





import warnings
from contextlib import contextmanager

from ...processing_utils import ProcessorMixin

class   __snake_case				(			lowerCamelCase__   ):






    '''simple docstring'''
    _lowerCAmelCase     =	["""image_processor""", """tokenizer"""]
    _lowerCAmelCase     =	"""AutoImageProcessor"""
    _lowerCAmelCase     =	"""AutoTokenizer"""





    def __init__(   self						:		List[Any]			,						snake_case						:		List[Any]=None			,						snake_case						:		str=None			,						**snake_case						:		Union[str, Any]							):

      """simple docstring"""





      __lowerCAmelCase			=				None
      if "feature_extractor" in kwargs:
        warnings.warn(
            '''The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'''
            ''' instead.'''			,						SCREAMING_SNAKE_CASE_			,						)
        __lowerCAmelCase			=				kwargs.pop('''feature_extractor'''							)

      __lowerCAmelCase			=				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__(SCREAMING_SNAKE_CASE_			,						SCREAMING_SNAKE_CASE_							)
      __lowerCAmelCase			=				self.image_processor
      __lowerCAmelCase			=				False





    def __call__(   self						:		Any			,						*snake_case						:		Union[str, Any]			,						**snake_case						:		Union[str, Any]							):

      """simple docstring"""





      if self._in_target_context_manager:
        return self.current_processor(*SCREAMING_SNAKE_CASE_			,						**SCREAMING_SNAKE_CASE_							)

      __lowerCAmelCase			=				kwargs.pop('''images'''			,						SCREAMING_SNAKE_CASE_							)
      __lowerCAmelCase			=				kwargs.pop('''text'''			,						SCREAMING_SNAKE_CASE_							)
      if len(SCREAMING_SNAKE_CASE_							) > 0:
        __lowerCAmelCase			=				args[0]
        __lowerCAmelCase			=				args[1:]

      if images is None and text is None:
        raise ValueError('''You need to specify either an `images` or `text` input to process.'''							)

      if images is not None:
        __lowerCAmelCase			=				self.image_processor(SCREAMING_SNAKE_CASE_			,						*SCREAMING_SNAKE_CASE_			,						**SCREAMING_SNAKE_CASE_							)
      if text is not None:
        __lowerCAmelCase			=				self.tokenizer(SCREAMING_SNAKE_CASE_			,						**SCREAMING_SNAKE_CASE_							)

      if text is None:
        return inputs
      elif images is None:
        return encodings
      else:
        __lowerCAmelCase			=				encodings['''input_ids''']
        return inputs





    def 	A		(   self						:		str			,						*snake_case						:		List[str]			,						**snake_case						:		Union[str, Any]							):

      """simple docstring"""





      return self.tokenizer.batch_decode(*SCREAMING_SNAKE_CASE_			,						**SCREAMING_SNAKE_CASE_							)





    def 	A		(   self						:		Optional[int]			,						*snake_case						:		Optional[Any]			,						**snake_case						:		Optional[Any]							):

      """simple docstring"""





      return self.tokenizer.decode(*SCREAMING_SNAKE_CASE_			,						**SCREAMING_SNAKE_CASE_							)





    @contextmanager
    def 	A		(   self						:		Optional[int]							):

      """simple docstring"""





      warnings.warn(
          '''`as_target_processor` is deprecated and will be removed in v5 of Transformers. You can process your '''
          '''labels by using the argument `text` of the regular `__call__` method (either in the same call as '''
          '''your images inputs, or in a separate call.'''							)
      __lowerCAmelCase			=				True
      __lowerCAmelCase			=				self.tokenizer
      yield
      __lowerCAmelCase			=				self.image_processor
      __lowerCAmelCase			=				False





    @property
    def 	A		(   self						:		Any							):

      """simple docstring"""





      warnings.warn(
          '''`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'''			,						SCREAMING_SNAKE_CASE_			,						)
      return self.image_processor_class





    @property
    def 	A		(   self						:		Union[str, Any]							):

      """simple docstring"""





      warnings.warn(
          '''`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'''			,						SCREAMING_SNAKE_CASE_			,						)
      return self.image_processor







class   __snake_case				:






    '''simple docstring'''





    def __init__(   self						:		Any							):

      """simple docstring"""





      __lowerCAmelCase			=				{}
      # indexmap keys are an index and it's values are the number at that index
      __lowerCAmelCase			=				{}





    def 	A		(   self						:		List[Any]			,						snake_case						:		list | str | range			,						snake_case						:		int							):

      """simple docstring"""





      if isinstance(snake_case			,						(range, str)							):
        __lowerCAmelCase			=				list(snake_case							)
      elif not isinstance(snake_case			,						snake_case							):
        raise TypeError(
            '''binary_search_delete() only accepts either a list, range or str'''							)

      __lowerCAmelCase			=				0
      __lowerCAmelCase			=				len(snake_case							) - 1

      while low <= high:
        __lowerCAmelCase			=				(low + high) // 2
        if array[mid] == item:
          array.pop(snake_case							)
          return array
        elif array[mid] < item:
          __lowerCAmelCase			=				mid + 1
        else:
          __lowerCAmelCase			=				mid - 1
      raise ValueError(
          '''Either the item is not in the array or the array was unsorted'''							)





    def 	A		(   self						:		Tuple			,						snake_case						:		list | str | range			,						snake_case						:		int							):

      """simple docstring"""





      if isinstance(snake_case			,						(range, str)							):
        __lowerCAmelCase			=				list(snake_case							)
      elif not isinstance(snake_case			,						snake_case							):
        raise TypeError(
            '''binary_search_insert() only accepts either a list, range or str'''							)

      __lowerCAmelCase			=				0
      __lowerCAmelCase			=				len(snake_case							) - 1

      while low <= high:
        __lowerCAmelCase			=				(low + high) // 2
        if array[mid] == index:
          # If the item already exists in the array,
          # insert it after the existing item
          array.insert(mid + 1			,						snake_case							)
          return array
        elif array[mid] < index:
          __lowerCAmelCase			=				mid + 1
        else:
          __lowerCAmelCase			=				mid - 1

        # If the item doesn't exist in the array, insert it at the appropriate position
      array.insert(snake_case			,						snake_case							)
      return array





    def 	A		(   self						:		Tuple			,						snake_case						:		int			,						snake_case						:		int							):

      """simple docstring"""





      if index in self.indexmap:
        __lowerCAmelCase			=				self.indexmap[index]
        if len(self.numbermap[n]							) == 1:
          del self.numbermap[n]
        else:
          __lowerCAmelCase			=				self.binary_search_delete(self.numbermap[n]			,						snake_case							)

        # Set new index
      __lowerCAmelCase			=				number

      # Number not seen before or empty so insert number value
      if number not in self.numbermap:
        __lowerCAmelCase			=				[index]

      # Here we need to perform a binary search insertion in order to insert
      # The item in the correct place
      else:
        __lowerCAmelCase			=				self.binary_search_insert(
            self.numbermap[number]			,						snake_case							)





    def 	A		(   self						:		List[str]			,						snake_case						:		int							):

      """simple docstring"""





      return self.numbermap.get(snake_case			,						[-1]							)[0]


if __name__ == "__main__":
      import doctest

      doctest.testmod()
