

"""simple docstring"""






import json
from typing import Iterator, List, Union

from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors import TemplateProcessing







class       snake_case__  ( lowerCAmelCase_     ):







			def __init__(			self			: Optional[int]			,  lowercase			: str = "▁"			,  lowercase			: bool = True			,  lowercase			: Union[str, AddedToken] = "<unk>"			,  lowercase			: Union[str, AddedToken] = "</s>"			,  lowercase			: Union[str, AddedToken] = "<pad>"			,  ):





								'''simple docstring'''



								UpperCAmelCase			:   Any      =				{
								    "pad": {"id": 0, "token": pad_token},
								    "eos": {"id": 1, "token": eos_token},
								    "unk": {"id": 2, "token": unk_token},
								}

								UpperCAmelCase			:   List[Any]      =				[None] * len(self.special_tokens  )
								for token_dict in self.special_tokens.values():
													UpperCAmelCase			:   List[str]      =				token_dict["token"]

								UpperCAmelCase			:   List[str]      =				Tokenizer(Unigram()  )

								UpperCAmelCase			:   List[Any]      =				normalizers.Sequence(
								    [
								        normalizers.Nmt(),
								        normalizers.NFKC(),
								        normalizers.Replace(Regex(" {2,}"  )			,  " "  ),
								        normalizers.Lowercase(),
								    ]  )
								UpperCAmelCase			:   List[str]      =				pre_tokenizers.Sequence(
								    [
								        pre_tokenizers.Metaspace(replacement=lowercase			,  add_prefix_space=lowercase  ),
								        pre_tokenizers.Digits(individual_digits=lowercase  ),
								        pre_tokenizers.Punctuation(),
								    ]  )
								UpperCAmelCase			:   List[Any]      =				decoders.Metaspace(replacement=lowercase			,  add_prefix_space=lowercase  )

								UpperCAmelCase			:   List[str]      =				TemplateProcessing(
								    single=f"""$A {self.special_tokens['eos']['token']}"""			,  special_tokens=[(self.special_tokens["eos"]["token"], self.special_tokens["eos"]["id"])]			,  )

								UpperCAmelCase			:   str      =				{
								    "model": "SentencePieceUnigram",
								    "replacement": replacement,
								    "add_prefix_space": add_prefix_space,
								}

								super().__init__(lowercase			,  lowercase  )







			def 			__lowerCAmelCase				(			self			: Optional[int]			,  lowercase			: Union[str, List[str]]			,  lowercase			: int = 80_00			,  lowercase			: bool = True			,  ):





								'''simple docstring'''



								UpperCAmelCase			:   int      =				trainers.UnigramTrainer(
								    vocab_size=lowercase			,  special_tokens=self.special_tokens_list			,  show_progress=lowercase			,  )

								if isinstance(lowercase			,  lowercase  ):
													UpperCAmelCase			:   Any      =				[files]
								self._tokenizer.train(lowercase			,  trainer=lowercase  )

								self.add_unk_id()







			def 			__lowerCAmelCase				(			self			: Tuple			,  lowercase			: Union[Iterator[str], Iterator[Iterator[str]]]			,  lowercase			: int = 80_00			,  lowercase			: bool = True			,  ):





								'''simple docstring'''



								UpperCAmelCase			:   Dict      =				trainers.UnigramTrainer(
								    vocab_size=lowercase			,  special_tokens=self.special_tokens_list			,  show_progress=lowercase			,  )

								self._tokenizer.train_from_iterator(lowercase			,  trainer=lowercase  )

								self.add_unk_id()







			def 			__lowerCAmelCase				(			self			: Union[str, Any]  ):





								'''simple docstring'''



								UpperCAmelCase			:   Union[str, Any]      =				json.loads(self._tokenizer.to_str()  )

								UpperCAmelCase			:   Any      =				self.special_tokens["unk"]["id"]

								UpperCAmelCase			:   List[Any]      =				Tokenizer.from_str(json.dumps(lowercase  )  )





"""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


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

snake_case_   :   Tuple        =       {"""vocab_file""": """sentencepiece.bpe.model"""}

snake_case_   :   List[str]        =       {
    """vocab_file""": {
        """camembert-base""": """https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model""",
    }
}

snake_case_   :   List[Any]        =       {
    """camembert-base""": 5_1_2,
}

snake_case_   :   Any        =       """▁"""







class       snake_case__  ( lowerCAmelCase_     ):
			SCREAMING_SNAKE_CASE__     				=						VOCAB_FILES_NAMES
			SCREAMING_SNAKE_CASE__     				=						PRETRAINED_VOCAB_FILES_MAP
			SCREAMING_SNAKE_CASE__     				=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			SCREAMING_SNAKE_CASE__     				=						['''input_ids''', '''attention_mask''']







