
'''simple docstring'''


from __future__ import annotations

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




class     __snake_case			:




		def __init__(  self					:Optional[Any]			,    _SCREAMING_SNAKE_CASE					:int)					->			None:






								'''simple docstring'''






								UpperCamelCase_     :	int					     =     -1
								UpperCamelCase_     :	int					     =     -1
								UpperCamelCase_     :	list[int]					     =     [-1] * length
								UpperCamelCase_     :	Node | None					     =     None
								UpperCamelCase_     :	Node | None					     =     None





		def __repr__(  self					:str)					->			str:






								'''simple docstring'''






								return F"""Node(min_value={self.minn} max_value={self.maxx})"""







def 					__magic_name__(       UpperCAmelCase__ :       list[int]	):
						UpperCamelCase_     :	List[Any]					     =     Node(len(UpperCAmelCase__	)	)
						UpperCamelCase_     ,UpperCamelCase_     :	Union[str, Any]					     =     min(UpperCAmelCase__	), max(UpperCAmelCase__	)
						# Leaf node case where the node contains only one unique value
						if root.minn == root.maxx:
												return root
						UpperCamelCase_     :	Optional[int]					     =     (root.minn + root.maxx) // 2

						UpperCamelCase_     :	list[int]					     =     []
						UpperCamelCase_     :	list[int]					     =     []

						for index, num in enumerate(UpperCAmelCase__	):
												if num <= pivot:
																		left_arr.append(UpperCAmelCase__	)
												else:
																		right_arr.append(UpperCAmelCase__	)
												UpperCamelCase_     :	Tuple					     =     len(UpperCAmelCase__	)
						UpperCamelCase_     :	List[Any]					     =     build_tree(UpperCAmelCase__	)
						UpperCamelCase_     :	Optional[Any]					     =     build_tree(UpperCAmelCase__	)
						return root
def 					__magic_name__(       UpperCAmelCase__ :       Node | None							,				UpperCAmelCase__ :       int							,				UpperCAmelCase__ :       int	):
						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_     :	Any					     =     (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 					__magic_name__(       UpperCAmelCase__ :       Node | None							,				UpperCAmelCase__ :       int							,				UpperCAmelCase__ :       int							,				UpperCAmelCase__ :       int	):
						if start > end:
												return 0
						UpperCamelCase_     :	Tuple					     =     rank_till_index(UpperCAmelCase__							,				UpperCAmelCase__							,				UpperCAmelCase__	)
						UpperCamelCase_     :	Union[str, Any]					     =     rank_till_index(UpperCAmelCase__							,				UpperCAmelCase__							,				start - 1	)
						return rank_till_end - rank_before_start
def 					__magic_name__(       UpperCAmelCase__ :       Node | None							,				UpperCAmelCase__ :       int							,				UpperCAmelCase__ :       int							,				UpperCAmelCase__ :       int	):
						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_     :	Optional[Any]					     =     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 					__magic_name__(       UpperCAmelCase__ :       Node | None							,				UpperCAmelCase__ :       int							,				UpperCAmelCase__ :       int							,				UpperCAmelCase__ :       int							,				UpperCAmelCase__ :       int	):
						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_     :	Dict					     =     range_counting(
						    node.left							,				(node.map_left[start - 1] if start else 0)							,				node.map_left[end] - 1							,				UpperCAmelCase__							,				UpperCAmelCase__							,				)
						UpperCamelCase_     :	Optional[Any]					     =     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()






'''simple docstring'''


from typing import TYPE_CHECKING

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


__SCREAMING_SNAKE_CASE						=      {
    "configuration_markuplm": ["MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "MarkupLMConfig"],
    "feature_extraction_markuplm": ["MarkupLMFeatureExtractor"],
    "processing_markuplm": ["MarkupLMProcessor"],
    "tokenization_markuplm": ["MarkupLMTokenizer"],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__SCREAMING_SNAKE_CASE						=      ["MarkupLMTokenizerFast"]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__SCREAMING_SNAKE_CASE						=      [
	    "MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "MarkupLMForQuestionAnswering",
	    "MarkupLMForSequenceClassification",
	    "MarkupLMForTokenClassification",
	    "MarkupLMModel",
	    "MarkupLMPreTrainedModel",
	]


if TYPE_CHECKING:
	from .configuration_markuplm import MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP, MarkupLMConfig
	from .feature_extraction_markuplm import MarkupLMFeatureExtractor
	from .processing_markuplm import MarkupLMProcessor
	from .tokenization_markuplm import MarkupLMTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_markuplm_fast import MarkupLMTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_markuplm import (
		    MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST,
		    MarkupLMForQuestionAnswering,
		    MarkupLMForSequenceClassification,
		    MarkupLMForTokenClassification,
		    MarkupLMModel,
		    MarkupLMPreTrainedModel,
		)


else:
	import sys

	__SCREAMING_SNAKE_CASE						=      _LazyModule(__name__, globals()["__file__"], _import_structure)




