





import warnings

from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor


__A             =       logging.get_logger(__name__)



class      _SCREAMING_SNAKE_CASE		(			__SCREAMING_SNAKE_CASE					):







 '''simple docstring'''

 def __init__(self       :     List[Any] ,				*UpperCAmelCase_       :     Union[str, Any] ,				**UpperCAmelCase_       :     Tuple) ->None:



   '''simple docstring'''



   warnings.warn(
       "The class VideoMAEFeatureExtractor is deprecated and will be removed in version 5 of Transformers."
       " Please use VideoMAEImageProcessor instead." ,				UpperCAmelCase_ ,				)
   super().__init__(*UpperCAmelCase_ ,				**UpperCAmelCase_)













import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer


__A             =       logging.get_logger(__name__)

__A             =       {"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}

__A             =       {
    "vocab_file": {
        "squeezebert/squeezebert-uncased": (
            "https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/vocab.txt"
        ),
        "squeezebert/squeezebert-mnli": "https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/vocab.txt",
        "squeezebert/squeezebert-mnli-headless": (
            "https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/vocab.txt"
        ),
    },
    "tokenizer_file": {
        "squeezebert/squeezebert-uncased": (
            "https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/tokenizer.json"
        ),
        "squeezebert/squeezebert-mnli": (
            "https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/tokenizer.json"
        ),
        "squeezebert/squeezebert-mnli-headless": (
            "https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/tokenizer.json"
        ),
    },
}

__A             =       {
    "squeezebert/squeezebert-uncased": 512,
    "squeezebert/squeezebert-mnli": 512,
    "squeezebert/squeezebert-mnli-headless": 512,
}


__A             =       {
    "squeezebert/squeezebert-uncased": {"do_lower_case": True},
    "squeezebert/squeezebert-mnli": {"do_lower_case": True},
    "squeezebert/squeezebert-mnli-headless": {"do_lower_case": True},
}



class      _SCREAMING_SNAKE_CASE		(			__SCREAMING_SNAKE_CASE					):







 '''simple docstring'''
 lowercase_	=    VOCAB_FILES_NAMES
 lowercase_	=    PRETRAINED_VOCAB_FILES_MAP
 lowercase_	=    PRETRAINED_INIT_CONFIGURATION
 lowercase_	=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowercase_	=    SqueezeBertTokenizer

 def __init__(self       :     Any ,				UpperCAmelCase_       :     int=None ,				UpperCAmelCase_       :     List[str]=None ,				UpperCAmelCase_       :     int=True ,				UpperCAmelCase_       :     Optional[int]="[UNK]" ,				UpperCAmelCase_       :     int="[SEP]" ,				UpperCAmelCase_       :     Optional[Any]="[PAD]" ,				UpperCAmelCase_       :     Optional[int]="[CLS]" ,				UpperCAmelCase_       :     str="[MASK]" ,				UpperCAmelCase_       :     Union[str, Any]=True ,				UpperCAmelCase_       :     Optional[Any]=None ,				**UpperCAmelCase_       :     Dict ,				) ->Union[str, Any]:



   '''simple docstring'''



   super().__init__(
       UpperCAmelCase_ ,				tokenizer_file=UpperCAmelCase_ ,				do_lower_case=UpperCAmelCase_ ,				unk_token=UpperCAmelCase_ ,				sep_token=UpperCAmelCase_ ,				pad_token=UpperCAmelCase_ ,				cls_token=UpperCAmelCase_ ,				mask_token=UpperCAmelCase_ ,				tokenize_chinese_chars=UpperCAmelCase_ ,				strip_accents=UpperCAmelCase_ ,				**UpperCAmelCase_ ,				)

   lowerCamelCase__:   Dict    						=json.loads(self.backend_tokenizer.normalizer.__getstate__())
   if (
       normalizer_state.get("lowercase" ,				UpperCAmelCase_) != do_lower_case
       or normalizer_state.get("strip_accents" ,				UpperCAmelCase_) != strip_accents
       or normalizer_state.get("handle_chinese_chars" ,				UpperCAmelCase_) != tokenize_chinese_chars
   ):
     lowerCamelCase__:   Any    						=getattr(UpperCAmelCase_ ,				normalizer_state.pop("type"))
     lowerCamelCase__:   Union[str, Any]    						=do_lower_case
     lowerCamelCase__:   Optional[Any]    						=strip_accents
     lowerCamelCase__:   Optional[int]    						=tokenize_chinese_chars
     lowerCamelCase__:   int    						=normalizer_class(**UpperCAmelCase_)

   lowerCamelCase__:   Any    						=do_lower_case

 def 							SCREAMING_SNAKE_CASE_      (self       :     str ,				UpperCAmelCase_       :     List[str] ,				UpperCAmelCase_       :     str=None) ->Dict:



   '''simple docstring'''



   lowerCamelCase__:   List[str]    						=[self.cls_token_id] + token_ids_a + [self.sep_token_id]

   if token_ids_a:
     output += token_ids_a + [self.sep_token_id]

   return output

 def 							SCREAMING_SNAKE_CASE_      (self       :     Optional[int] ,				UpperCAmelCase_       :     List[int] ,				UpperCAmelCase_       :     Optional[List[int]] = None) ->List[int]:



   '''simple docstring'''



   lowerCamelCase__:   Dict    						=[self.sep_token_id]
   lowerCamelCase__:   Tuple    						=[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'''



   lowerCamelCase__:   Optional[int]    						=self._tokenizer.model.save(UpperCAmelCase_ ,				name=UpperCAmelCase_)
   return tuple(UpperCAmelCase_)