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





								'''simple docstring'''



								UpperCAmelCase			:   Optional[Any]      =				AddedToken(lowercase			,  lstrip=lowercase			,  rstrip=lowercase  ) if isinstance(lowercase			,  lowercase  ) else mask_token

								UpperCAmelCase			:   int      =				{} if sp_model_kwargs is None else sp_model_kwargs

								super().__init__(
								    bos_token=lowercase			,  eos_token=lowercase			,  unk_token=lowercase			,  sep_token=lowercase			,  cls_token=lowercase			,  pad_token=lowercase			,  mask_token=lowercase			,  additional_special_tokens=lowercase			,  sp_model_kwargs=self.sp_model_kwargs			,  **lowercase			,  )
								UpperCAmelCase			:   Tuple      =				spm.SentencePieceProcessor(**self.sp_model_kwargs  )
								self.sp_model.Load(str(lowercase  )  )
								UpperCAmelCase			:   str      =				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>
								UpperCAmelCase			:   Union[str, Any]      =				{"<s>NOTUSED": 0, "<pad>": 1, "</s>NOTUSED": 2, "<unk>": 3}
								UpperCAmelCase			:   Union[str, Any]      =				len(self.fairseq_tokens_to_ids  )
								UpperCAmelCase			:   Dict      =				len(self.sp_model  ) + len(self.fairseq_tokens_to_ids  )
								UpperCAmelCase			:   List[Any]      =				{v: k for k, v in self.fairseq_tokens_to_ids.items()}







			def 			__lowerCAmelCase				(			self			: Union[str, Any]			,  lowercase			: List[int]			,  lowercase			: Optional[List[int]] = None  ):





								'''simple docstring'''



								if token_ids_a is None:
													return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
								UpperCAmelCase			:   Dict      =				[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			: Dict			,  lowercase			: List[int]			,  lowercase			: Optional[List[int]] = None			,  lowercase			: bool = False  ):





								'''simple docstring'''



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

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







			def 			__lowerCAmelCase				(			self			: Tuple			,  lowercase			: List[int]			,  lowercase			: Optional[List[int]] = None  ):





								'''simple docstring'''



								UpperCAmelCase			:   Optional[Any]      =				[self.sep_token_id]
								UpperCAmelCase			:   List[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]







			@property
			def 			__lowerCAmelCase				(			self			: Optional[int]  ):





								'''simple docstring'''



								return len(self.fairseq_tokens_to_ids  ) + len(self.sp_model  )







			def 			__lowerCAmelCase				(			self			: List[Any]  ):





								'''simple docstring'''



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







			def 			__lowerCAmelCase				(			self			: Optional[Any]			,  lowercase			: str  ):





								'''simple docstring'''



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







			def 			__lowerCAmelCase				(			self			: int			,  lowercase			: Optional[Any]  ):





								'''simple docstring'''



								if token in self.fairseq_tokens_to_ids:
													return self.fairseq_tokens_to_ids[token]
								elif self.sp_model.PieceToId(lowercase  ) == 0:
													# Convert sentence piece unk token to fairseq unk token index
													return self.unk_token_id
								return self.fairseq_offset + self.sp_model.PieceToId(lowercase  )







			def 			__lowerCAmelCase				(			self			: Any			,  lowercase			: Dict  ):





								'''simple docstring'''



								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 			__lowerCAmelCase				(			self			: Tuple			,  lowercase			: Optional[int]  ):





								'''simple docstring'''



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







			def __getstate__(			self			: str  ):





								'''simple docstring'''



								UpperCAmelCase			:   List[str]      =				self.__dict__.copy()
								UpperCAmelCase			:   Dict      =				None
								return state







			def __setstate__(			self			: List[str]			,  lowercase			: str  ):





								'''simple docstring'''



								UpperCAmelCase			:   List[Any]      =				d

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

								UpperCAmelCase			:   List[Any]      =				spm.SentencePieceProcessor(**self.sp_model_kwargs  )
								self.sp_model.Load(self.vocab_file  )







			def 			__lowerCAmelCase				(			self			: Optional[Any]			,  lowercase			: str			,  lowercase			: Optional[str] = None  ):





								'''simple docstring'''



								if not os.path.isdir(lowercase  ):
													logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""  )
													return
								UpperCAmelCase			:   Optional[Any]      =				os.path.join(
								    lowercase			,  (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]  )

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

								return (out_vocab_file,)


