


'''simple docstring'''


import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging


lowerCamelCase__					=   logging.get_logger(__name__)


lowerCamelCase__					=   {'vocab_file': 'vocab.json', 'merges_file': 'merges.txt'}

# See all LED models at https://huggingface.co/models?filter=LED
lowerCamelCase__					=   {
    'vocab_file': {
        'allenai/led-base-16384': 'https://huggingface.co/allenai/led-base-16384/resolve/main/vocab.json',
    },
    'merges_file': {
        'allenai/led-base-16384': 'https://huggingface.co/allenai/led-base-16384/resolve/main/merges.txt',
    },
    'tokenizer_file': {
        'allenai/led-base-16384': 'https://huggingface.co/allenai/led-base-16384/resolve/main/tokenizer.json',
    },
}

lowerCamelCase__					=   {
    'allenai/led-base-16384': 16_384,
}






@lru_cache()
# Copied from transformers.models.bart.tokenization_bart.bytes_to_unicode
def        __lowerCAmelCase       ():
		_UpperCAmelCase						:				Dict	    =					(
		    list(range(ord("!"      )					,       ord("~"      ) + 1      )      ) + list(range(ord("¡"      )					,       ord("¬"      ) + 1      )      ) + list(range(ord("®"      )					,       ord("ÿ"      ) + 1      )      )
		)
		_UpperCAmelCase						:				Tuple	    =					bs[:]
		_UpperCAmelCase						:				int	    =					0
		for b in range(2**8      ):
				if b not in bs:
						bs.append(__lowerCAmelCase      )
						cs.append(2**8 + n      )
						n += 1
		_UpperCAmelCase						:				Dict	    =					[chr(__lowerCAmelCase      ) for n in cs]
		return dict(zip(__lowerCAmelCase					,       __lowerCAmelCase      )      )






def        __lowerCAmelCase       (__lowerCAmelCase      ):
		_UpperCAmelCase						:				Dict	    =					set()
		_UpperCAmelCase						:				int	    =					word[0]
		for char in word[1:]:
				pairs.add((prev_char, char)      )
				_UpperCAmelCase						:				List[Any]	    =					char
		return pairs






class 		lowerCAmelCase__	(	UpperCAmelCase__		):
			lowerCAmelCase       :		Any				      =   VOCAB_FILES_NAMES
			lowerCAmelCase       :		List[str]				      =   PRETRAINED_VOCAB_FILES_MAP
			lowerCAmelCase       :		Dict				      =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCAmelCase       :		Tuple				      =   ["input_ids", "attention_mask"]




			def __init__(						self     :   str		,     lowerCamelCase__     :   List[str]		,     lowerCamelCase__     :   str		,     lowerCamelCase__     :   Union[str, Any]="replace"		,     lowerCamelCase__     :   Optional[int]="<s>"		,     lowerCamelCase__     :   Optional[Any]="</s>"		,     lowerCamelCase__     :   str="</s>"		,     lowerCamelCase__     :   Any="<s>"		,     lowerCamelCase__     :   str="<unk>"		,     lowerCamelCase__     :   Optional[Any]="<pad>"		,     lowerCamelCase__     :   Dict="<mask>"		,     lowerCamelCase__     :   int=False		,     **lowerCamelCase__     :   int		,     )      ->Optional[int]:



					'''simple docstring'''







