from __future__ import annotations

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

SCREAMING_SNAKE_CASE :	Union[str, Any]							     =		TypeVar("""T""")
class    A_ (       Generic[T] ):

  def __init__(		self :      str     ,							__SCREAMING_SNAKE_CASE :      list[T]     ,							__SCREAMING_SNAKE_CASE :      Callable[[T, T], T]       ):
   __a       =  None

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

  def 		_UpperCAmelCase   (		self :      Tuple       ):
   for p in range(self.N - 1     ,							0     ,							-1       ):
    __a       =  self.fn(self.st[p * 2]     ,							self.st[p * 2 + 1]       )

  def 		_UpperCAmelCase   (		self :      Any     ,							__SCREAMING_SNAKE_CASE :      int     ,							__SCREAMING_SNAKE_CASE :      T       ):
   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 :      List[Any]     ,							__SCREAMING_SNAKE_CASE :      int     ,							__SCREAMING_SNAKE_CASE :      int       ):  # 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(__SCREAMING_SNAKE_CASE     ,							self.st[l]       )
    if r % 2 == 0:
     __a       =  self.st[r] if res is None else self.fn(__SCREAMING_SNAKE_CASE     ,							self.st[r]       )
    __a       ,     __a       =  (l + 1) // 2, (r - 1) // 2
   return res


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

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

  SCREAMING_SNAKE_CASE :	Optional[Any]							     =		{
      0: 7,
      1: 2,
      2: 6,
      3: -14,
      4: 5,
      5: 4,
      6: 7,
      7: -10,
      8: 9,
      9: 10,
      10: 12,
      11: 1,
  }

  SCREAMING_SNAKE_CASE :	Tuple							     =		SegmentTree(test_array, min)
  SCREAMING_SNAKE_CASE :	Optional[int]							     =		SegmentTree(test_array, max)
  SCREAMING_SNAKE_CASE :	int							     =		SegmentTree(test_array, lambda a, b: a + b)



  def   __A		(			):



   """simple docstring"""


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

  test_all_segments()

  for index, value in test_updates.items():
    SCREAMING_SNAKE_CASE :	Dict							     =		value
    min_segment_tree.update(index, value)
    max_segment_tree.update(index, value)
    sum_segment_tree.update(index, value)
    test_all_segments()



import pytest

import datasets.config
from datasets.utils.info_utils import is_small_dataset



@pytest.mark.parametrize("dataset_size"							,				[None, 400 * 2**20, 600 * 2**20]					)
@pytest.mark.parametrize("input_in_memory_max_size"							,				["default", 0, 100 * 2**20, 900 * 2**20]					)
def   __A		(			_A							,				_A							,				_A					):



 """simple docstring"""


 if input_in_memory_max_size != "default":
  monkeypatch.setattr(datasets.config							,				"IN_MEMORY_MAX_SIZE"							,				_A					)
 __a       =  datasets.config.IN_MEMORY_MAX_SIZE
 if input_in_memory_max_size == "default":
  assert in_memory_max_size == 0
 else:
  assert in_memory_max_size == input_in_memory_max_size
 if dataset_size and in_memory_max_size:
  __a       =  dataset_size < in_memory_max_size
 else:
  __a       =  False
 __a       =  is_small_dataset(_A					)
 assert result == expected


