



"""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:
			__SCREAMING_SNAKE_CASE	:    List[str]     				=   None

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

__SCREAMING_SNAKE_CASE	:    List[str]     				=   {
    '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',
    },
}

__SCREAMING_SNAKE_CASE	:    Optional[Any]     				=   {
    '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,
}

__SCREAMING_SNAKE_CASE	:    Any     				=   '▁'


class 				lowerCamelCase_( _SCREAMING_SNAKE_CASE     ):





					'''simple docstring'''



					lowercase__ :							Any              =			VOCAB_FILES_NAMES
					lowercase__ :							Union[str, Any]              =			PRETRAINED_VOCAB_FILES_MAP
					lowercase__ :							List[str]              =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					lowercase__ :							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.
									_lowerCamelCase   	=					(
									    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					,							)

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

					def       snake_case__   (     self					,							lowerCamelCase__					,							lowerCamelCase__ = None ):
									_lowerCamelCase   	=					[self.sep_token_id]
									_lowerCamelCase   	=					[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					,							lowerCamelCase__					,							lowerCamelCase__ = None ):
									_lowerCamelCase   	=					[self.sep_token_id]
									_lowerCamelCase   	=					[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					,							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
									_lowerCamelCase   	=					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

from collections.abc import Iterator





class 			lowerCamelCase_				:


 '''simple docstring'''







 def __init__(				self    :						Union[str, Any]							,							_lowerCAmelCase    :						int		):
       SCREAMING_SNAKE_CASE_      		=     value
       SCREAMING_SNAKE_CASE_      		=     None
       SCREAMING_SNAKE_CASE_      		=     None





class 			lowerCamelCase_				:


 '''simple docstring'''







 def __init__(				self    :						int							,							_lowerCAmelCase    :						Node		):
       SCREAMING_SNAKE_CASE_      		=     tree



 def  lowerCAmelCase_    (				self    :						Union[str, Any]							,							_lowerCAmelCase    :						Node | None		):
       if node is None:
             return 0
       return node.value + (
           self.depth_first_search(node.left		) + self.depth_first_search(node.right		)
       )




 def __iter__(				self    :						Dict		):
       yield self.depth_first_search(self.tree		)


if __name__ == "__main__":
   import doctest

   doctest.testmod()