
'''simple docstring'''






import warnings
from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType

class 			UpperCAmelCase__    (							A			):
    lowerCAmelCase_					     =		['image_processor', 'tokenizer']
    lowerCAmelCase_					     =		'ViltImageProcessor'
    lowerCAmelCase_					     =		('BertTokenizer', 'BertTokenizerFast')



    def __init__(						self   :							str,__A   :							int=None,__A   :							Optional[int]=None,**__A   :							Union[str, Any]  ):
          _lowerCamelCase					: int		    = None
          if "feature_extractor" in kwargs:
                warnings.warn(
                    "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
                    " instead.",__A,)
                _lowerCamelCase					: Tuple		    = kwargs.pop("feature_extractor"  )

          _lowerCamelCase					: Any		    = image_processor if image_processor is not None else feature_extractor
          if image_processor is None:
                raise ValueError("You need to specify an `image_processor`."  )
          if tokenizer is None:
                raise ValueError("You need to specify a `tokenizer`."  )

          super().__init__(__A,__A  )
          _lowerCamelCase					: Tuple		    = self.image_processor



    def __call__(						self   :							Optional[int],__A   :							int,__A   :							Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None,__A   :							bool = True,__A   :							Union[bool, str, PaddingStrategy] = False,__A   :							Union[bool, str, TruncationStrategy] = None,__A   :							Optional[int] = None,__A   :							int = 0,__A   :							Optional[int] = None,__A   :							Optional[bool] = None,__A   :							Optional[bool] = None,__A   :							bool = False,__A   :							bool = False,__A   :							bool = False,__A   :							bool = False,__A   :							bool = True,__A   :							Optional[Union[str, TensorType]] = None,**__A   :							Union[str, Any],):
          _lowerCamelCase					: Optional[int]		    = self.tokenizer(
              text=__A,add_special_tokens=__A,padding=__A,truncation=__A,max_length=__A,stride=__A,pad_to_multiple_of=__A,return_token_type_ids=__A,return_attention_mask=__A,return_overflowing_tokens=__A,return_special_tokens_mask=__A,return_offsets_mapping=__A,return_length=__A,verbose=__A,return_tensors=__A,**__A,)
          # add pixel_values + pixel_mask
          _lowerCamelCase					: Dict		    = self.image_processor(__A,return_tensors=__A  )
          encoding.update(__A  )

          return encoding



    def 	lowerCamelCase_	(						self   :							List[Any],*__A   :							List[str],**__A   :							List[str]  ):
          return self.tokenizer.batch_decode(*__A,**__A  )



    def 	lowerCamelCase_	(						self   :							Optional[int],*__A   :							Union[str, Any],**__A   :							str  ):
          return self.tokenizer.decode(*__A,**__A  )



    @property
    def 	lowerCamelCase_	(						self   :							Optional[Any]  ):
          _lowerCamelCase					: Tuple		    = self.tokenizer.model_input_names
          _lowerCamelCase					: str		    = self.image_processor.model_input_names
          return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names  )  )



    @property
    def 	lowerCamelCase_	(						self   :							Dict  ):
          warnings.warn(
              "`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.",__A,)
          return self.image_processor_class



    @property
    def 	lowerCamelCase_	(						self   :							str  ):
          warnings.warn(
              "`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.",__A,)
          return self.image_processor





'''simple docstring'''





from typing import Optional
from urllib.parse import quote

import huggingface_hub as hfh
from packaging import version





def       __a      (  _UpperCamelCase:       str   ,		_UpperCamelCase:       str   ,		_UpperCamelCase:       Optional[str] = None       )		->					str:

     """simple docstring"""




     if version.parse(hfh.__version__       ).release < version.parse("0.11.0"       ).release:
          # old versions of hfh don't url-encode the file path
          _snake_case				= quote(_UpperCamelCase       )
     return hfh.hf_hub_url(_UpperCamelCase   ,		_UpperCamelCase   ,		repo_type="dataset"   ,		revision=_UpperCamelCase       )


