
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


UpperCamelCase_						:     Union[str, Any]	       =							logging.get_logger(__name__)

UpperCamelCase_						:     Any	       =							{"""vocab_file""": """sentencepiece.bpe.model"""}

UpperCamelCase_						:     Optional[int]	       =							{
    """vocab_file""": {
        """camembert-base""": """https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model""",
    }
}

UpperCamelCase_						:     List[Any]	       =							{
    """camembert-base""": 512,
}

UpperCamelCase_						:     int	       =							"""▁"""




class   __lowercase						(						__snake_case       ):
	_A       =   VOCAB_FILES_NAMES
	_A       =   PRETRAINED_VOCAB_FILES_MAP
	_A       =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	_A       =   ["input_ids", "attention_mask"]






	def __init__(self				: str      ,	snake_case				: Any      ,	snake_case				: Union[str, Any]="<s>"      ,	snake_case				: str="</s>"      ,	snake_case				: Optional[int]="</s>"      ,	snake_case				: Union[str, Any]="<s>"      ,	snake_case				: str="<unk>"      ,	snake_case				: List[Any]="<pad>"      ,	snake_case				: Dict="<mask>"      ,	snake_case				: Optional[int]=["<s>NOTUSED", "</s>NOTUSED"]      ,	snake_case				: Optional[Dict[str, Any]] = None      ,	**snake_case				: int      ,	) ->			None:
							# Mask token behave like a normal word, i.e. include the space before it
							_lowercase       :	Any           =   AddedToken(snake_case      ,	lstrip=snake_case      ,	rstrip=snake_case    ) if isinstance(snake_case      ,	snake_case    ) else mask_token

							_lowercase       :	Any           =   {} if sp_model_kwargs is None else sp_model_kwargs

							super().__init__(
							    bos_token=snake_case      ,	eos_token=snake_case      ,	unk_token=snake_case      ,	sep_token=snake_case      ,	cls_token=snake_case      ,	pad_token=snake_case      ,	mask_token=snake_case      ,	additional_special_tokens=snake_case      ,	sp_model_kwargs=self.sp_model_kwargs      ,	**snake_case      ,	)
							_lowercase       :	Optional[int]           =   spm.SentencePieceProcessor(**self.sp_model_kwargs    )
							self.sp_model.Load(str(snake_case    )    )
							_lowercase       :	List[Any]           =   vocab_file
							# HACK: These tokens were added by fairseq but don't seem to be actually used when duplicated in the actual
							# sentencepiece vocabulary (this is the case for <s> and </s>
							_lowercase       :	List[Any]           =   {"<s>NOTUSED": 0, "<pad>": 1, "</s>NOTUSED": 2, "<unk>": 3}
							_lowercase       :	Optional[Any]           =   len(self.fairseq_tokens_to_ids    )
							_lowercase       :	int           =   len(self.sp_model    ) + len(self.fairseq_tokens_to_ids    )
							_lowercase       :	str           =   {v: k for k, v in self.fairseq_tokens_to_ids.items()}






	def       _a(self				: List[Any]      ,	snake_case				: List[int]      ,	snake_case				: Optional[List[int]] = None    ) ->			List[int]:

							if token_ids_a is None:
													return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
							_lowercase       :	str           =   [self.cls_token_id]
							_lowercase       :	Dict           =   [self.sep_token_id]
							return cls + token_ids_a + sep + sep + token_ids_a + sep






	def       _a(self				: Dict      ,	snake_case				: List[int]      ,	snake_case				: Optional[List[int]] = None      ,	snake_case				: bool = False    ) ->			List[int]:
							if already_has_special_tokens:
													return super().get_special_tokens_mask(
													    token_ids_a=snake_case      ,	token_ids_a=snake_case      ,	already_has_special_tokens=snake_case    )

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






	def       _a(self				: List[str]      ,	snake_case				: List[int]      ,	snake_case				: Optional[List[int]] = None    ) ->			List[int]:
							_lowercase       :	str           =   [self.sep_token_id]
							_lowercase       :	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]






