
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					:							Dict           =							None

__snake_case					:							int           =							logging.get_logger(__name__)
__snake_case					:							Optional[int]           =							{"vocab_file": "tokenizer.model", "tokenizer_file": "tokenizer.json"}

__snake_case					:							Optional[int]           =							"[INST]", "[/INST]"
__snake_case					:							Tuple           =							"<<SYS>>\n", "\n<</SYS>>\n\n"

# fmt: off
__snake_case					:							str           =							"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__       (  UpperCAmelCase__):

						'''simple docstring'''



						__a     :    str												=			VOCAB_FILES_NAMES
						__a     :    List[Any]												=			LlamaTokenizer
						__a     :    Dict												=			"""left"""
						__a     :    int												=			["""input_ids""", """attention_mask"""]


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

									UpperCAmelCase__		:Optional[Any] 		=    vocab_file
									UpperCAmelCase__		:List[Any] 		=    False if not self.vocab_file else True


						def    A__       (  self	)  ->Dict:
									UpperCAmelCase__		:List[Any] 		=    self.bos_token
									UpperCAmelCase__		:Any 		=    self.bos_token_id

									UpperCAmelCase__		:str 		=    self.eos_token
									UpperCAmelCase__		:Any 		=    self.eos_token_id

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

									UpperCAmelCase__		: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)	)
									UpperCAmelCase__		:List[Any] 		=    processors.TemplateProcessing(
									    single=lowerCamelCase_  , pair=lowerCamelCase_  , special_tokens=lowerCamelCase_	)


						@property
						def    A__       (  self	)  ->str:
									return self._add_eos_token


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


						@add_eos_token.setter
						def    A__       (  self  , A	)  ->List[Any]:
									UpperCAmelCase__		:List[Any] 		=    value
									self.update_post_processor()


						@add_bos_token.setter
						def    A__       (  self  , A	)  ->Any:
									UpperCAmelCase__		:int 		=    value
									self.update_post_processor()


						def    A__       (  self  , A  , A = None	)  ->int:

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

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

									return (out_vocab_file,)


						def    A__       (  self  , A	)  ->Optional[int]:
									UpperCAmelCase__		: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...)'	)

									UpperCAmelCase__		:Optional[Any] 		=    []
									if len(conversation.past_user_inputs	) > 0:
												if not conversation.past_user_inputs[0].startswith(lowerCamelCase_	) or E_SYS not in conversation.past_user_inputs[0]:
															UpperCAmelCase__		:int 		=    (
															    B_SYS + DEFAULT_SYSTEM_PROMPT + E_SYS + conversation.past_user_inputs[0]
															)
									elif not dialogue[0][1].startswith(lowerCamelCase_	) or E_SYS not in dialogue[0][1]:
												UpperCAmelCase__		:Tuple 		=    (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=lowerCamelCase_	)
									        + [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=lowerCamelCase_	)
									return dialog_tokens










_lowercase:					Optional[Any]      =						[[0, 1, 1], [0, 0, 1], [1, 0, 0]]



class       _lowercase				:





	"""simple docstring"""




	def __init__(self						,			lowerCamelCase_						):
						"""simple docstring"""

						a   	=  name
						a   	=  []
						a   	=  []




	def 	UpperCamelCase_			(self						,			lowerCamelCase_						):
						"""simple docstring"""

						self.inbound.append(lowerCamelCase_						)




	def 	UpperCamelCase_			(self						,			lowerCamelCase_						):
						"""simple docstring"""

						self.outbound.append(lowerCamelCase_						)




	def __repr__(self						):
						"""simple docstring"""

						return F'''<node={self.name} inbound={self.inbound} outbound={self.outbound}>'''






def        a( A			:       Optional[Any]					,	A			:       Optional[int]=3					,	A			:       str=0.85			)						->			Optional[Any]:
					"""simple docstring"""





					a   	=  {}
					for node in nodes:
										a   	=  1

					a   	=  {}
					for node in nodes:
										a   	=  len(node.outbound			)

					for i in range(A			):
										print(f'''======= Iteration {i + 1} ======='''			)
										for _, node in enumerate(A			):
															a   	=  (1 - d) + d * sum(
															    ranks[ib] / outbounds[ib] for ib in node.inbound			)
										print(A			)






def        a( )						->			List[Any]:
					"""simple docstring"""





					a   	=  list(input("Enter Names of the Nodes: "			).split()			)

					a   	=  [Node(A			) for name in names]

					for ri, row in enumerate(A			):
										for ci, col in enumerate(A			):
															if col == 1:
																				nodes[ci].add_inbound(names[ri]			)
																				nodes[ri].add_outbound(names[ci]			)

					print("======= Nodes ======="			)
					for node in nodes:
										print(A			)

					page_rank(A			)


if __name__ == "__main__":
				main()
