
import os
import re
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


SCREAMING_SNAKE_CASE__   :			Any												=    logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__   :			Tuple												=    {"vocab_file": "spiece.model"}

SCREAMING_SNAKE_CASE__   :			Any												=    {
    "vocab_file": {
        "google/bigbird-roberta-base": "https://huggingface.co/google/bigbird-roberta-base/resolve/main/spiece.model",
        "google/bigbird-roberta-large": (
            "https://huggingface.co/google/bigbird-roberta-large/resolve/main/spiece.model"
        ),
        "google/bigbird-base-trivia-itc": (
            "https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/spiece.model"
        ),
    }
}

SCREAMING_SNAKE_CASE__   :			Optional[int]												=    {
    "google/bigbird-roberta-base": 4_096,
    "google/bigbird-roberta-large": 4_096,
    "google/bigbird-base-trivia-itc": 4_096,
}

class    lowerCAmelCase__     (	__lowercase			):
		a__       :						Tuple        =		VOCAB_FILES_NAMES
		a__       :						Tuple        =		PRETRAINED_VOCAB_FILES_MAP
		a__       :						Tuple        =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		a__       :						Union[str, Any]        =		["""input_ids""", """attention_mask"""]
		a__       :						List[int]        =		[]






		def __init__(		self		:							Optional[Any]							,			SCREAMING_SNAKE_CASE__		:							int							,			SCREAMING_SNAKE_CASE__		:							int="<unk>"							,			SCREAMING_SNAKE_CASE__		:							Any="<s>"							,			SCREAMING_SNAKE_CASE__		:							Optional[int]="</s>"							,			SCREAMING_SNAKE_CASE__		:							Optional[Any]="<pad>"							,			SCREAMING_SNAKE_CASE__		:							int="[SEP]"							,			SCREAMING_SNAKE_CASE__		:							str="[MASK]"							,			SCREAMING_SNAKE_CASE__		:							int="[CLS]"							,			SCREAMING_SNAKE_CASE__		:							Optional[Dict[str, Any]] = None							,			**SCREAMING_SNAKE_CASE__		:							List[Any]							,			)     ->							None:
						__lowerCamelCase    					=	AddedToken(SCREAMING_SNAKE_CASE__							,			lstrip=SCREAMING_SNAKE_CASE__							,			rstrip=SCREAMING_SNAKE_CASE__  ) if isinstance(SCREAMING_SNAKE_CASE__							,			SCREAMING_SNAKE_CASE__  ) else bos_token
						__lowerCamelCase    					=	AddedToken(SCREAMING_SNAKE_CASE__							,			lstrip=SCREAMING_SNAKE_CASE__							,			rstrip=SCREAMING_SNAKE_CASE__  ) if isinstance(SCREAMING_SNAKE_CASE__							,			SCREAMING_SNAKE_CASE__  ) else eos_token
						__lowerCamelCase    					=	AddedToken(SCREAMING_SNAKE_CASE__							,			lstrip=SCREAMING_SNAKE_CASE__							,			rstrip=SCREAMING_SNAKE_CASE__  ) if isinstance(SCREAMING_SNAKE_CASE__							,			SCREAMING_SNAKE_CASE__  ) else unk_token
						__lowerCamelCase    					=	AddedToken(SCREAMING_SNAKE_CASE__							,			lstrip=SCREAMING_SNAKE_CASE__							,			rstrip=SCREAMING_SNAKE_CASE__  ) if isinstance(SCREAMING_SNAKE_CASE__							,			SCREAMING_SNAKE_CASE__  ) else pad_token
						__lowerCamelCase    					=	AddedToken(SCREAMING_SNAKE_CASE__							,			lstrip=SCREAMING_SNAKE_CASE__							,			rstrip=SCREAMING_SNAKE_CASE__  ) if isinstance(SCREAMING_SNAKE_CASE__							,			SCREAMING_SNAKE_CASE__  ) else cls_token
						__lowerCamelCase    					=	AddedToken(SCREAMING_SNAKE_CASE__							,			lstrip=SCREAMING_SNAKE_CASE__							,			rstrip=SCREAMING_SNAKE_CASE__  ) if isinstance(SCREAMING_SNAKE_CASE__							,			SCREAMING_SNAKE_CASE__  ) else sep_token