	@property
	def       _a(self				: List[str]    ) ->			Dict:
							return len(self.fairseq_tokens_to_ids    ) + len(self.sp_model    )






	def       _a(self				: Dict    ) ->			str:
							_lowercase       :	List[Any]           =   {self.convert_ids_to_tokens(snake_case    ): i for i in range(self.vocab_size    )}
							vocab.update(self.added_tokens_encoder    )
							return vocab






	def       _a(self				: List[str]      ,	snake_case				: str    ) ->			List[str]:
							return self.sp_model.encode(snake_case      ,	out_type=snake_case    )






	def       _a(self				: Tuple      ,	snake_case				: int    ) ->			Dict:
							if token in self.fairseq_tokens_to_ids:
													return self.fairseq_tokens_to_ids[token]
							elif self.sp_model.PieceToId(snake_case    ) == 0:
													# Convert sentence piece unk token to fairseq unk token index
													return self.unk_token_id
							return self.fairseq_offset + self.sp_model.PieceToId(snake_case    )






	def       _a(self				: Union[str, Any]      ,	snake_case				: List[Any]    ) ->			List[str]:
							if index in self.fairseq_ids_to_tokens:
													return self.fairseq_ids_to_tokens[index]
							return self.sp_model.IdToPiece(index - self.fairseq_offset    )






	def       _a(self				: Tuple      ,	snake_case				: Dict    ) ->			List[str]:
							_lowercase       :	Optional[Any]           =   []
							_lowercase       :	Optional[int]           =   ""
							_lowercase       :	Dict           =   False
							for token in tokens:
													# make sure that special tokens are not decoded using sentencepiece model
													if token in self.all_special_tokens:
																			if not prev_is_special:
																									out_string += " "
																			out_string += self.sp_model.decode(snake_case    ) + token
																			_lowercase       :	str           =   True
																			_lowercase       :	Any           =   []
													else:
																			current_sub_tokens.append(snake_case    )
																			_lowercase       :	Tuple           =   False
							out_string += self.sp_model.decode(snake_case    )
							return out_string.strip()






	def __getstate__(self				: Optional[Any]    ) ->			Optional[Any]:
							_lowercase       :	str           =   self.__dict__.copy()
							_lowercase       :	str           =   None
							return state






	def __setstate__(self				: List[str]      ,	snake_case				: Dict    ) ->			str:
							_lowercase       :	Any           =   d

							# for backward compatibility
							if not hasattr(self      ,	"sp_model_kwargs"    ):
													_lowercase       :	Any           =   {}

							_lowercase       :	Dict           =   spm.SentencePieceProcessor(**self.sp_model_kwargs    )
							self.sp_model.Load(self.vocab_file    )






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

							if os.path.abspath(self.vocab_file    ) != os.path.abspath(snake_case    ) and os.path.isfile(self.vocab_file    ):
													copyfile(self.vocab_file      ,	snake_case    )
							elif not os.path.isfile(self.vocab_file    ):
													with open(snake_case      ,	"wb"    ) as fi:
																			_lowercase       :	Any           =   self.sp_model.serialized_model_proto()
																			fi.write(snake_case    )

							return (out_vocab_file,)






def 		UpperCamelCase     (       _UpperCAmelCase  :   str  )   ->			bool:






						'''simple docstring'''

						_lowercase       :	List[str]           =   [int(_UpperCAmelCase  ) for i in ip_va_address.split("."  ) if i.isdigit()]
						return len(_UpperCAmelCase  ) == 4 and all(0 <= int(_UpperCAmelCase  ) <= 254 for octet in octets  )


if __name__ == "__main__":
							UpperCamelCase_						:     Dict	       =							input().strip()
							UpperCamelCase_						:     List[Any]	       =							"""valid""" if is_ip_va_address_valid(ip) else """invalid"""
							print(f'''{ip} is a {valid_or_invalid} IP v4 address.''')




