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:
						A_      =      None

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

A_      =      {
    "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",
    },
}

A_      =      {
    "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,
}

A_      =      "▁"






class      __lowercase					(    _A    ):
						lowercase					 =     VOCAB_FILES_NAMES
						lowercase					 =     PRETRAINED_VOCAB_FILES_MAP
						lowercase					 =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						lowercase					 =     AlbertTokenizer

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


									'''simple docstring'''

									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				:      int							,							__lowerCamelCase				:      List[int]							,							__lowerCamelCase				:      Optional[List[int]] = None   )							->		List[int]:


									'''simple docstring'''

									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				:      Tuple							,							__lowerCamelCase				:      List[int]							,							__lowerCamelCase				:      Optional[List[int]] = None   )							->		List[int]:


									'''simple docstring'''

									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				:      Optional[int]							,							__lowerCamelCase				:      str							,							__lowerCamelCase				:      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(__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,)






def        __UpperCAmelCase    (       UpperCAmelCase,		UpperCAmelCase       )->       int:



			"""simple docstring"""







			while a != 0:
						lowercase		,lowercase							=		b % a, a
			return b






def        __UpperCAmelCase    (       UpperCAmelCase,		UpperCAmelCase       )->       int:



			"""simple docstring"""







			if gcd(UpperCAmelCase,		UpperCAmelCase       ) != 1:
						lowercase							=		f'mod inverse of {a!r} and {m!r} does not exist'
						raise ValueError(UpperCAmelCase       )
			lowercase		,lowercase		,lowercase							=		1, 0, a
			lowercase		,lowercase		,lowercase							=		0, 1, m
			while va != 0:
						lowercase							=		ua // va
						lowercase		,lowercase		,lowercase		,lowercase		,lowercase		,lowercase							=		(ua - q * va), (ua - q * va), (ua - q * va), va, va, va
			return ua % m





