
'''simple docstring'''
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					:    Optional[int]           = None


lowerCAmelCase					:    str           = logging.get_logger(__name__)

lowerCAmelCase					:    Tuple           = {'vocab_file': 'sentencepiece.bpe.model', 'tokenizer_file': 'tokenizer.json'}

lowerCAmelCase					:    Any           = {
    '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					:    Union[str, Any]           = {
    'camembert-base': 5_12,
}

lowerCAmelCase					:    Tuple           = '▁'


class 			SCREAMING_SNAKE_CASE__      (     snake_case_):
				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_						,				)->		str:







											'''simple docstring'''






											UpperCamelCase   			=     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_						,				)

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







				def 						UpperCAmelCase_    (       self						,				A_						,				A_ = None     )->		List[int]:







											'''simple docstring'''






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







				def 						UpperCAmelCase_    (       self						,				A_						,				A_ = None     )->		List[int]:







											'''simple docstring'''






											UpperCamelCase   			=     [self.sep_token_id]
											UpperCamelCase   			=     [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]:







											'''simple docstring'''






											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
											UpperCamelCase   			=     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,)






'''simple docstring'''
def 		A_(     A						:		list[int]):
							UpperCamelCase   			=     []
							if len(A) == 1:
														return [nums.copy()]
							for _ in range(len(A)):
														UpperCamelCase   			=     nums.pop(0)
														UpperCamelCase   			=     permute(A)
														for perm in permutations:
																					perm.append(A)
														result.extend(A)
														nums.append(A)
							return result







def 		A_(     A						:		str):

							def backtrack(A						:		str):
														if start == len(A) - 1:
																					output.append(nums[:])
														else:
																					for i in range(A		,     len(A)):
																												UpperCamelCase			,	UpperCamelCase   			=     nums[i], nums[start]
																												backtrack(start + 1)
																												UpperCamelCase			,	UpperCamelCase   			=     nums[i], nums[start]  # backtrack

							UpperCamelCase   			=     []
							backtrack(0)
							return output


if __name__ == "__main__":
						import doctest

						# use res to print the data in permute2 function
						lowerCAmelCase					:    Dict           = permutea([1, 2, 3])
						print(res)
						doctest.testmod()




