
from __future__ import annotations

from itertools import permutations
from random import randint
from timeit import repeat


def 							SCREAMING_SNAKE_CASE_      (			):
      UpperCamelCase__    :   str					=				[randint(-1_0_0_0 ,		1_0_0_0		) for i in range(1_0		)]
      UpperCamelCase__    :   str					=				randint(-5_0_0_0 ,		5_0_0_0		)
      return (arr, r)


lowerCamelCase      =make_dataset()


def 							SCREAMING_SNAKE_CASE_      (			UpperCamelCase__ ,		UpperCamelCase__		):
      for triplet in permutations(UpperCamelCase__ ,		3		):
            if sum(UpperCamelCase__		) == target:
                  return tuple(sorted(UpperCamelCase__		)		)
      return (0, 0, 0)


def 							SCREAMING_SNAKE_CASE_      (			UpperCamelCase__ ,		UpperCamelCase__		):
      arr.sort()
      UpperCamelCase__    :   int					=				len(UpperCamelCase__		)
      for i in range(n - 1		):
            UpperCamelCase__				,UpperCamelCase__    :   Optional[int]					=				i + 1, n - 1
            while left < right:
                  if arr[i] + arr[left] + arr[right] == target:
                        return (arr[i], arr[left], arr[right])
                  elif arr[i] + arr[left] + arr[right] < target:
                        left += 1
                  elif arr[i] + arr[left] + arr[right] > target:
                        right -= 1
      return (0, 0, 0)


def 							SCREAMING_SNAKE_CASE_      (			):
      UpperCamelCase__    :   List[str]					=				'''
from __main__ import dataset, triplet_sum1, triplet_sum2
'''
      UpperCamelCase__    :   List[Any]					=				'''
triplet_sum1(*dataset)
'''
      UpperCamelCase__    :   List[Any]					=				'''
triplet_sum2(*dataset)
'''
      UpperCamelCase__    :   Union[str, Any]					=				repeat(setup=UpperCamelCase__ ,		stmt=UpperCamelCase__ ,		repeat=5 ,		number=1_0_0_0_0		)
      UpperCamelCase__    :   Optional[int]					=				repeat(setup=UpperCamelCase__ ,		stmt=UpperCamelCase__ ,		repeat=5 ,		number=1_0_0_0_0		)
      return (min(UpperCamelCase__		), min(UpperCamelCase__		))


if __name__ == "__main__":
    from doctest import testmod

    testmod()
    lowerCamelCase      =solution_times()
    print(F'''The time for naive implementation is {times[0]}.''')
    print(F'''The time for optimized implementation is {times[1]}.''')




from typing import TYPE_CHECKING

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


lowerCamelCase      ={"configuration_swin": ["SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP", "SwinConfig", "SwinOnnxConfig"]}


try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase      =[
        "SWIN_PRETRAINED_MODEL_ARCHIVE_LIST",
        "SwinForImageClassification",
        "SwinForMaskedImageModeling",
        "SwinModel",
        "SwinPreTrainedModel",
        "SwinBackbone",
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase      =[
        "TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST",
        "TFSwinForImageClassification",
        "TFSwinForMaskedImageModeling",
        "TFSwinModel",
        "TFSwinPreTrainedModel",
    ]

if TYPE_CHECKING:
    from .configuration_swin import SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinConfig, SwinOnnxConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_swin import (
            SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
            SwinBackbone,
            SwinForImageClassification,
            SwinForMaskedImageModeling,
            SwinModel,
            SwinPreTrainedModel,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_swin import (
            TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFSwinForImageClassification,
            TFSwinForMaskedImageModeling,
            TFSwinModel,
            TFSwinPreTrainedModel,
        )

else:
    import sys

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


