
class       __A:

					def __init__(	self					:     Dict   ,					__UpperCamelCase					:     int   ):
												lowerCamelCase_							  =					size
												lowerCamelCase_							  =					[0] * size
												lowerCamelCase_							  =					[0] * size

					@staticmethod
					def    lowercase__      (	__UpperCamelCase					:     int   ):
												return index | (index + 1)

					@staticmethod
					def    lowercase__      (	__UpperCamelCase					:     int   ):
												return (index & (index + 1)) - 1

					def    lowercase__      (	self					:     Dict   ,					__UpperCamelCase					:     int   ,					__UpperCamelCase					:     int   ):
												lowerCamelCase_							  =					value
												while index < self.size:
																			lowerCamelCase_							  =					self.get_prev(__UpperCamelCase   ) + 1
																			if current_left_border == index:
																										lowerCamelCase_							  =					value
																			else:
																										lowerCamelCase_							  =					max(__UpperCamelCase   ,					__UpperCamelCase   ,					__UpperCamelCase   )
																			lowerCamelCase_							  =					self.get_next(__UpperCamelCase   )



					def    lowercase__      (	self					:     str   ,					__UpperCamelCase					:     int   ,					__UpperCamelCase					:     int   ):
												right -= 1  # Because of right is exclusive
												lowerCamelCase_							  =					0
												while left <= right:
																			lowerCamelCase_							  =					self.get_prev(__UpperCamelCase   )
																			if left <= current_left:
																										lowerCamelCase_							  =					max(__UpperCamelCase   ,					self.tree[right]   )
																										lowerCamelCase_							  =					current_left
																			else:
																										lowerCamelCase_							  =					max(__UpperCamelCase   ,					self.arr[right]   )
																										right -= 1
												return result


if __name__ == "__main__":
		import doctest

		doctest.testmod()







from typing import List, Optional, Union

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





class       __A(				UpperCAmelCase       ):
					SCREAMING_SNAKE_CASE			    =    ['''image_processor''', '''tokenizer''']
					SCREAMING_SNAKE_CASE			    =    '''BlipImageProcessor'''
					SCREAMING_SNAKE_CASE			    =    '''AutoTokenizer'''

					def __init__(	self					:     Union[str, Any]   ,					__UpperCamelCase					:     List[Any]   ,					__UpperCamelCase					:     List[str]   ):
												lowerCamelCase_							  =					False
												super().__init__(__UpperCamelCase   ,					__UpperCamelCase   )
												lowerCamelCase_							  =					self.image_processor

					def __call__(	self					:     Any   ,					__UpperCamelCase					:     ImageInput = None   ,					__UpperCamelCase					:     Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None   ,					__UpperCamelCase					:     bool = True   ,					__UpperCamelCase					:     Union[bool, str, PaddingStrategy] = False   ,					__UpperCamelCase					:     Union[bool, str, TruncationStrategy] = None   ,					__UpperCamelCase					:     Optional[int] = None   ,					__UpperCamelCase					:     int = 0   ,					__UpperCamelCase					:     Optional[int] = None   ,					__UpperCamelCase					:     Optional[bool] = None   ,					__UpperCamelCase					:     bool = False   ,					__UpperCamelCase					:     bool = False   ,					__UpperCamelCase					:     bool = False   ,					__UpperCamelCase					:     bool = False   ,					__UpperCamelCase					:     bool = False   ,					__UpperCamelCase					:     bool = True   ,					__UpperCamelCase					:     Optional[Union[str, TensorType]] = None   ,					**__UpperCamelCase					:     Optional[Any]   ,					):
												if images is None and text is None:
																			raise ValueError("""You have to specify either images or text."""   )

												# Get only text
												if images is None:
																			lowerCamelCase_							  =					self.tokenizer
																			lowerCamelCase_							  =					self.tokenizer(
																			    text=__UpperCamelCase   ,					add_special_tokens=__UpperCamelCase   ,					padding=__UpperCamelCase   ,					truncation=__UpperCamelCase   ,					max_length=__UpperCamelCase   ,					stride=__UpperCamelCase   ,					pad_to_multiple_of=__UpperCamelCase   ,					return_attention_mask=__UpperCamelCase   ,					return_overflowing_tokens=__UpperCamelCase   ,					return_special_tokens_mask=__UpperCamelCase   ,					return_offsets_mapping=__UpperCamelCase   ,					return_token_type_ids=__UpperCamelCase   ,					return_length=__UpperCamelCase   ,					verbose=__UpperCamelCase   ,					return_tensors=__UpperCamelCase   ,					**__UpperCamelCase   ,					)
																			return text_encoding

												# add pixel_values
												lowerCamelCase_							  =					self.image_processor(__UpperCamelCase   ,					return_tensors=__UpperCamelCase   )

												if text is not None:
																			lowerCamelCase_							  =					self.tokenizer(
																			    text=__UpperCamelCase   ,					add_special_tokens=__UpperCamelCase   ,					padding=__UpperCamelCase   ,					truncation=__UpperCamelCase   ,					max_length=__UpperCamelCase   ,					stride=__UpperCamelCase   ,					pad_to_multiple_of=__UpperCamelCase   ,					return_attention_mask=__UpperCamelCase   ,					return_overflowing_tokens=__UpperCamelCase   ,					return_special_tokens_mask=__UpperCamelCase   ,					return_offsets_mapping=__UpperCamelCase   ,					return_token_type_ids=__UpperCamelCase   ,					return_length=__UpperCamelCase   ,					verbose=__UpperCamelCase   ,					return_tensors=__UpperCamelCase   ,					**__UpperCamelCase   ,					)
												else:
																			lowerCamelCase_							  =					None

												if text_encoding is not None:
																			encoding_image_processor.update(__UpperCamelCase   )

												return encoding_image_processor

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

					def    lowercase__      (	self					:     List[str]   ,					*__UpperCamelCase					:     List[Any]   ,					**__UpperCamelCase					:     int   ):
												return self.tokenizer.decode(*__UpperCamelCase   ,					**__UpperCamelCase   )



					@property
					# Copied from transformers.models.blip.processing_blip.BlipProcessor.model_input_names
					def    lowercase__      (	self					:     Optional[int]   ):
												lowerCamelCase_							  =					self.tokenizer.model_input_names
												lowerCamelCase_							  =					self.image_processor.model_input_names
												return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names   )   )





