




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:
   lowercase__				:      List[Any]	   = None

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

lowercase__				:      Union[str, 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",
    },
}

lowercase__				:      int	   = {
    "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,
}

lowercase__				:      List[Any]	   = "▁"




class       a__	( UpperCamelCase__				):
     a		:      int		 =     VOCAB_FILES_NAMES
     a		:      Union[str, Any]		 =     PRETRAINED_VOCAB_FILES_MAP
     a		:      Optional[int]		 =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     a		:      int		 =     AlbertTokenizer







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



          '''simple docstring'''



          a     =				(
              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_  ,		)

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







     def       lowerCAmelCase_    (     self  ,		A  ,		A = 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       lowerCAmelCase_    (     self  ,		A  ,		A = 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       lowerCAmelCase_    (     self  ,		A  ,		A = 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
          a     =				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,)










lowercase__				:      Optional[int]	   = [
    "DownloadConfig",
    "DownloadManager",
    "DownloadMode",
    "StreamingDownloadManager",
]

from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import StreamingDownloadManager

