



from __future__ import annotations

UpperCamelCase_	       =   [2, 1, 4, 5, 6, 0, 8, 9, 1, 2, 0, 6, 4, 2, 0, 6, 5, 3, 2, 7]







class 							a_  :

						def __init__(    self	:List[str]   ,						_lowercase	:int)		->					None:
												UpperCAmelCase_     							=     -1
												UpperCAmelCase_     							=     -1
												UpperCAmelCase_     							=     [-1] * length
												UpperCAmelCase_     							=     None
												UpperCAmelCase_     							=     None




						def __repr__(    self	:Any)		->					str:
												return f"Node(min_value={self.minn} max_value={self.maxx})"







def 				A			(		__UpperCAmelCase	)       ->       Node | None:



						'''simple docstring'''






						UpperCAmelCase_     							=     Node(len(__UpperCAmelCase	)	)
						UpperCAmelCase_							,      UpperCAmelCase_     							=     min(__UpperCAmelCase	), max(__UpperCAmelCase	)
						# Leaf node case where the node contains only one unique value
						if root.minn == root.maxx:
												return root
						UpperCAmelCase_     							=     (root.minn + root.maxx) // 2

						UpperCAmelCase_     							=     []
						UpperCAmelCase_     							=     []

						for index, num in enumerate(__UpperCAmelCase	):
												if num <= pivot:
																		left_arr.append(__UpperCAmelCase	)
												else:
																		right_arr.append(__UpperCAmelCase	)
												UpperCAmelCase_     							=     len(__UpperCAmelCase	)
						UpperCAmelCase_     							=     build_tree(__UpperCAmelCase	)
						UpperCAmelCase_     							=     build_tree(__UpperCAmelCase	)
						return root







def 				A			(		__UpperCAmelCase							,					__UpperCAmelCase							,					__UpperCAmelCase	)       ->       int:



						'''simple docstring'''






						if index < 0 or node is None:
												return 0
						# Leaf node cases
						if node.minn == node.maxx:
												return index + 1 if node.minn == num else 0
						UpperCAmelCase_     							=     (node.minn + node.maxx) // 2
						if num <= pivot:
												# go the left subtree and map index to the left subtree
												return rank_till_index(node.left							,					__UpperCAmelCase							,					node.map_left[index] - 1	)
						else:
												# go to the right subtree and map index to the right subtree
												return rank_till_index(node.right							,					__UpperCAmelCase							,					index - node.map_left[index]	)







def 				A			(		__UpperCAmelCase							,					__UpperCAmelCase							,					__UpperCAmelCase							,					__UpperCAmelCase	)       ->       int:



						'''simple docstring'''






						if start > end:
												return 0
						UpperCAmelCase_     							=     rank_till_index(__UpperCAmelCase							,					__UpperCAmelCase							,					__UpperCAmelCase	)
						UpperCAmelCase_     							=     rank_till_index(__UpperCAmelCase							,					__UpperCAmelCase							,					start - 1	)
						return rank_till_end - rank_before_start







def 				A			(		__UpperCAmelCase							,					__UpperCAmelCase							,					__UpperCAmelCase							,					__UpperCAmelCase	)       ->       int:



						'''simple docstring'''






						if index > (end - start) or start > end or node is None:
												return -1
						# Leaf node case
						if node.minn == node.maxx:
												return node.minn
						# Number of elements in the left subtree in interval [start, end]
						UpperCAmelCase_     							=     node.map_left[end] - (
						    node.map_left[start - 1] if start else 0
						)
						if num_elements_in_left_tree > index:
												return quantile(
												    node.left							,					__UpperCAmelCase							,					(node.map_left[start - 1] if start else 0)							,					node.map_left[end] - 1							,					)
						else:
												return quantile(
												    node.right							,					index - num_elements_in_left_tree							,					start - (node.map_left[start - 1] if start else 0)							,					end - node.map_left[end]							,					)







def 				A			(		__UpperCAmelCase							,					__UpperCAmelCase							,					__UpperCAmelCase							,					__UpperCAmelCase							,					__UpperCAmelCase	)       ->       int:



						'''simple docstring'''






						if (
						    start > end
						    or node is None
						    or start_num > end_num
						    or node.minn > end_num
						    or node.maxx < start_num
						):
												return 0
						if start_num <= node.minn and node.maxx <= end_num:
												return end - start + 1
						UpperCAmelCase_     							=     range_counting(
						    node.left							,					(node.map_left[start - 1] if start else 0)							,					node.map_left[end] - 1							,					__UpperCAmelCase							,					__UpperCAmelCase							,					)
						UpperCAmelCase_     							=     range_counting(
						    node.right							,					start - (node.map_left[start - 1] if start else 0)							,					end - node.map_left[end]							,					__UpperCAmelCase							,					__UpperCAmelCase							,					)
						return left + right


if __name__ == "__main__":
							import doctest

							doctest.testmod()










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


UpperCamelCase_	       =   {"configuration_vit_hybrid": ["VIT_HYBRID_PRETRAINED_CONFIG_ARCHIVE_MAP", "ViTHybridConfig"]}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase_	       =   [
							    "VIT_HYBRID_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "ViTHybridForImageClassification",
							    "ViTHybridModel",
							    "ViTHybridPreTrainedModel",
							]

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase_	       =   ["ViTHybridImageProcessor"]


if TYPE_CHECKING:
							from .configuration_vit_hybrid import VIT_HYBRID_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTHybridConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_vit_hybrid import (
														    VIT_HYBRID_PRETRAINED_MODEL_ARCHIVE_LIST,
														    ViTHybridForImageClassification,
														    ViTHybridModel,
														    ViTHybridPreTrainedModel,
														)

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .image_processing_vit_hybrid import ViTHybridImageProcessor


else:
							import sys

							UpperCamelCase_	       =   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





