



'''simple docstring'''

from __future__ import annotations

import math

class       __magic_name__		:







							def __init__(				self   :			Union[str, Any]      ,_UpperCAmelCase   :			int						):
									_a	: Optional[Any]								=				size
									# approximate the overall size of segment tree with given value
									_a	: Dict								=				[0 for i in range(0      ,4 * size						)]
									# create array to store lazy update
									_a	: Union[str, Any]								=				[0 for i in range(0      ,4 * size						)]
									_a	: Union[str, Any]								=				[0 for i in range(0      ,4 * size						)]  # flag for lazy update







							def 				__lowercase     (				self   :			List[str]      ,_UpperCAmelCase   :			int						):
									return idx * 2







							def 				__lowercase     (				self   :			int      ,_UpperCAmelCase   :			int						):
									return idx * 2 + 1







							def 				__lowercase     (				self   :			Dict      ,_UpperCAmelCase   :			int      ,_UpperCAmelCase   :			int      ,_UpperCAmelCase   :			int      ,_UpperCAmelCase   :			list[int]						):
									if left_element == right_element:
											_a	: int								=				a[left_element - 1]
									else:
											_a	: Optional[int]								=				(left_element + right_element) // 2
											self.build(self.left(_UpperCAmelCase						)      ,_UpperCAmelCase      ,_UpperCAmelCase      ,_UpperCAmelCase						)
											self.build(self.right(_UpperCAmelCase						)      ,mid + 1      ,_UpperCAmelCase      ,_UpperCAmelCase						)
											_a	: str								=				max(
											    self.segment_tree[self.left(_UpperCAmelCase						)]      ,self.segment_tree[self.right(_UpperCAmelCase						)]						)







							def 				__lowercase     (				self   :			str      ,_UpperCAmelCase   :			int      ,_UpperCAmelCase   :			int      ,_UpperCAmelCase   :			int      ,_UpperCAmelCase   :			int      ,_UpperCAmelCase   :			int      ,_UpperCAmelCase   :			int						):
									if self.flag[idx] is True:
											_a	: Optional[Any]								=				self.lazy[idx]
											_a	: str								=				False
											if left_element != right_element:
													_a	: Dict								=				self.lazy[idx]
													_a	: Union[str, Any]								=				self.lazy[idx]
													_a	: Dict								=				True
													_a	: Optional[Any]								=				True

									if right_element < a or left_element > b:
											return True
									if left_element >= a and right_element <= b:
											_a	: List[Any]								=				val
											if left_element != right_element:
													_a	: int								=				val
													_a	: Union[str, Any]								=				val
													_a	: List[str]								=				True
													_a	: Optional[int]								=				True
											return True
									_a	: Optional[Any]								=				(left_element + right_element) // 2
									self.update(self.left(_UpperCAmelCase						)      ,_UpperCAmelCase      ,_UpperCAmelCase      ,_UpperCAmelCase      ,_UpperCAmelCase      ,_UpperCAmelCase						)
									self.update(self.right(_UpperCAmelCase						)      ,mid + 1      ,_UpperCAmelCase      ,_UpperCAmelCase      ,_UpperCAmelCase      ,_UpperCAmelCase						)
									_a	: List[str]								=				max(
									    self.segment_tree[self.left(_UpperCAmelCase						)]      ,self.segment_tree[self.right(_UpperCAmelCase						)]						)
									return True







							def 				__lowercase     (				self   :			Optional[Any]      ,_UpperCAmelCase   :			int      ,_UpperCAmelCase   :			int      ,_UpperCAmelCase   :			int      ,_UpperCAmelCase   :			int      ,_UpperCAmelCase   :			int						):
									if self.flag[idx] is True:
											_a	: Tuple								=				self.lazy[idx]
											_a	: List[Any]								=				False
											if left_element != right_element:
													_a	: Optional[int]								=				self.lazy[idx]
													_a	: Dict								=				self.lazy[idx]
													_a	: Optional[int]								=				True
													_a	: Union[str, Any]								=				True
									if right_element < a or left_element > b:
											return -math.inf
									if left_element >= a and right_element <= b:
											return self.segment_tree[idx]
									_a	: Tuple								=				(left_element + right_element) // 2
									_a	: List[str]								=				self.query(self.left(_UpperCAmelCase						)      ,_UpperCAmelCase      ,_UpperCAmelCase      ,_UpperCAmelCase      ,_UpperCAmelCase						)
									_a	: Dict								=				self.query(self.right(_UpperCAmelCase						)      ,mid + 1      ,_UpperCAmelCase      ,_UpperCAmelCase      ,_UpperCAmelCase						)
									return max(_UpperCAmelCase      ,_UpperCAmelCase						)







							def __str__(				self   :			Any						):
									return str([self.query(1      ,1      ,self.size      ,_UpperCAmelCase      ,_UpperCAmelCase						) for i in range(1      ,self.size + 1						)]						)


if __name__ == "__main__":
							__lowerCAmelCase		     =  [1, 2, -4, 7, 3, -5, 6, 11, -20, 9, 14, 15, 5, 2, -8]
							__lowerCAmelCase		     =  15
							__lowerCAmelCase		     =  SegmentTree(size)
							segt.build(1, 1, size, A)
							print(segt.query(1, 1, size, 4, 6))
							print(segt.query(1, 1, size, 7, 11))
							print(segt.query(1, 1, size, 7, 12))
							segt.update(1, 1, size, 1, 3, 111)
							print(segt.query(1, 1, size, 1, 15))
							segt.update(1, 1, size, 7, 8, 235)
							print(segt)









'''simple docstring'''

from typing import TYPE_CHECKING

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


__lowerCAmelCase		     =  {
    '''configuration_ernie''': ['''ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ErnieConfig''', '''ErnieOnnxConfig'''],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase		     =  [
							    '''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

							__lowerCAmelCase		     =  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




