


import os
from typing import List, Optional, Union

from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
from ..auto import AutoTokenizer



class 				A       (			UpperCAmelCase__				):
					'''simple docstring'''






					A__     =					['''image_processor''', '''tokenizer''']
					A__     =					'''BlipImageProcessor'''
					A__     =					'''AutoTokenizer'''

					def __init__(self       :		List[Any] ,   _UpperCAmelCase       :		str ,   _UpperCAmelCase       :		str ,   _UpperCAmelCase       :		Any						)		->  Any:




							"""simple docstring"""


							super().__init__(_UpperCAmelCase ,   _UpperCAmelCase						)

							# add QFormer tokenizer
							lowercase__	     =						qformer_tokenizer

					def __call__(self       :		Optional[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       :		Dict ,   )		->  BatchFeature:




							"""simple docstring"""


							if images is None and text is None:
									raise ValueError("""You have to specify at least images or text."""						)

							lowercase__	     =						BatchFeature()

							if text is not None:
									lowercase__	     =						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 ,   )
									encoding.update(_UpperCAmelCase						)
									lowercase__	     =						self.qformer_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 ,   )
									lowercase__	     =						qformer_text_encoding.pop("""input_ids"""						)
									lowercase__	     =						qformer_text_encoding.pop("""attention_mask"""						)

							if images is not None:
									lowercase__	     =						self.image_processor(_UpperCAmelCase ,   return_tensors=_UpperCAmelCase						)
									encoding.update(_UpperCAmelCase						)

							return encoding

					def     lowerCamelCase__	(self       :		Tuple ,   *_UpperCAmelCase       :		Any ,   **_UpperCAmelCase       :		List[Any]						)		->  Optional[int]:




							"""simple docstring"""


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

					def     lowerCamelCase__	(self       :		str ,   *_UpperCAmelCase       :		Optional[int] ,   **_UpperCAmelCase       :		Union[str, Any]						)		->  int:




							"""simple docstring"""


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

					@property
					# Copied from transformers.models.blip.processing_blip.BlipProcessor.model_input_names
					def     lowerCamelCase__	(self       :		List[str]						)		->  Dict:




							"""simple docstring"""


							lowercase__	     =						self.tokenizer.model_input_names
							lowercase__	     =						self.image_processor.model_input_names
							return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names						)						)

					def     lowerCamelCase__	(self       :		Optional[int] ,   _UpperCAmelCase       :		int ,   **_UpperCAmelCase       :		Optional[int]						)		->  int:




							"""simple docstring"""


							if os.path.isfile(_UpperCAmelCase						):
									raise ValueError(f'''Provided path ({save_directory}) should be a directory, not a file'''						)
							os.makedirs(_UpperCAmelCase ,   exist_ok=_UpperCAmelCase						)
							lowercase__	     =						os.path.join(_UpperCAmelCase ,   """qformer_tokenizer"""						)
							self.qformer_tokenizer.save_pretrained(_UpperCAmelCase						)
							return super().save_pretrained(_UpperCAmelCase ,   **_UpperCAmelCase						)


					@classmethod
					def     lowerCamelCase__	(cls       :		Tuple ,   _UpperCAmelCase       :		int ,   **_UpperCAmelCase       :		Optional[int]						)		->  List[Any]:




							"""simple docstring"""


							lowercase__	     =						AutoTokenizer.from_pretrained(_UpperCAmelCase ,   subfolder="""qformer_tokenizer"""						)
							lowercase__	     =						cls._get_arguments_from_pretrained(_UpperCAmelCase ,   **_UpperCAmelCase						)
							args.append(_UpperCAmelCase						)
							return cls(*_UpperCAmelCase						)






from collections.abc import Sequence
from queue import Queue






class     __a			:



	def __init__(    self				:     str					,						snake_case_				:     List[str]					,						snake_case_				:     Tuple					,						snake_case_				:     Tuple					,						snake_case_				:     Optional[Any]=None					,						snake_case_				:     Dict=None)->				Optional[int]:
						__lowerCAmelCase						 =start
						__lowerCAmelCase						 =end
						__lowerCAmelCase						 =val
						__lowerCAmelCase						 =(start + end) // 2
						__lowerCAmelCase						 =left
						__lowerCAmelCase						 =right



