
'''simple docstring'''




import os
from pathlib import Path







def 						lowerCAmelCase_							(  ):




    '''simple docstring'''



    from torch.utils.cpp_extension import load

    A			:  Optional[int]   =		Path(snake_case__		).resolve().parent.parent.parent / '''kernels''' / '''deformable_detr'''
    A			:  List[Any]   =		[
        root / filename
        for filename in [
            '''vision.cpp''',
            os.path.join('''cpu'''						,							'''ms_deform_attn_cpu.cpp'''		),
            os.path.join('''cuda'''						,							'''ms_deform_attn_cuda.cu'''		),
        ]
    ]

    load(
        '''MultiScaleDeformableAttention'''						,							snake_case__						,							with_cuda=snake_case__						,							extra_include_paths=[str(snake_case__		)]						,							extra_cflags=['''-DWITH_CUDA=1''']						,							extra_cuda_cflags=[
            '''-DCUDA_HAS_FP16=1''',
            '''-D__CUDA_NO_HALF_OPERATORS__''',
            '''-D__CUDA_NO_HALF_CONVERSIONS__''',
            '''-D__CUDA_NO_HALF2_OPERATORS__''',
        ]						,							)

    import MultiScaleDeformableAttention as MSDA

    return MSDA






'''simple docstring'''




import math
from collections.abc import Callable







def 						lowerCAmelCase_							(  snake_case__						,							snake_case__						,							snake_case__		):




    '''simple docstring'''



    A			:  float   =		xa
    A			:  float   =		xa
    while True:
        if x_n == x_na or function(snake_case__		) == function(snake_case__		):
            raise ZeroDivisionError('''float division by zero, could not find root'''		)
        A			:  float   =		x_na - (
            function(snake_case__		) / ((function(snake_case__		) - function(snake_case__		)) / (x_na - x_n))
        )
        if abs(x_na - x_na		) < 10**-5:
            return x_na
        A			:  Any   =		x_na
        A			:  Any   =		x_na







def 						lowerCAmelCase_							(  snake_case__		):




    '''simple docstring'''



    return math.pow(snake_case__						,							3		) - (2 * x) - 5


if __name__ == "__main__":
      print(intersection(f, 3, 3.5))




