






"""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_albert import AlbertTokenizer
else:
			lowercase    			=       None

lowercase    			=       logging.get_logger(__name__)
lowercase    			=       {'''vocab_file''': '''spiece.model''', '''tokenizer_file''': '''tokenizer.json'''}

lowercase    			=       {
    '''vocab_file''': {
        '''albert-base-v1''': '''https://huggingface.co/albert-base-v1/resolve/main/spiece.model''',
        '''albert-large-v1''': '''https://huggingface.co/albert-large-v1/resolve/main/spiece.model''',
        '''albert-xlarge-v1''': '''https://huggingface.co/albert-xlarge-v1/resolve/main/spiece.model''',
        '''albert-xxlarge-v1''': '''https://huggingface.co/albert-xxlarge-v1/resolve/main/spiece.model''',
        '''albert-base-v2''': '''https://huggingface.co/albert-base-v2/resolve/main/spiece.model''',
        '''albert-large-v2''': '''https://huggingface.co/albert-large-v2/resolve/main/spiece.model''',
        '''albert-xlarge-v2''': '''https://huggingface.co/albert-xlarge-v2/resolve/main/spiece.model''',
        '''albert-xxlarge-v2''': '''https://huggingface.co/albert-xxlarge-v2/resolve/main/spiece.model''',
    },
    '''tokenizer_file''': {
        '''albert-base-v1''': '''https://huggingface.co/albert-base-v1/resolve/main/tokenizer.json''',
        '''albert-large-v1''': '''https://huggingface.co/albert-large-v1/resolve/main/tokenizer.json''',
        '''albert-xlarge-v1''': '''https://huggingface.co/albert-xlarge-v1/resolve/main/tokenizer.json''',
        '''albert-xxlarge-v1''': '''https://huggingface.co/albert-xxlarge-v1/resolve/main/tokenizer.json''',
        '''albert-base-v2''': '''https://huggingface.co/albert-base-v2/resolve/main/tokenizer.json''',
        '''albert-large-v2''': '''https://huggingface.co/albert-large-v2/resolve/main/tokenizer.json''',
        '''albert-xlarge-v2''': '''https://huggingface.co/albert-xlarge-v2/resolve/main/tokenizer.json''',
        '''albert-xxlarge-v2''': '''https://huggingface.co/albert-xxlarge-v2/resolve/main/tokenizer.json''',
    },
}

lowercase    			=       {
    '''albert-base-v1''': 512,
    '''albert-large-v1''': 512,
    '''albert-xlarge-v1''': 512,
    '''albert-xxlarge-v1''': 512,
    '''albert-base-v2''': 512,
    '''albert-large-v2''': 512,
    '''albert-xlarge-v2''': 512,
    '''albert-xxlarge-v2''': 512,
}

lowercase    			=       '''▁'''

class 						A_							(      _a  ):
				UpperCAmelCase__        =				VOCAB_FILES_NAMES
				UpperCAmelCase__        =				PRETRAINED_VOCAB_FILES_MAP
				UpperCAmelCase__        =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				UpperCAmelCase__        =				AlbertTokenizer







				def __init__(							self							:						str						,    __lowerCamelCase							:						str=None						,    __lowerCamelCase							:						List[str]=None						,    __lowerCamelCase							:						Any=True						,    __lowerCamelCase							:						Optional[int]=True						,    __lowerCamelCase							:						Union[str, Any]=False						,    __lowerCamelCase							:						Optional[int]="[CLS]"						,    __lowerCamelCase							:						str="[SEP]"						,    __lowerCamelCase							:						int="<unk>"						,    __lowerCamelCase							:						int="[SEP]"						,    __lowerCamelCase							:						Optional[Any]="<pad>"						,    __lowerCamelCase							:						List[str]="[CLS]"						,    __lowerCamelCase							:						Optional[Any]="[MASK]"						,    **__lowerCamelCase							:						int						,    )				->					str:
										# Mask token behave like a normal word, i.e. include the space before it and
										# is included in the raw text, there should be a match in a non-normalized sentence.
										__magic_name__     :   Any            =     (
										    AddedToken(_A						,    lstrip=_A						,    rstrip=_A						,    normalized=_A	)
										    if isinstance(_A						,    _A	)
										    else mask_token
										)

										super().__init__(
										    _A						,    tokenizer_file=_A						,    do_lower_case=_A						,    remove_space=_A						,    keep_accents=_A						,    bos_token=_A						,    eos_token=_A						,    unk_token=_A						,    sep_token=_A						,    pad_token=_A						,    cls_token=_A						,    mask_token=_A						,    **_A						,    )

										__magic_name__     :   List[str]            =     do_lower_case
										__magic_name__     :   int            =     remove_space
										__magic_name__     :   int            =     keep_accents
										__magic_name__     :   Tuple            =     vocab_file
										__magic_name__     :   List[str]            =     False if not self.vocab_file else True







				def     _snake_case					(							self							:						List[Any]						,    __lowerCamelCase							:						Union[str, Any]						,    __lowerCamelCase							:						int = None	)				->					Optional[int]:
										__magic_name__     :   str            =     [self.sep_token_id]
										__magic_name__     :   Any            =     [self.cls_token_id]
										if token_ids_a is None:
																return cls + token_ids_a + sep
										return cls + token_ids_a + sep + token_ids_a + sep







				def     _snake_case					(							self							:						Optional[int]						,    __lowerCamelCase							:						List[str]						,    __lowerCamelCase							:						Optional[int] = None	)				->					Optional[int]:
										__magic_name__     :   Union[str, Any]            =     [self.sep_token_id]
										__magic_name__     :   Tuple            =     [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	) * [0] + len(token_ids_a + sep	) * [1]







				def     _snake_case					(							self							:						List[Any]						,    __lowerCamelCase							:						Union[str, Any]						,    __lowerCamelCase							:						Dict = None	)				->					Dict:
										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
										__magic_name__     :   Union[str, Any]            =     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 _lowerCAmelCase	(  __lowerCamelCase:int   ):

						'''simple docstring'''






						__magic_name__            =     n ** (1 / 3)
						return (val * val * val) == n


if __name__ == "__main__":
			print(perfect_cube(27))
			print(perfect_cube(4))



