

"""simple docstring"""




from __future__ import annotations

import math







class   __lowercase      :

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






   '''simple docstring'''
   UpperCAmelCase__       :	str        =       size
   # approximate the overall size of segment tree with given value
   UpperCAmelCase__       :	Any        =       [0 for i in range(0       ,4 * size     )]
   # create array to store lazy update
   UpperCAmelCase__       :	Dict        =       [0 for i in range(0       ,4 * size     )]
   UpperCAmelCase__       :	List[Any]        =       [0 for i in range(0       ,4 * size     )]  # flag for lazy update

  def  __lowercase							(	self		:      int       ,A		:      int     ):






   '''simple docstring'''
   return idx * 2

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






   '''simple docstring'''
   return idx * 2 + 1

  def  __lowercase							(	self		:      Union[str, Any]       ,A		:      int       ,A		:      int       ,A		:      int       ,A		:      list[int]     ):






   '''simple docstring'''
   if left_element == right_element:
    UpperCAmelCase__       :	Optional[int]        =       a[left_element - 1]
   else:
    UpperCAmelCase__       :	Dict        =       (left_element + right_element) // 2
    self.build(self.left(A     )       ,A       ,A       ,A     )
    self.build(self.right(A     )       ,mid + 1       ,A       ,A     )
    UpperCAmelCase__       :	Union[str, Any]        =       max(
        self.segment_tree[self.left(A     )]       ,self.segment_tree[self.right(A     )]     )

  def  __lowercase							(	self		:      Optional[int]       ,A		:      int       ,A		:      int       ,A		:      int       ,A		:      int       ,A		:      int       ,A		:      int     ):






   '''simple docstring'''
   if self.flag[idx] is True:
    UpperCAmelCase__       :	Dict        =       self.lazy[idx]
    UpperCAmelCase__       :	int        =       False
    if left_element != right_element:
     UpperCAmelCase__       :	List[str]        =       self.lazy[idx]
     UpperCAmelCase__       :	List[Any]        =       self.lazy[idx]
     UpperCAmelCase__       :	List[Any]        =       True
     UpperCAmelCase__       :	Any        =       True

   if right_element < a or left_element > b:
    return True
   if left_element >= a and right_element <= b:
    UpperCAmelCase__       :	Any        =       val
    if left_element != right_element:
     UpperCAmelCase__       :	str        =       val
     UpperCAmelCase__       :	List[str]        =       val
     UpperCAmelCase__       :	Tuple        =       True
     UpperCAmelCase__       :	Optional[int]        =       True
    return True
   UpperCAmelCase__       :	Optional[int]        =       (left_element + right_element) // 2
   self.update(self.left(A     )       ,A       ,A       ,A       ,A       ,A     )
   self.update(self.right(A     )       ,mid + 1       ,A       ,A       ,A       ,A     )
   UpperCAmelCase__       :	List[str]        =       max(
       self.segment_tree[self.left(A     )]       ,self.segment_tree[self.right(A     )]     )
   return True

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






   '''simple docstring'''
   if self.flag[idx] is True:
    UpperCAmelCase__       :	Any        =       self.lazy[idx]
    UpperCAmelCase__       :	Optional[int]        =       False
    if left_element != right_element:
     UpperCAmelCase__       :	List[Any]        =       self.lazy[idx]
     UpperCAmelCase__       :	Union[str, Any]        =       self.lazy[idx]
     UpperCAmelCase__       :	Optional[int]        =       True
     UpperCAmelCase__       :	Optional[int]        =       True
   if right_element < a or left_element > b:
    return -math.inf
   if left_element >= a and right_element <= b:
    return self.segment_tree[idx]
   UpperCAmelCase__       :	Dict        =       (left_element + right_element) // 2
   UpperCAmelCase__       :	Tuple        =       self.query(self.left(A     )       ,A       ,A       ,A       ,A     )
   UpperCAmelCase__       :	Any        =       self.query(self.right(A     )       ,mid + 1       ,A       ,A       ,A     )
   return max(A       ,A     )




  def __str__(	self		:      str     ):






