



from __future__ import annotations

from collections.abc import Callable
from typing import Any, Generic, TypeVar

__snake_case     :Any			       =TypeVar('T')



class        lowerCAmelCase__					(  Generic[T]       ):


				def __init__(							self      :  Union[str, Any]						, __UpperCamelCase      :  list[T]						, __UpperCamelCase      :  Callable[[T, T], T]       )		->     None:
											A      						=    None

											A      						=    len(__UpperCamelCase       )
											A      						=    [any_type for _ in range(self.N       )] + arr
											A      						=    fnc
											self.build()


				def __UpperCamelCase						(							self      :  List[str]       )		->     None:
											for p in range(self.N - 1						, 0						, -1       ):
																		A      						=    self.fn(self.st[p * 2]						, self.st[p * 2 + 1]       )


				def __UpperCamelCase						(							self      :  int						, __UpperCamelCase      :  int						, __UpperCamelCase      :  T       )		->     None:
											p += self.N
											A      						=    v
											while p > 1:
																		A      						=    p // 2
																		A      						=    self.fn(self.st[p * 2]						, self.st[p * 2 + 1]       )


				def __UpperCamelCase						(							self      :  Union[str, Any]						, __UpperCamelCase      :  int						, __UpperCamelCase      :  int       )		->     T | None:  # noqa: E741
											A						,   A      						=    l + self.N, r + self.N

											A      						=    None
											while l <= r:
																		if l % 2 == 1:
																									A      						=    self.st[l] if res is None else self.fn(__UpperCamelCase						, self.st[l]       )
																		if r % 2 == 0:
																									A      						=    self.st[r] if res is None else self.fn(__UpperCamelCase						, self.st[r]       )
																		A						,   A      						=    (l + 1) // 2, (r - 1) // 2
											return res


if __name__ == "__main__":
				from functools import reduce

				__snake_case     :int			       =[1, 10, -2, 9, -3, 8, 4, -7, 5, 6, 11, -12]

				__snake_case     :int			       ={
				    0: 7,
				    1: 2,
				    2: 6,
				    3: -14,
				    4: 5,
				    5: 4,
				    6: 7,
				    7: -10,
				    8: 9,
				    9: 10,
				    10: 12,
				    11: 1,
				}

				__snake_case     :int			       =SegmentTree(test_array, min)
				__snake_case     :List[str]			       =SegmentTree(test_array, max)
				__snake_case     :Any			       =SegmentTree(test_array, lambda a, b: a + b)






				def  lowerCamelCase_	(      )       ->							None:

											'''simple docstring'''






											for i in range(len(lowerCAmelCase__				)				):
																		for j in range(lowerCAmelCase__			,	len(lowerCAmelCase__				)				):
																									A      						=    reduce(lowerCAmelCase__			,	test_array[i : j + 1]				)
																									A      						=    reduce(lowerCAmelCase__			,	test_array[i : j + 1]				)
																									A      						=    reduce(lambda lowerCAmelCase__			,	lowerCAmelCase__				: a + b			,	test_array[i : j + 1]				)
																									assert min_range == min_segment_tree.query(lowerCAmelCase__			,	lowerCAmelCase__				)
																									assert max_range == max_segment_tree.query(lowerCAmelCase__			,	lowerCAmelCase__				)
																									assert sum_range == sum_segment_tree.query(lowerCAmelCase__			,	lowerCAmelCase__				)

				test_all_segments()

				for index, value in test_updates.items():
								__snake_case     :Optional[Any]			       =value
								min_segment_tree.update(index, value)
								max_segment_tree.update(index, value)
								sum_segment_tree.update(index, value)
								test_all_segments()




import os
import time

import numpy as np
import onnxruntime as ort


__snake_case     :Any			       ='1'
__snake_case     :List[str]			       ='0'
__snake_case     :Union[str, Any]			       ='1'

__snake_case     :Optional[Any]			       =ort.SessionOptions()
__snake_case     :List[str]			       =ort.GraphOptimizationLevel.ORT_DISABLE_ALL
print('Create inference session...')
__snake_case     :int			       =['TensorrtExecutionProvider', 'CUDAExecutionProvider']
__snake_case     :Optional[Any]			       =ort.InferenceSession('model.onnx', sess_options=sess_opt, providers=execution_provider)
__snake_case     :int			       =ort.RunOptions()

__snake_case     :Tuple			       =128
__snake_case     :List[Any]			       =1
__snake_case     :Union[str, Any]			       =np.ones((batch, sequence), dtype=np.intaa)
__snake_case     :Optional[Any]			       =np.ones((batch, sequence), dtype=np.intaa)
__snake_case     :Optional[int]			       =np.ones((batch, sequence), dtype=np.intaa)

print('Warm up phase...')
sess.run(
    None,
    {
        sess.get_inputs()[0].name: input_ids,
        sess.get_inputs()[1].name: attention_mask,
        sess.get_inputs()[2].name: token_type_ids,
    },
    run_options=run_opt,
)

print('Start inference...')
__snake_case     :Union[str, Any]			       =time.time()
__snake_case     :int			       =2000
__snake_case     :Optional[int]			       ={}
for iter in range(max_iters):
				__snake_case     :Optional[Any]			       =sess.run(
				    None,
				    {
				        sess.get_inputs()[0].name: input_ids,
				        sess.get_inputs()[1].name: attention_mask,
				        sess.get_inputs()[2].name: token_type_ids,
				    },
				    run_options=run_opt,
				)
print('Average Inference Time = {:.3f} ms'.format((time.time() - start_time) * 1000 / max_iters))