




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      :						List[str]							=  None

_lowerCamelCase      :						str							=  logging.get_logger(__name__)
_lowerCamelCase      :						Tuple							=  {"""vocab_file""": """spiece.model""", """tokenizer_file""": """tokenizer.json"""}

_lowerCamelCase      :						Any							=  {
    """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      :						Any							=  {
    """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      :						Any							=  """▁"""


class 							UpperCamelCase_       (					UpperCAmelCase__	):

    '''simple docstring'''






    UpperCAmelCase__				    = VOCAB_FILES_NAMES
    UpperCAmelCase__				    = PRETRAINED_VOCAB_FILES_MAP
    UpperCAmelCase__				    = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    UpperCAmelCase__				    = AlbertTokenizer


    def __init__(     self :      int   ,					UpperCAmelCase__ :      int=None   ,					UpperCAmelCase__ :      Dict=None   ,					UpperCAmelCase__ :      Optional[Any]=True   ,					UpperCAmelCase__ :      Optional[int]=True   ,					UpperCAmelCase__ :      List[Any]=False   ,					UpperCAmelCase__ :      Optional[Any]="[CLS]"   ,					UpperCAmelCase__ :      str="[SEP]"   ,					UpperCAmelCase__ :      int="<unk>"   ,					UpperCAmelCase__ :      Union[str, Any]="[SEP]"   ,					UpperCAmelCase__ :      Dict="<pad>"   ,					UpperCAmelCase__ :      List[Any]="[CLS]"   ,					UpperCAmelCase__ :      str="[MASK]"   ,					**UpperCAmelCase__ :      int   ,					)		->str:





           '''simple docstring'''

           A__ 					=       (
               AddedToken(UpperCAmelCase__   ,					lstrip=UpperCAmelCase__   ,					rstrip=UpperCAmelCase__   ,					normalized=UpperCAmelCase__)
               if isinstance(UpperCAmelCase__   ,					UpperCAmelCase__)
               else mask_token
           )

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

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


    def 			SCREAMING_SNAKE_CASE				(     self :      Any   ,					UpperCAmelCase__ :      List[int]   ,					UpperCAmelCase__ :      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 			SCREAMING_SNAKE_CASE				(     self :      Dict   ,					UpperCAmelCase__ :      List[int]   ,					UpperCAmelCase__ :      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 			SCREAMING_SNAKE_CASE				(     self :      Union[str, Any]   ,					UpperCAmelCase__ :      str   ,					UpperCAmelCase__ :      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(UpperCAmelCase__):
                  logger.error(f"""Vocabulary path ({save_directory}) should be a directory""")
                  return
           A__ 					=       os.path.join(
               UpperCAmelCase__   ,					(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file'''])

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

           return (out_vocab_file,)










def 		__UpperCAmelCase     (	a_ = 10**9):
							snake_case_           =				1
							snake_case_           =				2

							snake_case_           =				0
							snake_case_           =				0
							snake_case_           =				0
							while perimeter <= max_perimeter:
														perimeters_sum += perimeter

														prev_value += 2 * value
														value += prev_value

														snake_case_           =				2 * value + 2 if i % 2 == 0 else 2 * value - 2
														i += 1

							return perimeters_sum


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