   '''simple docstring'''
   return str([self.query(1       ,1       ,self.size       ,A       ,A     ) for i in range(1       ,self.size + 1     )]     )


if __name__ == "__main__":
      __UpperCAmelCase			=					[1, 2, -4, 7, 3, -5, 6, 11, -20, 9, 14, 15, 5, 2, -8]
      __UpperCAmelCase			=					15
      __UpperCAmelCase			=					SegmentTree(size)
      segt.build(1, 1, size, A)
      print(segt.query(1, 1, size, 4, 6))
      print(segt.query(1, 1, size, 7, 11))
      print(segt.query(1, 1, size, 7, 12))
      segt.update(1, 1, size, 1, 3, 111)
      print(segt.query(1, 1, size, 1, 15))
      segt.update(1, 1, size, 7, 8, 235)
      print(segt)











"""simple docstring"""

import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding





class 							lowercase_			(	__lowerCAmelCase				):



 '''simple docstring'''
 UpperCAmelCase       :	Any     =      ['''image_processor''', '''tokenizer''']
 UpperCAmelCase       :	Optional[int]     =      '''ViTImageProcessor'''
 UpperCAmelCase       :	int     =      ('''CLIPTokenizer''', '''CLIPTokenizerFast''')

 def __init__(					self			:			Tuple       ,				_UpperCAmelCase			:			int=None       ,				_UpperCAmelCase			:			Tuple=None       ,				**_UpperCAmelCase			:			Dict						):
       _A     =  None
       if "feature_extractor" in kwargs:
             warnings.warn(
                 'The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'
                 ' instead.'       ,				_UpperCAmelCase       ,				)
             _A     =  kwargs.pop('feature_extractor'						)

       _A     =  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__(_UpperCAmelCase       ,				_UpperCAmelCase						)

 def __call__(					self			:			Optional[Any]       ,				_UpperCAmelCase			:			int=None       ,				_UpperCAmelCase			:			int=None       ,				_UpperCAmelCase			:			Optional[Any]=None       ,				_UpperCAmelCase			:			Optional[int]=None       ,				**_UpperCAmelCase			:			Union[str, Any]						):
       if text is None and visual_prompt is None and images is None:
             raise ValueError('You have to specify either text, visual prompt or images.'						)

       if text is not None and visual_prompt is not None:
             raise ValueError('You have to specify exactly one type of prompt. Either text or visual prompt.'						)

       if text is not None:
             _A     =  self.tokenizer(_UpperCAmelCase       ,				return_tensors=_UpperCAmelCase       ,				**_UpperCAmelCase						)

       if visual_prompt is not None:
             _A     =  self.image_processor(_UpperCAmelCase       ,				return_tensors=_UpperCAmelCase       ,				**_UpperCAmelCase						)

       if images is not None:
             _A     =  self.image_processor(_UpperCAmelCase       ,				return_tensors=_UpperCAmelCase       ,				**_UpperCAmelCase						)

       if visual_prompt is not None and images is not None:
             _A     =  {
                 'pixel_values': image_features.pixel_values,
                 'conditional_pixel_values': prompt_features.pixel_values,
             }
             return encoding
       elif text is not None and images is not None:
             _A     =  image_features.pixel_values
             return encoding
       elif text is not None:
             return encoding
       elif visual_prompt is not None:
             _A     =  {
                 'conditional_pixel_values': prompt_features.pixel_values,
             }
             return encoding
       else:
             return BatchEncoding(data=dict(**_UpperCAmelCase						)       ,				tensor_type=_UpperCAmelCase						)

 def      lowerCAmelCase_				(					self			:			str       ,				*_UpperCAmelCase			:			List[Any]       ,				**_UpperCAmelCase			:			Union[str, Any]						):
       return self.tokenizer.batch_decode(*_UpperCAmelCase       ,				**_UpperCAmelCase						)

 def      lowerCAmelCase_				(					self			:			Union[str, Any]       ,				*_UpperCAmelCase			:			List[str]       ,				**_UpperCAmelCase			:			Union[str, Any]						):
       return self.tokenizer.decode(*_UpperCAmelCase       ,				**_UpperCAmelCase						)

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



 @property
 def      lowerCAmelCase_				(					self			:			Tuple						):
       warnings.warn(
           '`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'       ,				_UpperCAmelCase       ,				)
       return self.image_processor