					_UpperCAmelCase						:				int	    =					AddedToken(lowerCamelCase__		,     lstrip=lowerCamelCase__		,     rstrip=lowerCamelCase__       ) if isinstance(lowerCamelCase__		,     lowerCamelCase__       ) else bos_token
					_UpperCAmelCase						:				Optional[Any]	    =					AddedToken(lowerCamelCase__		,     lstrip=lowerCamelCase__		,     rstrip=lowerCamelCase__       ) if isinstance(lowerCamelCase__		,     lowerCamelCase__       ) else eos_token
					_UpperCAmelCase						:				Tuple	    =					AddedToken(lowerCamelCase__		,     lstrip=lowerCamelCase__		,     rstrip=lowerCamelCase__       ) if isinstance(lowerCamelCase__		,     lowerCamelCase__       ) else sep_token
					_UpperCAmelCase						:				Any	    =					AddedToken(lowerCamelCase__		,     lstrip=lowerCamelCase__		,     rstrip=lowerCamelCase__       ) if isinstance(lowerCamelCase__		,     lowerCamelCase__       ) else cls_token
					_UpperCAmelCase						:				Optional[Any]	    =					AddedToken(lowerCamelCase__		,     lstrip=lowerCamelCase__		,     rstrip=lowerCamelCase__       ) if isinstance(lowerCamelCase__		,     lowerCamelCase__       ) else unk_token
					_UpperCAmelCase						:				int	    =					AddedToken(lowerCamelCase__		,     lstrip=lowerCamelCase__		,     rstrip=lowerCamelCase__       ) if isinstance(lowerCamelCase__		,     lowerCamelCase__       ) else pad_token

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

					super().__init__(
					    errors=lowerCamelCase__		,     bos_token=lowerCamelCase__		,     eos_token=lowerCamelCase__		,     unk_token=lowerCamelCase__		,     sep_token=lowerCamelCase__		,     cls_token=lowerCamelCase__		,     pad_token=lowerCamelCase__		,     mask_token=lowerCamelCase__		,     add_prefix_space=lowerCamelCase__		,     **lowerCamelCase__		,     )

					with open(lowerCamelCase__		,     encoding="utf-8"       ) as vocab_handle:
							_UpperCAmelCase						:				Tuple	    =					json.load(lowerCamelCase__       )
					_UpperCAmelCase						:				List[Any]	    =					{v: k for k, v in self.encoder.items()}
					_UpperCAmelCase						:				Optional[int]	    =					errors  # how to handle errors in decoding
					_UpperCAmelCase						:				int	    =					bytes_to_unicode()
					_UpperCAmelCase						:				Tuple	    =					{v: k for k, v in self.byte_encoder.items()}
					with open(lowerCamelCase__		,     encoding="utf-8"       ) as merges_handle:
							_UpperCAmelCase						:				Tuple	    =					merges_handle.read().split("\n"       )[1:-1]
					_UpperCAmelCase						:				str	    =					[tuple(merge.split()       ) for merge in bpe_merges]
					_UpperCAmelCase						:				Dict	    =					dict(zip(lowerCamelCase__		,     range(len(lowerCamelCase__       )       )       )       )
					_UpperCAmelCase						:				List[Any]	    =					{}
					_UpperCAmelCase						:				List[Any]	    =					add_prefix_space

					# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
					_UpperCAmelCase						:				str	    =					re.compile(R"'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"       )




			@property
			# Copied from transformers.models.bart.tokenization_bart.BartTokenizer.vocab_size
			def 							lowerCAmelCase__			(						self     :   str       )      ->Union[str, Any]:



					'''simple docstring'''







					return len(self.encoder       )




			def 							lowerCAmelCase__			(						self     :   str       )      ->Optional[int]:



					'''simple docstring'''







					return dict(self.encoder		,     **self.added_tokens_encoder       )




			def 							lowerCAmelCase__			(						self     :   Tuple		,     lowerCamelCase__     :   List[Any]       )      ->Dict:



					'''simple docstring'''







					if token in self.cache:
							return self.cache[token]
					_UpperCAmelCase						:				Optional[int]	    =					tuple(lowerCamelCase__       )
					_UpperCAmelCase						:				int	    =					get_pairs(lowerCamelCase__       )

					if not pairs:
							return token

					while True:
							_UpperCAmelCase						:				Union[str, Any]	    =					min(lowerCamelCase__		,     key=lambda lowerCamelCase__       : self.bpe_ranks.get(lowerCamelCase__		,     float("inf"       )       )       )
							if bigram not in self.bpe_ranks:
									break
							_UpperCAmelCase    ,			_UpperCAmelCase						:				List[str]	    =					bigram
							_UpperCAmelCase						:				List[str]	    =					[]
							_UpperCAmelCase						:				Optional[Any]	    =					0
							while i < len(lowerCamelCase__       ):
									try:
											_UpperCAmelCase						:				str	    =					word.index(lowerCamelCase__		,     lowerCamelCase__       )
									except ValueError:
											new_word.extend(word[i:]       )
											break
									else:
											new_word.extend(word[i:j]       )
											_UpperCAmelCase						:				Any	    =					j

