




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

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
		from .tokenization_camembert import CamembertTokenizer
else:
		__lowerCAmelCase		:				Any       			=		None


__lowerCAmelCase		:				Dict       			=		logging.get_logger(__name__)

__lowerCAmelCase		:				Optional[int]       			=		{'vocab_file': 'sentencepiece.bpe.model', 'tokenizer_file': 'tokenizer.json'}

__lowerCAmelCase		:				Dict       			=		{
    'vocab_file': {
        'camembert-base': 'https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model',
    },
    'tokenizer_file': {
        'camembert-base': 'https://huggingface.co/camembert-base/resolve/main/tokenizer.json',
    },
}

__lowerCAmelCase		:				str       			=		{
    'camembert-base': 512,
}

__lowerCAmelCase		:				Dict       			=		'▁'




class     snake_case__							(_UpperCamelCase   ):
				"""simple docstring"""



				SCREAMING_SNAKE_CASE_       :							List[str]							 =					VOCAB_FILES_NAMES
				SCREAMING_SNAKE_CASE_       :							Any							 =					PRETRAINED_VOCAB_FILES_MAP
				SCREAMING_SNAKE_CASE_       :							str							 =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				SCREAMING_SNAKE_CASE_       :							Optional[int]							 =					["""input_ids""", """attention_mask"""]
				SCREAMING_SNAKE_CASE_       :							Any							 =					CamembertTokenizer





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

							super().__init__(
							    __lowerCamelCase					,      tokenizer_file=__lowerCamelCase					,      bos_token=__lowerCamelCase					,      eos_token=__lowerCamelCase					,      sep_token=__lowerCamelCase					,      cls_token=__lowerCamelCase					,      unk_token=__lowerCamelCase					,      pad_token=__lowerCamelCase					,      mask_token=__lowerCamelCase					,      additional_special_tokens=__lowerCamelCase					,      **__lowerCamelCase					,      )

							a    =			vocab_file
							a    =			False if not self.vocab_file else True





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

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





				def 							__UpperCAmelCase							(      self				:     Tuple					,      __lowerCamelCase				:     List[int]					,      __lowerCamelCase				:     Optional[List[int]] = None							)					->     List[int]:
							a    =			[self.sep_token_id]
							a    =			[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 							__UpperCAmelCase							(      self				:     List[Any]					,      __lowerCamelCase				:     str					,      __lowerCamelCase				:     Optional[str] = None							)					->     Tuple[str]:
							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
							a    =			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,)









"""simple docstring"""





def   __SCREAMING_SNAKE_CASE  (      A_						,     A_ ):
	return numa ^ numa < 0


if __name__ == "__main__":
							import doctest

							doctest.testmod()