						# Mask token behave like a normal word, i.e. include the space before it
						__lowerCamelCase    					=	AddedToken(SCREAMING_SNAKE_CASE__							,			lstrip=SCREAMING_SNAKE_CASE__							,			rstrip=SCREAMING_SNAKE_CASE__  ) if isinstance(SCREAMING_SNAKE_CASE__							,			SCREAMING_SNAKE_CASE__  ) else mask_token

						__lowerCamelCase    					=	{} if sp_model_kwargs is None else sp_model_kwargs

						super().__init__(
						    bos_token=SCREAMING_SNAKE_CASE__							,			eos_token=SCREAMING_SNAKE_CASE__							,			unk_token=SCREAMING_SNAKE_CASE__							,			pad_token=SCREAMING_SNAKE_CASE__							,			sep_token=SCREAMING_SNAKE_CASE__							,			mask_token=SCREAMING_SNAKE_CASE__							,			cls_token=SCREAMING_SNAKE_CASE__							,			sp_model_kwargs=self.sp_model_kwargs							,			**SCREAMING_SNAKE_CASE__							,			)

						__lowerCamelCase    					=	vocab_file

						__lowerCamelCase    					=	spm.SentencePieceProcessor(**self.sp_model_kwargs  )
						self.sp_model.Load(SCREAMING_SNAKE_CASE__  )






		@property
		def  __A       (		self		:							str  )     ->							Any:
						return self.sp_model.get_piece_size()






		def  __A       (		self		:							Dict  )     ->							Dict:
						__lowerCamelCase    					=	{self.convert_ids_to_tokens(SCREAMING_SNAKE_CASE__  ): i for i in range(self.vocab_size  )}
						vocab.update(self.added_tokens_encoder  )
						return vocab






		def __getstate__(		self		:							Dict  )     ->							str:
						__lowerCamelCase    					=	self.__dict__.copy()
						__lowerCamelCase    					=	None
						return state






		def __setstate__(		self		:							List[str]							,			SCREAMING_SNAKE_CASE__		:							str  )     ->							int:
						__lowerCamelCase    					=	d

						# for backward compatibility
						if not hasattr(self							,			'''sp_model_kwargs'''  ):
										__lowerCamelCase    					=	{}

						__lowerCamelCase    					=	spm.SentencePieceProcessor(**self.sp_model_kwargs  )
						self.sp_model.Load(self.vocab_file  )






		def  __A       (		self		:							Tuple							,			SCREAMING_SNAKE_CASE__		:							str  )     ->							List[str]:
						return self.sp_model.encode(SCREAMING_SNAKE_CASE__							,			out_type=SCREAMING_SNAKE_CASE__  )






		def  __A       (		self		:							List[str]							,			SCREAMING_SNAKE_CASE__		:							Any  )     ->							List[str]:
						return self.sp_model.piece_to_id(SCREAMING_SNAKE_CASE__  )






		def  __A       (		self		:							int							,			SCREAMING_SNAKE_CASE__		:							Optional[int]  )     ->							List[Any]:
						__lowerCamelCase    					=	self.sp_model.IdToPiece(SCREAMING_SNAKE_CASE__  )
						return token






		def  __A       (		self		:							Tuple							,			SCREAMING_SNAKE_CASE__		:							str  )     ->							Optional[int]:
						__lowerCamelCase    					=	[]
						__lowerCamelCase    					=	''''''
						__lowerCamelCase    					=	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(SCREAMING_SNAKE_CASE__  ) + token
														__lowerCamelCase    					=	True
														__lowerCamelCase    					=	[]
										else:
														current_sub_tokens.append(SCREAMING_SNAKE_CASE__  )
														__lowerCamelCase    					=	False
						out_string += self.sp_model.decode(SCREAMING_SNAKE_CASE__  )
						return out_string.strip()






		def  __A       (		self		:							List[Any]							,			SCREAMING_SNAKE_CASE__		:							List[int]							,			SCREAMING_SNAKE_CASE__		:							bool = False							,			SCREAMING_SNAKE_CASE__		:							bool = None							,			SCREAMING_SNAKE_CASE__		:							bool = True							,			**SCREAMING_SNAKE_CASE__		:							Tuple							,			)     ->							str:
						__lowerCamelCase    					=	kwargs.pop('''use_source_tokenizer'''							,			SCREAMING_SNAKE_CASE__  )

