"""simple docstring"""



from __future__ import annotations

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

__lowercase		:		List[Any]								=				TypeVar("T")



class   _A						(    Generic[T]       ):




    """simple docstring"""




    def __init__(		self				:  str						,   A_				:  str						,   A_				:  Any     )     ->							None:
         __snake_case				=				None

         __snake_case				=				len(__SCREAMING_SNAKE_CASE     )
         __snake_case				=				[any_type for _ in range(self.N     )] + arr
         __snake_case				=				fnc
         self.build()
    def 			lowercase       (		self				:  int     )     ->							None:







         for p in range(self.N - 1						,   0						,   -1     ):
              __snake_case				=				self.fn(self.st[p * 2]						,   self.st[p * 2 + 1]     )
    def 			lowercase       (		self				:  Dict						,   A_				:  Optional[Any]						,   A_				:  List[str]     )     ->							None:
         p += self.N
         __snake_case				=				v
         while p > 1:
              __snake_case				=				p // 2
              __snake_case				=				self.fn(self.st[p * 2]						,   self.st[p * 2 + 1]     )







    def 			lowercase       (		self				:  Optional[int]						,   A_				:  Optional[Any]						,   A_				:  int     )     ->							T | None:  # noqa: E741
         __snake_case				=				l + self.N, r + self.N

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


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

       __lowercase		:		List[str]								=				[1, 10, -2, 9, -3, 8, 4, -7, 5, 6, 11, -12]

       __lowercase		:		Optional[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,
       }

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





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

       test_all_segments()

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

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCamelCase  ={
    "configuration_luke": ["LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP", "LukeConfig"],
    "tokenization_luke": ["LukeTokenizer"],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase  =[
        "LUKE_PRETRAINED_MODEL_ARCHIVE_LIST",
        "LukeForEntityClassification",
        "LukeForEntityPairClassification",
        "LukeForEntitySpanClassification",
        "LukeForMultipleChoice",
        "LukeForQuestionAnswering",
        "LukeForSequenceClassification",
        "LukeForTokenClassification",
        "LukeForMaskedLM",
        "LukeModel",
        "LukePreTrainedModel",
    ]


if TYPE_CHECKING:
    from .configuration_luke import LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP, LukeConfig
    from .tokenization_luke import LukeTokenizer

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_luke import (
            LUKE_PRETRAINED_MODEL_ARCHIVE_LIST,
            LukeForEntityClassification,
            LukeForEntityPairClassification,
            LukeForEntitySpanClassification,
            LukeForMaskedLM,
            LukeForMultipleChoice,
            LukeForQuestionAnswering,
            LukeForSequenceClassification,
            LukeForTokenClassification,
            LukeModel,
            LukePreTrainedModel,
        )

else:
    import sys

    lowerCamelCase  =_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


