


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:
	lowerCAmelCase           =		None

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

lowerCAmelCase           =		{
    '''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''',
    },
}

lowerCAmelCase           =		{
    '''albert-base-v1''': 5_1_2,
    '''albert-large-v1''': 5_1_2,
    '''albert-xlarge-v1''': 5_1_2,
    '''albert-xxlarge-v1''': 5_1_2,
    '''albert-base-v2''': 5_1_2,
    '''albert-large-v2''': 5_1_2,
    '''albert-xlarge-v2''': 5_1_2,
    '''albert-xxlarge-v2''': 5_1_2,
}

lowerCAmelCase           =		'''▁'''





class       A    (   A_ ):
							UpperCamelCase_   :							Any       =VOCAB_FILES_NAMES
							UpperCamelCase_   :							List[str]       =PRETRAINED_VOCAB_FILES_MAP
							UpperCamelCase_   :							List[Any]       =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							UpperCamelCase_   :							Dict       =AlbertTokenizer


							def __init__(self      ,				lowerCAmelCase=None      ,				lowerCAmelCase=None      ,				lowerCAmelCase=True      ,				lowerCAmelCase=True      ,				lowerCAmelCase=False      ,				lowerCAmelCase="[CLS]"      ,				lowerCAmelCase="[SEP]"      ,				lowerCAmelCase="<unk>"      ,				lowerCAmelCase="[SEP]"      ,				lowerCAmelCase="<pad>"      ,				lowerCAmelCase="[CLS]"      ,				lowerCAmelCase="[MASK]"      ,				**lowerCAmelCase      ,				):
									# 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.
									__lowercase=			(
									    AddedToken(lowerCAmelCase      ,				lstrip=lowerCAmelCase      ,				rstrip=lowerCAmelCase      ,				normalized=lowerCAmelCase					)
									    if isinstance(lowerCAmelCase      ,				lowerCAmelCase					)
									    else mask_token
									)

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

									__lowercase=			do_lower_case
									__lowercase=			remove_space
									__lowercase=			keep_accents
									__lowercase=			vocab_file
									__lowercase=			False if not self.vocab_file else True


							def 			_A       (self      ,				lowerCAmelCase      ,				lowerCAmelCase = None					):
									__lowercase=			[self.sep_token_id]
									__lowercase=			[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 			_A       (self      ,				lowerCAmelCase      ,				lowerCAmelCase = None					):
									__lowercase=			[self.sep_token_id]
									__lowercase=			[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 			_A       (self      ,				lowerCAmelCase      ,				lowerCAmelCase = None					):
									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
									__lowercase=			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,)










from __future__ import annotations







def        _lowerCamelCase(	lowercase__	)						->	list[int]:

		'''simple docstring'''







		__lowercase=			2
		__lowercase=			[]
		while i * i <= n:
				if n % i:
						i += 1
				else:
						n //= i
						factors.append(lowercase__	)
		if n > 1:
				factors.append(lowercase__	)
		return factors


if __name__ == "__main__":
	import doctest

	doctest.testmod()






