






from collections.abc import Sequence
from queue import Queue
class  lowerCAmelCase_       :




							def __init__(   self     :   str ,							SCREAMING_SNAKE_CASE_     :   List[Any] ,							SCREAMING_SNAKE_CASE_     :   str ,							SCREAMING_SNAKE_CASE_     :   List[Any] ,							SCREAMING_SNAKE_CASE_     :   Dict=None ,							SCREAMING_SNAKE_CASE_     :   int=None	):
											lowerCAmelCase__      			=						start
											lowerCAmelCase__      			=						end
											lowerCAmelCase__      			=						val
											lowerCAmelCase__      			=						(start + end) // 2
											lowerCAmelCase__      			=						left
											lowerCAmelCase__      			=						right




							def __repr__(   self     :   List[Any]	):
											return f'SegmentTreeNode(start={self.start}, end={self.end}, val={self.val})'



class  lowerCAmelCase_       :




							def __init__(   self     :   List[Any] ,							SCREAMING_SNAKE_CASE_     :   Sequence ,							SCREAMING_SNAKE_CASE_     :   Union[str, Any]	):
											lowerCAmelCase__      			=						collection
											lowerCAmelCase__      			=						function
											if self.collection:
															lowerCAmelCase__      			=						self._build_tree(0 ,							len(SCREAMING_SNAKE_CASE_	) - 1	)




							def 						__snake_case					(   self     :   Dict ,							SCREAMING_SNAKE_CASE_     :   Optional[Any] ,							SCREAMING_SNAKE_CASE_     :   str	):
											self._update_tree(self.root ,							SCREAMING_SNAKE_CASE_ ,							SCREAMING_SNAKE_CASE_	)




							def 						__snake_case					(   self     :   Dict ,							SCREAMING_SNAKE_CASE_     :   Tuple ,							SCREAMING_SNAKE_CASE_     :   Union[str, Any]	):
											return self._query_range(self.root ,							SCREAMING_SNAKE_CASE_ ,							SCREAMING_SNAKE_CASE_	)




							def 						__snake_case					(   self     :   Optional[int] ,							SCREAMING_SNAKE_CASE_     :   int ,							SCREAMING_SNAKE_CASE_     :   str	):
											if start == end:
															return SegmentTreeNode(SCREAMING_SNAKE_CASE_ ,							SCREAMING_SNAKE_CASE_ ,							self.collection[start]	)
											lowerCAmelCase__      			=						(start + end) // 2
											lowerCAmelCase__      			=						self._build_tree(SCREAMING_SNAKE_CASE_ ,							SCREAMING_SNAKE_CASE_	)
											lowerCAmelCase__      			=						self._build_tree(mid + 1 ,							SCREAMING_SNAKE_CASE_	)
											return SegmentTreeNode(SCREAMING_SNAKE_CASE_ ,							SCREAMING_SNAKE_CASE_ ,							self.fn(left.val ,							right.val	) ,							SCREAMING_SNAKE_CASE_ ,							SCREAMING_SNAKE_CASE_	)




							def 						__snake_case					(   self     :   str ,							SCREAMING_SNAKE_CASE_     :   Optional[Any] ,							SCREAMING_SNAKE_CASE_     :   Optional[int] ,							SCREAMING_SNAKE_CASE_     :   int	):
											if node.start == i and node.end == i:
															lowerCAmelCase__      			=						val
															return
											if i <= node.mid:
															self._update_tree(node.left ,							SCREAMING_SNAKE_CASE_ ,							SCREAMING_SNAKE_CASE_	)
											else:
															self._update_tree(node.right ,							SCREAMING_SNAKE_CASE_ ,							SCREAMING_SNAKE_CASE_	)
											lowerCAmelCase__      			=						self.fn(node.left.val ,							node.right.val	)




							def 						__snake_case					(   self     :   Dict ,							SCREAMING_SNAKE_CASE_     :   Any ,							SCREAMING_SNAKE_CASE_     :   Optional[int] ,							SCREAMING_SNAKE_CASE_     :   List[str]	):
											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 ,							SCREAMING_SNAKE_CASE_ ,							SCREAMING_SNAKE_CASE_	)
															else:
																			# range in left child tree and right child tree
																			return self.fn(
																			    self._query_range(node.left ,							SCREAMING_SNAKE_CASE_ ,							node.mid	) ,							self._query_range(node.right ,							node.mid + 1 ,							SCREAMING_SNAKE_CASE_	) ,							)
											else:
															# range in right child tree
															return self._query_range(node.right ,							SCREAMING_SNAKE_CASE_ ,							SCREAMING_SNAKE_CASE_	)




							def 						__snake_case					(   self     :   Any	):
											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)
						_UpperCAmelCase			:		List[str]   				=    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_tensorflow_text_available, is_torch_available


_UpperCAmelCase			:		Optional[Any]   				=    {
    "configuration_ernie": ["ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP", "ErnieConfig", "ErnieOnnxConfig"],
}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_UpperCAmelCase			:		Any   				=    [
			    "ERNIE_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "ErnieForCausalLM",
			    "ErnieForMaskedLM",
			    "ErnieForMultipleChoice",
			    "ErnieForNextSentencePrediction",
			    "ErnieForPreTraining",
			    "ErnieForQuestionAnswering",
			    "ErnieForSequenceClassification",
			    "ErnieForTokenClassification",
			    "ErnieModel",
			    "ErniePreTrainedModel",
			]

if TYPE_CHECKING:
			from .configuration_ernie import ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP, ErnieConfig, ErnieOnnxConfig

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_ernie import (
						    ERNIE_PRETRAINED_MODEL_ARCHIVE_LIST,
						    ErnieForCausalLM,
						    ErnieForMaskedLM,
						    ErnieForMultipleChoice,
						    ErnieForNextSentencePrediction,
						    ErnieForPreTraining,
						    ErnieForQuestionAnswering,
						    ErnieForSequenceClassification,
						    ErnieForTokenClassification,
						    ErnieModel,
						    ErniePreTrainedModel,
						)

else:
			import sys

			_UpperCAmelCase			:		Dict   				=    _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