						__lowerCamelCase    					=	self.convert_ids_to_tokens(SCREAMING_SNAKE_CASE__							,			skip_special_tokens=SCREAMING_SNAKE_CASE__  )

						# To avoid mixing byte-level and unicode for byte-level BPT
						# we need to build string separately for added tokens and byte-level tokens
						# cf. https://github.com/huggingface/transformers/issues/1133
						__lowerCamelCase    					=	[]
						__lowerCamelCase    					=	[]
						for token in filtered_tokens:
										if skip_special_tokens and token in self.all_special_ids:
														continue
										if token in self.added_tokens_encoder:
														if current_sub_text:
																		sub_texts.append(self.convert_tokens_to_string(SCREAMING_SNAKE_CASE__  )  )
																		__lowerCamelCase    					=	[]
														sub_texts.append(SCREAMING_SNAKE_CASE__  )
										else:
														current_sub_text.append(SCREAMING_SNAKE_CASE__  )
						if current_sub_text:
										sub_texts.append(self.convert_tokens_to_string(SCREAMING_SNAKE_CASE__  )  )

						# Mimic the behavior of the Rust tokenizer:
						# No space before [MASK] and [SEP]
						if spaces_between_special_tokens:
										__lowerCamelCase    					=	re.sub(R''' (\[(MASK|SEP)\])'''							,			R'''\1'''							,			''' '''.join(SCREAMING_SNAKE_CASE__  )  )
						else:
										__lowerCamelCase    					=	''''''.join(SCREAMING_SNAKE_CASE__  )

						__lowerCamelCase    					=	(
						    clean_up_tokenization_spaces
						    if clean_up_tokenization_spaces is not None
						    else self.clean_up_tokenization_spaces
						)
						if clean_up_tokenization_spaces:
										__lowerCamelCase    					=	self.clean_up_tokenization(SCREAMING_SNAKE_CASE__  )
										return clean_text
						else:
										return text






		def  __A       (		self		:							Optional[Any]							,			SCREAMING_SNAKE_CASE__		:							str							,			SCREAMING_SNAKE_CASE__		:							Optional[str] = None  )     ->							Tuple[str]:
						if not os.path.isdir(SCREAMING_SNAKE_CASE__  ):
										logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''  )
										return
						__lowerCamelCase    					=	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__  ) and os.path.isfile(self.vocab_file  ):
										copyfile(self.vocab_file							,			SCREAMING_SNAKE_CASE__  )
						elif not os.path.isfile(self.vocab_file  ):
										with open(SCREAMING_SNAKE_CASE__							,			'''wb'''  ) as fi:
														__lowerCamelCase    					=	self.sp_model.serialized_model_proto()
														fi.write(SCREAMING_SNAKE_CASE__  )

						return (out_vocab_file,)






		def  __A       (		self		:							List[str]							,			SCREAMING_SNAKE_CASE__		:							List[int]							,			SCREAMING_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]
						__lowerCamelCase    					=	[self.cls_token_id]
						__lowerCamelCase    					=	[self.sep_token_id]
						return cls + token_ids_a + sep + token_ids_a + sep






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

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







		def  __A       (		self		:							int							,			SCREAMING_SNAKE_CASE__		:							List[int]							,			SCREAMING_SNAKE_CASE__		:							Optional[List[int]] = None  )     ->							List[int]:
						__lowerCamelCase    					=	[self.sep_token_id]
						__lowerCamelCase    					=	[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  ) * [0] + len(token_ids_a + sep  ) * [1]





import os




def  __magic_name__ (   )			->   str:
				__lowerCamelCase    					=	os.path.join(os.path.dirname(__lowerCAmelCase							)		,  '''num.txt'''							)
				with open(__lowerCAmelCase							) as file_hand:
								return str(sum(int(__lowerCAmelCase							) for line in file_hand							)							)[:10]


if __name__ == "__main__":
					print(solution())



