





'''simple docstring'''






from __future__ import annotations

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







def 					_a						(       ) ->				tuple[list[int], int]:



			"""simple docstring"""


			__snake_case					:      str							      =     [randint(-1000    ,	1000 ) for i in range(10 )]
			__snake_case					:      str							      =     randint(-5000    ,	5000 )
			return (arr, r)


__UpperCamelCase					    =	make_dataset()







def 					_a						(       _lowerCamelCase    ,	_lowerCamelCase ) ->				tuple[int, ...]:



			"""simple docstring"""


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







def 					_a						(       _lowerCamelCase    ,	_lowerCamelCase ) ->				tuple[int, int, int]:



			"""simple docstring"""


			arr.sort()
			__snake_case					:      Any							      =     len(_lowerCamelCase )
			for i in range(n - 1 ):
						__snake_case      ,     __snake_case					:      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 					_a						(       ) ->				tuple[float, float]:



			"""simple docstring"""


			__snake_case					:      Tuple							      =     """
from __main__ import dataset, triplet_sum1, triplet_sum2
"""
			__snake_case					:      int							      =     """
triplet_sum1(*dataset)
"""
			__snake_case					:      List[Any]							      =     """
triplet_sum2(*dataset)
"""
			__snake_case					:      str							      =     repeat(setup=_lowerCamelCase    ,	stmt=_lowerCamelCase    ,	repeat=5    ,	number=1_0000 )
			__snake_case					:      int							      =     repeat(setup=_lowerCamelCase    ,	stmt=_lowerCamelCase    ,	repeat=5    ,	number=1_0000 )
			return (min(_lowerCamelCase ), min(_lowerCamelCase ))


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

	testmod()
	__UpperCamelCase					    =	solution_times()
	print(f"""The time for naive implementation is {times[0]}.""")
	print(f"""The time for optimized implementation is {times[1]}.""")






'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


lowerCAmelCase     :  int											=    {
    """configuration_owlvit""": [
        """OWLVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """OwlViTConfig""",
        """OwlViTOnnxConfig""",
        """OwlViTTextConfig""",
        """OwlViTVisionConfig""",
    ],
    """processing_owlvit""": ["""OwlViTProcessor"""],
}


try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCAmelCase     :  Dict											=    ["""OwlViTFeatureExtractor"""]
       lowerCAmelCase     :  int											=    ["""OwlViTImageProcessor"""]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCAmelCase     :  Optional[Any]											=    [
           """OWLVIT_PRETRAINED_MODEL_ARCHIVE_LIST""",
           """OwlViTModel""",
           """OwlViTPreTrainedModel""",
           """OwlViTTextModel""",
           """OwlViTVisionModel""",
           """OwlViTForObjectDetection""",
       ]

if TYPE_CHECKING:
       from .configuration_owlvit import (
           OWLVIT_PRETRAINED_CONFIG_ARCHIVE_MAP,
           OwlViTConfig,
           OwlViTOnnxConfig,
           OwlViTTextConfig,
           OwlViTVisionConfig,
       )
       from .processing_owlvit import OwlViTProcessor

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .feature_extraction_owlvit import OwlViTFeatureExtractor
              from .image_processing_owlvit import OwlViTImageProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_owlvit import (
                  OWLVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  OwlViTForObjectDetection,
                  OwlViTModel,
                  OwlViTPreTrainedModel,
                  OwlViTTextModel,
                  OwlViTVisionModel,
              )

else:
       import sys

       lowerCAmelCase     :  Union[str, Any]											=    _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

