






from collections.abc import Sequence
from queue import Queue

class     _SCREAMING_SNAKE_CASE       :





	def __init__(		self				:					Union[str, Any] ,  __lowerCamelCase				:					Any ,  __lowerCamelCase				:					str ,  __lowerCamelCase				:					Any ,  __lowerCamelCase				:					str=None ,  __lowerCamelCase				:					Optional[Any]=None	):
		UpperCamelCase     :List[Any]          =	start
		UpperCamelCase     :str          =	end
		UpperCamelCase     :Tuple          =	val
		UpperCamelCase     :Tuple          =	(start + end) // 2
		UpperCamelCase     :str          =	left
		UpperCamelCase     :Optional[int]          =	right





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

class     _SCREAMING_SNAKE_CASE       :





	def __init__(		self				:					Optional[int] ,  __lowerCamelCase				:					Sequence ,  __lowerCamelCase				:					List[Any]	):
		UpperCamelCase     :int          =	collection
		UpperCamelCase     :List[Any]          =	function
		if self.collection:
			UpperCamelCase     :Tuple          =	self._build_tree(0 ,  len(__lowerCamelCase	) - 1	)





	def 						_A (		self				:					Any ,  __lowerCamelCase				:					List[Any] ,  __lowerCamelCase				:					int	):
		self._update_tree(self.root ,  __lowerCamelCase ,  __lowerCamelCase	)





	def 						_A (		self				:					Any ,  __lowerCamelCase				:					List[Any] ,  __lowerCamelCase				:					Tuple	):
		return self._query_range(self.root ,  __lowerCamelCase ,  __lowerCamelCase	)





	def 						_A (		self				:					Tuple ,  __lowerCamelCase				:					str ,  __lowerCamelCase				:					List[str]	):
		if start == end:
			return SegmentTreeNode(__lowerCamelCase ,  __lowerCamelCase ,  self.collection[start]	)
		UpperCamelCase     :Dict          =	(start + end) // 2
		UpperCamelCase     :List[str]          =	self._build_tree(__lowerCamelCase ,  __lowerCamelCase	)
		UpperCamelCase     :Union[str, Any]          =	self._build_tree(mid + 1 ,  __lowerCamelCase	)
		return SegmentTreeNode(__lowerCamelCase ,  __lowerCamelCase ,  self.fn(left.val ,  right.val	) ,  __lowerCamelCase ,  __lowerCamelCase	)





	def 						_A (		self				:					List[str] ,  __lowerCamelCase				:					Dict ,  __lowerCamelCase				:					List[Any] ,  __lowerCamelCase				:					List[str]	):
		if node.start == i and node.end == i:
			UpperCamelCase     :List[Any]          =	val
			return
		if i <= node.mid:
			self._update_tree(node.left ,  __lowerCamelCase ,  __lowerCamelCase	)
		else:
			self._update_tree(node.right ,  __lowerCamelCase ,  __lowerCamelCase	)
		UpperCamelCase     :Union[str, Any]          =	self.fn(node.left.val ,  node.right.val	)





	def 						_A (		self				:					List[str] ,  __lowerCamelCase				:					Union[str, Any] ,  __lowerCamelCase				:					Optional[int] ,  __lowerCamelCase				:					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 ,  __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				:					Optional[Any]	):
		if self.root is not None:
			UpperCamelCase     :Union[str, Any]          =	Queue()
			queue.put(self.root	)
			while not queue.empty():
				UpperCamelCase     :Optional[int]          =	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_ :						Optional[int]      =      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_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCAmelCase_ :						str      =      {'''configuration_opt''': ['''OPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''OPTConfig''']}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase_ :						Tuple      =      [
	    '''OPT_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''OPTForCausalLM''',
	    '''OPTModel''',
	    '''OPTPreTrainedModel''',
	    '''OPTForSequenceClassification''',
	    '''OPTForQuestionAnswering''',
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase_ :						Any      =      ['''TFOPTForCausalLM''', '''TFOPTModel''', '''TFOPTPreTrainedModel''']

try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase_ :						Optional[Any]      =      [
	    '''FlaxOPTForCausalLM''',
	    '''FlaxOPTModel''',
	    '''FlaxOPTPreTrainedModel''',
	]


if TYPE_CHECKING:
	from .configuration_opt import OPT_PRETRAINED_CONFIG_ARCHIVE_MAP, OPTConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_opt import (
		    OPT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    OPTForCausalLM,
		    OPTForQuestionAnswering,
		    OPTForSequenceClassification,
		    OPTModel,
		    OPTPreTrainedModel,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_opt import TFOPTForCausalLM, TFOPTModel, TFOPTPreTrainedModel

	try:
		if not is_flax_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_flax_opt import FlaxOPTForCausalLM, FlaxOPTModel, FlaxOPTPreTrainedModel

else:
	import sys

	UpperCAmelCase_ :						List[Any]      =      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