	def __repr__(    self				:     List[Any])->				Dict:
						return F"""SegmentTreeNode(start={self.start}, end={self.end}, val={self.val})"""






class     __a			:



	def __init__(    self				:     List[str]					,						snake_case_				:     Sequence					,						snake_case_				:     int)->				str:
						__lowerCAmelCase						 =collection
						__lowerCAmelCase						 =function
						if self.collection:
											__lowerCAmelCase						 =self._build_tree(0					,						len(snake_case_) - 1)



	def 		UpperCamelCase				(    self				:     Dict					,						snake_case_				:     Tuple					,						snake_case_				:     Optional[int])->				Optional[int]:
						self._update_tree(self.root					,						snake_case_					,						snake_case_)



	def 		UpperCamelCase				(    self				:     Optional[Any]					,						snake_case_				:     Any					,						snake_case_				:     Union[str, Any])->				Union[str, Any]:
						return self._query_range(self.root					,						snake_case_					,						snake_case_)



	def 		UpperCamelCase				(    self				:     List[str]					,						snake_case_				:     List[str]					,						snake_case_				:     List[str])->				List[Any]:
						if start == end:
											return SegmentTreeNode(snake_case_					,						snake_case_					,						self.collection[start])
						__lowerCAmelCase						 =(start + end) // 2
						__lowerCAmelCase						 =self._build_tree(snake_case_					,						snake_case_)
						__lowerCAmelCase						 =self._build_tree(mid + 1					,						snake_case_)
						return SegmentTreeNode(snake_case_					,						snake_case_					,						self.fn(left.val					,						right.val)					,						snake_case_					,						snake_case_)



	def 		UpperCamelCase				(    self				:     Dict					,						snake_case_				:     Tuple					,						snake_case_				:     int					,						snake_case_				:     int)->				List[Any]:
						if node.start == i and node.end == i:
											__lowerCAmelCase						 =val
											return
						if i <= node.mid:
											self._update_tree(node.left					,						snake_case_					,						snake_case_)
						else:
											self._update_tree(node.right					,						snake_case_					,						snake_case_)
						__lowerCAmelCase						 =self.fn(node.left.val					,						node.right.val)



	def 		UpperCamelCase				(    self				:     Tuple					,						snake_case_				:     str					,						snake_case_				:     str					,						snake_case_				:     List[Any])->				Optional[int]:
						if node.start == i and node.end == j:
											return node.val

						if i <= node.mid:
											if j <= node.mid:
																# range in left child tree
																return self._query_range(node.left					,						snake_case_					,						snake_case_)
											else:
																# range in left child tree and right child tree
																return self.fn(
																    self._query_range(node.left					,						snake_case_					,						node.mid)					,						self._query_range(node.right					,						node.mid + 1					,						snake_case_)					,						)
						else:
											# range in right child tree
											return self._query_range(node.right					,						snake_case_					,						snake_case_)



	def 		UpperCamelCase				(    self				:     List[str])->				Tuple:
						if self.root is not None:
											__lowerCAmelCase						 =Queue()
											queue.put(self.root)
											while not queue.empty():
																__lowerCAmelCase						 =queue.get()
																yield node

																if node.left is not None:
																					queue.put(node.left)

																if node.right is not None:
																					queue.put(node.right)


if __name__ == "__main__":
				import operator

				for fn in [operator.add, max, min]:
								print('''*''' * 50)
								lowercase_													=      SegmentTree([2, 1, 5, 3, 4], fn)
								for node in arr.traverse():
												print(node)
								print()

								arr.update(1, 5)
								for node in arr.traverse():
												print(node)
								print()

								print(arr.query_range(3, 4))  # 7
								print(arr.query_range(2, 2))  # 5
								print(arr.query_range(1, 3))  # 13
								print()




