






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': 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,
}

lowerCAmelCase_           = '▁'
class      UpperCamelCase (				snake_case__ ):







		"""simple docstring"""



		snake_case    =   VOCAB_FILES_NAMES
		snake_case    =   PRETRAINED_VOCAB_FILES_MAP
		snake_case    =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		snake_case    =   AlbertTokenizer
		def __init__(  self		:       str						,_SCREAMING_SNAKE_CASE		:       int=None						,_SCREAMING_SNAKE_CASE		:       List[str]=None						,_SCREAMING_SNAKE_CASE		:       List[str]=True						,_SCREAMING_SNAKE_CASE		:       str=True						,_SCREAMING_SNAKE_CASE		:       Optional[int]=False						,_SCREAMING_SNAKE_CASE		:       List[str]="[CLS]"						,_SCREAMING_SNAKE_CASE		:       Optional[int]="[SEP]"						,_SCREAMING_SNAKE_CASE		:       Tuple="<unk>"						,_SCREAMING_SNAKE_CASE		:       Union[str, Any]="[SEP]"						,_SCREAMING_SNAKE_CASE		:       Tuple="<pad>"						,_SCREAMING_SNAKE_CASE		:       Any="[CLS]"						,_SCREAMING_SNAKE_CASE		:       Optional[int]="[MASK]"						,**_SCREAMING_SNAKE_CASE		:       Any						,)    ->   Tuple:


						'''simple docstring'''
						# 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.
						A	 =      (
						    AddedToken(_SCREAMING_SNAKE_CASE						,lstrip=_SCREAMING_SNAKE_CASE						,rstrip=_SCREAMING_SNAKE_CASE						,normalized=_SCREAMING_SNAKE_CASE		)
						    if isinstance(_SCREAMING_SNAKE_CASE						,_SCREAMING_SNAKE_CASE		)
						    else mask_token
						)

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

						A	 =      do_lower_case
						A	 =      remove_space
						A	 =      keep_accents
						A	 =      vocab_file
						A	 =      False if not self.vocab_file else True
		def       A(  self		:       int						,_SCREAMING_SNAKE_CASE		:       List[int]						,_SCREAMING_SNAKE_CASE		:       Optional[List[int]] = None		)    ->   List[int]:


						'''simple docstring'''
						A	 =      [self.sep_token_id]
						A	 =      [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		:       List[Any]						,_SCREAMING_SNAKE_CASE		:       List[int]						,_SCREAMING_SNAKE_CASE		:       Optional[List[int]] = None		)    ->   List[int]:


						'''simple docstring'''
						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		) * [0] + len(token_ids_a + sep		) * [1]







		def       A(  self		:       Union[str, Any]						,_SCREAMING_SNAKE_CASE		:       str						,_SCREAMING_SNAKE_CASE		:       Optional[str] = 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(_SCREAMING_SNAKE_CASE		):
										logger.error(f'Vocabulary path ({save_directory}) should be a directory'		)
										return
						A	 =      os.path.join(
						    _SCREAMING_SNAKE_CASE						,(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']		)

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

						return (out_vocab_file,)













def      snake_case		(							UpperCAmelCase	:       int   ):
				A	 =      0
				while num > 0:
								digit_sum += num % 10
								num //= 10
				return digit_sum







def      snake_case		(							UpperCAmelCase	:       int = 1_00   ):
				A	 =      1
				A	 =      2

				for i in range(2,						max_n + 1   ):
								A	 =      pre_numerator
								A	 =      2 * i // 3 if i % 3 == 0 else 1
								A	 =      cur_numerator
								A	 =      e_cont * pre_numerator + temp

				return sum_digits(UpperCAmelCase   )


if __name__ == "__main__":
					print(f'''{solution() = }''')