									if word[i] == first and i < len(lowerCamelCase__       ) - 1 and word[i + 1] == second:
											new_word.append(first + second       )
											i += 2
									else:
											new_word.append(word[i]       )
											i += 1
							_UpperCAmelCase						:				Any	    =					tuple(lowerCamelCase__       )
							_UpperCAmelCase						:				Tuple	    =					new_word
							if len(lowerCamelCase__       ) == 1:
									break
							else:
									_UpperCAmelCase						:				Any	    =					get_pairs(lowerCamelCase__       )
					_UpperCAmelCase						:				str	    =					" ".join(lowerCamelCase__       )
					_UpperCAmelCase						:				int	    =					word
					return word




			def 							lowerCAmelCase__			(						self     :   Tuple		,     lowerCamelCase__     :   Optional[int]       )      ->Dict:



					'''simple docstring'''







					_UpperCAmelCase						:				int	    =					[]
					for token in re.findall(self.pat		,     lowerCamelCase__       ):
							_UpperCAmelCase						:				List[str]	    =					"".join(
							    self.byte_encoder[b] for b in token.encode("utf-8"       )       )  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
							bpe_tokens.extend(bpe_token for bpe_token in self.bpe(lowerCamelCase__       ).split(" "       )       )
					return bpe_tokens




			def 							lowerCAmelCase__			(						self     :   int		,     lowerCamelCase__     :   Dict       )      ->str:



					'''simple docstring'''







					return self.encoder.get(lowerCamelCase__		,     self.encoder.get(self.unk_token       )       )




			def 							lowerCAmelCase__			(						self     :   Union[str, Any]		,     lowerCamelCase__     :   str       )      ->List[str]:



					'''simple docstring'''







					return self.decoder.get(lowerCamelCase__       )




			def 							lowerCAmelCase__			(						self     :   Any		,     lowerCamelCase__     :   int       )      ->Union[str, Any]:



					'''simple docstring'''







					_UpperCAmelCase						:				List[Any]	    =					"".join(lowerCamelCase__       )
					_UpperCAmelCase						:				Dict	    =					bytearray([self.byte_decoder[c] for c in text]       ).decode("utf-8"		,     errors=self.errors       )
					return text




			def 							lowerCAmelCase__			(						self     :   List[str]		,     lowerCamelCase__     :   str		,     lowerCamelCase__     :   Optional[str] = None       )      ->Tuple[str]:



					'''simple docstring'''







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

					with open(lowerCamelCase__		,     "w"		,     encoding="utf-8"       ) as f:
							f.write(json.dumps(self.encoder		,     indent=2		,     sort_keys=lowerCamelCase__		,     ensure_ascii=lowerCamelCase__       ) + "\n"       )

					_UpperCAmelCase						:				List[str]	    =					0
					with open(lowerCamelCase__		,     "w"		,     encoding="utf-8"       ) as writer:
							writer.write("#version: 0.2\n"       )
							for bpe_tokens, token_index in sorted(self.bpe_ranks.items()		,     key=lambda lowerCamelCase__       : kv[1]       ):
									if index != token_index:
											logger.warning(
											    F"""Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."""
											    " Please check that the tokenizer is not corrupted!"       )
											_UpperCAmelCase						:				int	    =					token_index
									writer.write(" ".join(lowerCamelCase__       ) + "\n"       )
									index += 1

					return vocab_file, merge_file




			def 							lowerCAmelCase__			(						self     :   Union[str, Any]		,     lowerCamelCase__     :   List[int]		,     lowerCamelCase__     :   Optional[List[int]] = None       )      ->List[int]:



					'''simple docstring'''







					if token_ids_a is None:
							return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
					_UpperCAmelCase						:				int	    =					[self.cls_token_id]
					_UpperCAmelCase						:				List[str]	    =					[self.sep_token_id]
					return cls + token_ids_a + sep + sep + token_ids_a + sep




			def 							lowerCAmelCase__			(						self     :   List[Any]		,     lowerCamelCase__     :   List[int]		,     lowerCamelCase__     :   Optional[List[int]] = None		,     lowerCamelCase__     :   bool = False       )      ->List[int]:



					'''simple docstring'''







					if already_has_special_tokens:
							return super().get_special_tokens_mask(
							    token_ids_a=lowerCamelCase__		,     token_ids_a=lowerCamelCase__		,     already_has_special_tokens=lowerCamelCase__       )

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




			def 							lowerCAmelCase__			(						self     :   str		,     lowerCamelCase__     :   List[int]		,     lowerCamelCase__     :   Optional[List[int]] = None       )      ->List[int]:



					'''simple docstring'''







					_UpperCAmelCase						:				Tuple	    =					[self.sep_token_id]
					_UpperCAmelCase						:				str	    =					[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]




			def 							lowerCAmelCase__			(						self     :   str		,     lowerCamelCase__     :   Optional[Any]		,     lowerCamelCase__     :   List[Any]=False		,     **lowerCamelCase__     :   Union[str, Any]       )      ->List[str]:



					'''simple docstring'''







					_UpperCAmelCase						:				int	    =					kwargs.pop("add_prefix_space"		,     self.add_prefix_space       )
					if (is_split_into_words or add_prefix_space) and (len(lowerCamelCase__       ) > 0 and not text[0].isspace()):
							_UpperCAmelCase						:				Optional[int]	    =					" " + text
					return (text, kwargs)






			def 							lowerCAmelCase__			(						self     :   List[str]		,     lowerCamelCase__     :   Union[Dict[str, EncodedInput], BatchEncoding]		,     lowerCamelCase__     :   Optional[int] = None		,     lowerCamelCase__     :   PaddingStrategy = PaddingStrategy.DO_NOT_PAD		,     lowerCamelCase__     :   Optional[int] = None		,     lowerCamelCase__     :   Optional[bool] = None		,     )      ->dict:



					'''simple docstring'''







					_UpperCAmelCase						:				Optional[int]	    =					super()._pad(
					    encoded_inputs=lowerCamelCase__		,     max_length=lowerCamelCase__		,     padding_strategy=lowerCamelCase__		,     pad_to_multiple_of=lowerCamelCase__		,     return_attention_mask=lowerCamelCase__		,     )

					# Load from model defaults
					if return_attention_mask is None:
							_UpperCAmelCase						:				Tuple	    =					"attention_mask" in self.model_input_names

					if return_attention_mask and "global_attention_mask" in encoded_inputs:
							_UpperCAmelCase						:				Union[str, Any]	    =					encoded_inputs[self.model_input_names[0]]
							# `global_attention_mask` need to have the same length as other (sequential) inputs.
							_UpperCAmelCase						:				Union[str, Any]	    =					len(encoded_inputs["global_attention_mask"]       ) != len(lowerCamelCase__       )

							if needs_to_be_padded:
									_UpperCAmelCase						:				Optional[Any]	    =					len(lowerCamelCase__       ) - len(encoded_inputs["global_attention_mask"]       )

									if self.padding_side == "right":
											# Use `-1` since `0` in `global_attention_mask` means `local attention` instead of `not to attend`
											_UpperCAmelCase						:				str	    =					(
											    encoded_inputs["global_attention_mask"] + [-1] * difference
											)
									elif self.padding_side == "left":
											_UpperCAmelCase						:				str	    =					[-1] * difference + encoded_inputs[
											    "global_attention_mask"
											]
									else:
											raise ValueError("Invalid padding strategy:" + str(self.padding_side       )       )

					return encoded_inputs







'''simple docstring'''


