


'''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:
       lowerCAmelCase    :     int					=						None

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

lowerCAmelCase    :     Tuple					=						{
    """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    :     Dict					=						{
    """albert-base-v1""": 5_12,
    """albert-large-v1""": 5_12,
    """albert-xlarge-v1""": 5_12,
    """albert-xxlarge-v1""": 5_12,
    """albert-base-v2""": 5_12,
    """albert-large-v2""": 5_12,
    """albert-xlarge-v2""": 5_12,
    """albert-xxlarge-v2""": 5_12,
}

lowerCAmelCase    :     Optional[int]					=						"""▁"""
class 	UpperCamelCase__					( SCREAMING_SNAKE_CASE_	):



     """simple docstring"""






     __magic_name__    			=    VOCAB_FILES_NAMES
     __magic_name__    			=    PRETRAINED_VOCAB_FILES_MAP
     __magic_name__    			=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     __magic_name__    			=    AlbertTokenizer







     def __init__( self      ,	snake_case__=None      ,	snake_case__=None      ,	snake_case__=True      ,	snake_case__=True      ,	snake_case__=False      ,	snake_case__="[CLS]"      ,	snake_case__="[SEP]"      ,	snake_case__="<unk>"      ,	snake_case__="[SEP]"      ,	snake_case__="<pad>"      ,	snake_case__="[CLS]"      ,	snake_case__="[MASK]"      ,	**snake_case__      ,	):

            '''simple docstring'''

            _lowerCAmelCase    :							Optional[int]   			=       (
                AddedToken(snake_case__      ,	lstrip=snake_case__      ,	rstrip=snake_case__      ,	normalized=snake_case__   )
                if isinstance(snake_case__      ,	snake_case__   )
                else mask_token
            )

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

            _lowerCAmelCase    :							Dict   			=       do_lower_case
            _lowerCAmelCase    :							Tuple   			=       remove_space
            _lowerCAmelCase    :							Optional[int]   			=       keep_accents
            _lowerCAmelCase    :							Optional[Any]   			=       vocab_file
            _lowerCAmelCase    :							Tuple   			=       False if not self.vocab_file else True







     def a	( self      ,	snake_case__      ,	snake_case__ = None   ):

            '''simple docstring'''

            _lowerCAmelCase    :							Optional[Any]   			=       [self.sep_token_id]
            _lowerCAmelCase    :							Optional[int]   			=       [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      ,	snake_case__      ,	snake_case__ = None   ):

            '''simple docstring'''

            _lowerCAmelCase    :							List[str]   			=       [self.sep_token_id]
            _lowerCAmelCase    :							List[Any]   			=       [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      ,	snake_case__      ,	snake_case__ = None   ):

            '''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(snake_case__   ):
                   logger.error(F'Vocabulary path ({save_directory}) should be a directory'   )
                   return
            _lowerCAmelCase    :							Optional[Any]   			=       os.path.join(
                snake_case__      ,	(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']   )

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

            return (out_vocab_file,)





'''simple docstring'''







from collections import Counter
from timeit import timeit






def 			lowercase				(_A = ""   ,						):







       """simple docstring"""







       return sum(c % 2 for c in Counter(input_str.replace(' '   ,						''					).lower()					).values()					) < 2






def 			lowercase				(_A = ""					):







       """simple docstring"""







       if len(_A					) == 0:
              return True
       _lowerCAmelCase    :							Union[str, Any]   			=       input_str.replace(' '   ,						''					).lower()
       # character_freq_dict: Stores the frequency of every character in the input string
       _lowerCAmelCase    :							dict[str, int]   			=       {}

       for character in lower_case_input_str:
              _lowerCAmelCase    :							Union[str, Any]   			=       character_freq_dict.get(_A   ,						0					) + 1
       _lowerCAmelCase    :							List[Any]   			=       0

       for character_count in character_freq_dict.values():
              if character_count % 2:
                     odd_char += 1
       if odd_char > 1:
              return False
       return True






def 			lowercase				(_A = ""					):







       """simple docstring"""







       print('\nFor string = '   ,						_A   ,						':'					)
       print(
           '> can_string_be_rearranged_as_palindrome_counter()'   ,						'\tans ='   ,						can_string_be_rearranged_as_palindrome_counter(_A					)   ,						'\ttime ='   ,						timeit(
               'z.can_string_be_rearranged_as_palindrome_counter(z.check_str)'   ,						setup='import __main__ as z'   ,						)   ,						'seconds'   ,						)
       print(
           '> can_string_be_rearranged_as_palindrome()'   ,						'\tans ='   ,						can_string_be_rearranged_as_palindrome(_A					)   ,						'\ttime ='   ,						timeit(
               'z.can_string_be_rearranged_as_palindrome(z.check_str)'   ,						setup='import __main__ as z'   ,						)   ,						'seconds'   ,						)


if __name__ == "__main__":
       lowerCAmelCase    :     Tuple					=						input(
           """Enter string to determine if it can be rearranged as a palindrome or not: """
       ).strip()
       benchmark(check_str)
       lowerCAmelCase    :     Optional[Any]					=						can_string_be_rearranged_as_palindrome_counter(check_str)
       print(F'''{check_str} can {"" if status else "not "}be rearranged as a palindrome''')

