






from collections.abc import Sequence
from queue import Queue


class 							__UpperCamelCase     :







	def __init__(	self   :				Optional[Any]							,					_lowerCAmelCase   :				Tuple							,					_lowerCAmelCase   :				List[Any]							,					_lowerCAmelCase   :				Union[str, Any]							,					_lowerCAmelCase   :				Any=None							,					_lowerCAmelCase   :				Dict=None      )		->			List[Any]:
		"""simple docstring"""







		__lowercase   							=	start
		__lowercase   							=	end
		__lowercase   							=	val
		__lowercase   							=	(start + end) // 2
		__lowercase   							=	left
		__lowercase   							=	right







	def __repr__(	self   :				List[Any]      )		->			List[Any]:
		"""simple docstring"""







		return F'SegmentTreeNode(start={self.start}, end={self.end}, val={self.val})'


class 							__UpperCamelCase     :







	def __init__(	self   :				Dict							,					_lowerCAmelCase   :				Sequence							,					_lowerCAmelCase   :				str      )		->			Union[str, Any]:
		"""simple docstring"""







		__lowercase   							=	collection
		__lowercase   							=	function
		if self.collection:
			__lowercase   							=	self._build_tree(0							,					len(_lowerCAmelCase      ) - 1      )







	def 			_a (	self   :				int							,					_lowerCAmelCase   :				List[Any]							,					_lowerCAmelCase   :				List[str]      )		->			Tuple:
		"""simple docstring"""







		self._update_tree(self.root							,					_lowerCAmelCase							,					_lowerCAmelCase      )







	def 			_a (	self   :				Any							,					_lowerCAmelCase   :				List[Any]							,					_lowerCAmelCase   :				Tuple      )		->			List[Any]:
		"""simple docstring"""







		return self._query_range(self.root							,					_lowerCAmelCase							,					_lowerCAmelCase      )







	def 			_a (	self   :				Any							,					_lowerCAmelCase   :				str							,					_lowerCAmelCase   :				str      )		->			str:
		"""simple docstring"""







		if start == end:
			return SegmentTreeNode(_lowerCAmelCase							,					_lowerCAmelCase							,					self.collection[start]      )
		__lowercase   							=	(start + end) // 2
		__lowercase   							=	self._build_tree(_lowerCAmelCase							,					_lowerCAmelCase      )
		__lowercase   							=	self._build_tree(mid + 1							,					_lowerCAmelCase      )
		return SegmentTreeNode(_lowerCAmelCase							,					_lowerCAmelCase							,					self.fn(left.val							,					right.val      )							,					_lowerCAmelCase							,					_lowerCAmelCase      )







	def 			_a (	self   :				List[str]							,					_lowerCAmelCase   :				List[Any]							,					_lowerCAmelCase   :				Optional[Any]							,					_lowerCAmelCase   :				Union[str, Any]      )		->			Tuple:
		"""simple docstring"""







		if node.start == i and node.end == i:
			__lowercase   							=	val
			return
		if i <= node.mid:
			self._update_tree(node.left							,					_lowerCAmelCase							,					_lowerCAmelCase      )
		else:
			self._update_tree(node.right							,					_lowerCAmelCase							,					_lowerCAmelCase      )
		__lowercase   							=	self.fn(node.left.val							,					node.right.val      )







	def 			_a (	self   :				Optional[Any]							,					_lowerCAmelCase   :				Tuple							,					_lowerCAmelCase   :				Union[str, Any]							,					_lowerCAmelCase   :				List[Any]      )		->			Optional[int]:
		"""simple docstring"""







		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							,					_lowerCAmelCase							,					_lowerCAmelCase      )
			else:
				# range in left child tree and right child tree
				return self.fn(
				    self._query_range(node.left							,					_lowerCAmelCase							,					node.mid      )							,					self._query_range(node.right							,					node.mid + 1							,					_lowerCAmelCase      )							,					)
		else:
			# range in right child tree
			return self._query_range(node.right							,					_lowerCAmelCase							,					_lowerCAmelCase      )







	def 			_a (	self   :				List[Any]      )		->			Tuple:
		"""simple docstring"""







		if self.root is not None:
			__lowercase   							=	Queue()
			queue.put(self.root      )
			while not queue.empty():
				__lowercase   							=	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)
												__UpperCamelCase   :   Union[str, Any]      =    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()









from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A__      :     Optional[int]       =					{
    'configuration_clap': [
        'CLAP_PRETRAINED_MODEL_ARCHIVE_LIST',
        'ClapAudioConfig',
        'ClapConfig',
        'ClapTextConfig',
    ],
    'processing_clap': ['ClapProcessor'],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A__      :     str       =					[
							    'CLAP_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'ClapModel',
							    'ClapPreTrainedModel',
							    'ClapTextModel',
							    'ClapTextModelWithProjection',
							    'ClapAudioModel',
							    'ClapAudioModelWithProjection',
							]
							A__      :     List[Any]       =					['ClapFeatureExtractor']

if TYPE_CHECKING:
							from .configuration_clap import (
							    CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
							    ClapAudioConfig,
							    ClapConfig,
							    ClapTextConfig,
							)
							from .processing_clap import ClapProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_clap import ClapFeatureExtractor
														from .modeling_clap import (
														    CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
														    ClapAudioModel,
														    ClapAudioModelWithProjection,
														    ClapModel,
														    ClapPreTrainedModel,
														    ClapTextModel,
														    ClapTextModelWithProjection,
														)


else:
							import sys

							A__      :     int       =					_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