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


lowerCamelCase__					=   logging.get_logger(__name__)

lowerCamelCase__					=   {'vocab_file': 'sentencepiece.bpe.model'}

lowerCamelCase__					=   {
    'vocab_file': {
        'moussaKam/mbarthez': 'https://huggingface.co/moussaKam/mbarthez/resolve/main/sentencepiece.bpe.model',
        'moussaKam/barthez': 'https://huggingface.co/moussaKam/barthez/resolve/main/sentencepiece.bpe.model',
        'moussaKam/barthez-orangesum-title': (
            'https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/sentencepiece.bpe.model'
        ),
    },
}

lowerCamelCase__					=   {
    'moussaKam/mbarthez': 1_024,
    'moussaKam/barthez': 1_024,
    'moussaKam/barthez-orangesum-title': 1_024,
}

lowerCamelCase__					=   '▁'






class 		lowerCAmelCase__	(	UpperCAmelCase__		):
			lowerCAmelCase       :		Any				      =   VOCAB_FILES_NAMES
			lowerCAmelCase       :		Any				      =   PRETRAINED_VOCAB_FILES_MAP
			lowerCAmelCase       :		Union[str, Any]				      =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCAmelCase       :		int				      =   ["input_ids", "attention_mask"]




			def __init__(						self     :   int		,     lowerCamelCase__     :   Tuple		,     lowerCamelCase__     :   List[Any]="<s>"		,     lowerCamelCase__     :   Dict="</s>"		,     lowerCamelCase__     :   Union[str, Any]="</s>"		,     lowerCamelCase__     :   List[Any]="<s>"		,     lowerCamelCase__     :   List[str]="<unk>"		,     lowerCamelCase__     :   str="<pad>"		,     lowerCamelCase__     :   Tuple="<mask>"		,     lowerCamelCase__     :   Optional[Dict[str, Any]] = None		,     **lowerCamelCase__     :   Dict		,     )      ->None:



					'''simple docstring'''







					_UpperCAmelCase						:				Dict	    =					AddedToken(lowerCamelCase__		,     lstrip=lowerCamelCase__		,     rstrip=lowerCamelCase__       ) if isinstance(lowerCamelCase__		,     lowerCamelCase__       ) else mask_token

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

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

					_UpperCAmelCase						:				Union[str, Any]	    =					vocab_file
					_UpperCAmelCase						:				Dict	    =					spm.SentencePieceProcessor(**self.sp_model_kwargs       )
					self.sp_model.Load(str(lowerCamelCase__       )       )

					_UpperCAmelCase						:				Optional[int]	    =					{"<s>": 0, "<pad>": 1, "</s>": 2, "<unk>": 3}

					_UpperCAmelCase						:				List[str]	    =					len(self.sp_model       ) - 1
					_UpperCAmelCase						:				List[str]	    =					{v: k for k, v in self.fairseq_tokens_to_ids.items()}




			def 							lowerCAmelCase__			(						self     :   Dict		,     lowerCamelCase__     :   List[int]		,     lowerCamelCase__     :   Optional[List[int]] = None       )      ->List[int]:



					'''simple docstring'''







					if token_ids_a is None:
							return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
					_UpperCAmelCase						:				Union[str, Any]	    =					[self.cls_token_id]
					_UpperCAmelCase						:				str	    =					[self.sep_token_id]
					return cls + token_ids_a + sep + sep + token_ids_a + sep




			def 							lowerCAmelCase__			(						self     :   int		,     lowerCamelCase__     :   List[int]		,     lowerCamelCase__     :   Optional[List[int]] = None		,     lowerCamelCase__     :   bool = False       )      ->List[int]:



					'''simple docstring'''







					if already_has_special_tokens:
							return super().get_special_tokens_mask(
							    token_ids_a=lowerCamelCase__		,     token_ids_a=lowerCamelCase__		,     already_has_special_tokens=lowerCamelCase__       )

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




			def 							lowerCAmelCase__			(						self     :   List[str]		,     lowerCamelCase__     :   List[int]		,     lowerCamelCase__     :   Optional[List[int]] = None       )      ->List[int]:



					'''simple docstring'''







