user_inputs[0]
							)
			elif not dialogue[0][1].startswith(_SCREAMING_SNAKE_CASE						) or E_SYS not in dialogue[0][1]:
					lowerCAmelCase__  :     Any       	=   (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=_SCREAMING_SNAKE_CASE						)
			        + [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=_SCREAMING_SNAKE_CASE						)
			return dialog_tokens








from __future__ import annotations

import sys






def 	lowerCamelCase_       (			_a			):




		"""simple docstring"""






		if n < 0:
				raise ValueError('''Negative arguments are not supported'''			)
		return _fib(_a			)[0]






def 	lowerCamelCase_       (			_a			):




		"""simple docstring"""






		if n == 0:  # (F(0), F(1))
				return (0, 1)

		# F(2n) = F(n)[2F(n+1) − F(n)]
		# F(2n+1) = F(n+1)^2+F(n)^2
		lowerCAmelCase__	,      lowerCAmelCase__  :     Dict       	=   _fib(n // 2			)
		lowerCAmelCase__  :     Dict       	=   a * (b * 2 - a)
		lowerCAmelCase__  :     Union[str, Any]       	=   a * a + b * b
		return (d, c + d) if n % 2 else (c, d)


if __name__ == "__main__":
		lowerCamelCase		=						int(sys.argv[1])
		print(f'''fibonacci({n}) is {fibonacci(n)}''')




