






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:
	lowercase    				=   None


lowercase    				=   logging.get_logger(__name__)

lowercase    				=   {"vocab_file": "sentencepiece.bpe.model", "tokenizer_file": "tokenizer.json"}

lowercase    				=   {
    "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",
    },
}

lowercase    				=   {
    "camembert-base": 512,
}

lowercase    				=   "▁"




class 					UpperCamelCase_ (     snake_case_							):



	'''simple docstring'''




	lowerCAmelCase						=					VOCAB_FILES_NAMES
	lowerCAmelCase						=					PRETRAINED_VOCAB_FILES_MAP
	lowerCAmelCase						=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	lowerCAmelCase						=					['''input_ids''', '''attention_mask''']
	lowerCAmelCase						=					CamembertTokenizer




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

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

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




	def 				_UpperCamelCase     (			self			,     a			,     a = None   )			->       List[int]:

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




	def 				_UpperCamelCase     (			self			,     a			,     a = None   )			->       List[int]:
								snake_case_           =				[self.sep_token_id]
								snake_case_           =				[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			,     a			,     a = 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(a   ):
															logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''   )
															return
								snake_case_           =				os.path.join(
								    a			,     (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']   )

								if os.path.abspath(self.vocab_file   ) != os.path.abspath(a   ):
															copyfile(self.vocab_file			,     a   )

								return (out_vocab_file,)













import numpy as np





def 		__UpperCAmelCase     (	a_):
							return 1 / (1 + np.exp(-vector))


if __name__ == "__main__":
	import doctest

	doctest.testmod()