					_UpperCAmelCase						:				Optional[int]	    =					[self.sep_token_id]
					_UpperCAmelCase						:				Optional[int]	    =					[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 							lowerCAmelCase__			(						self     :   List[Any]       )      ->List[str]:



					'''simple docstring'''







					return len(self.sp_model       )




			def 							lowerCAmelCase__			(						self     :   int       )      ->int:



					'''simple docstring'''







					_UpperCAmelCase						:				List[Any]	    =					{self.convert_ids_to_tokens(lowerCamelCase__       ): i for i in range(self.vocab_size       )}
					vocab.update(self.added_tokens_encoder       )
					return vocab




			def 							lowerCAmelCase__			(						self     :   int		,     lowerCamelCase__     :   str       )      ->List[str]:



					'''simple docstring'''







					return self.sp_model.encode(lowerCamelCase__		,     out_type=lowerCamelCase__       )




			def 							lowerCAmelCase__			(						self     :   Dict		,     lowerCamelCase__     :   Union[str, Any]       )      ->List[Any]:



					'''simple docstring'''







					if token in self.fairseq_tokens_to_ids:
							return self.fairseq_tokens_to_ids[token]
					_UpperCAmelCase						:				Optional[Any]	    =					self.sp_model.PieceToId(lowerCamelCase__       )

					return spm_id if spm_id else self.unk_token_id




			def 							lowerCAmelCase__			(						self     :   str		,     lowerCamelCase__     :   Any       )      ->Optional[Any]:



					'''simple docstring'''







					if index in self.fairseq_ids_to_tokens:
							return self.fairseq_ids_to_tokens[index]
					return self.sp_model.IdToPiece(lowerCamelCase__       )




			def 							lowerCAmelCase__			(						self     :   Any		,     lowerCamelCase__     :   List[Any]       )      ->Optional[int]:



					'''simple docstring'''







					_UpperCAmelCase						:				Union[str, Any]	    =					[]
					_UpperCAmelCase						:				Optional[Any]	    =					""
					_UpperCAmelCase						:				Optional[int]	    =					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(lowerCamelCase__       ) + token
									_UpperCAmelCase						:				Union[str, Any]	    =					True
									_UpperCAmelCase						:				Union[str, Any]	    =					[]
							else:
									current_sub_tokens.append(lowerCamelCase__       )
									_UpperCAmelCase						:				int	    =					False
					out_string += self.sp_model.decode(lowerCamelCase__       )
					return out_string.strip()




			def __getstate__(						self     :   Dict       )      ->List[Any]:



					'''simple docstring'''







					_UpperCAmelCase						:				List[str]	    =					self.__dict__.copy()
					_UpperCAmelCase						:				Optional[int]	    =					None
					return state




			def __setstate__(						self     :   Any		,     lowerCamelCase__     :   Dict       )      ->Tuple:



					'''simple docstring'''







					_UpperCAmelCase						:				Dict	    =					d

					# for backward compatibility
					if not hasattr(self		,     "sp_model_kwargs"       ):
							_UpperCAmelCase						:				List[Any]	    =					{}

					_UpperCAmelCase						:				Optional[int]	    =					spm.SentencePieceProcessor(**self.sp_model_kwargs       )
					self.sp_model.Load(self.vocab_file       )






			def 							lowerCAmelCase__			(						self     :   Optional[Any]		,     lowerCamelCase__     :   str		,     lowerCamelCase__     :   Optional[str] = None       )      ->Tuple[str]:



					'''simple docstring'''







					if not os.path.isdir(lowerCamelCase__       ):
							logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""       )
							return
					_UpperCAmelCase						:				Union[str, Any]	    =					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__       ) and os.path.isfile(self.vocab_file       ):
							copyfile(self.vocab_file		,     lowerCamelCase__       )
					elif not os.path.isfile(self.vocab_file       ):
							with open(lowerCamelCase__		,     "wb"       ) as fi:
									_UpperCAmelCase						:				Dict	    =					self.sp_model.serialized_model_proto()
									fi.write(lowerCamelCase__       )

					return (out_vocab_file,)



