

import os
from pathlib import Path
def     UpperCAmelCase_       (						):





     '''simple docstring'''




     from torch.utils.cpp_extension import load

     SCREAMING_SNAKE_CASE__   =   Path(_A    ).resolve().parent.parent.parent / '''kernels''' / '''deformable_detr'''
     SCREAMING_SNAKE_CASE__   =   [
         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'''				,		_A				,		with_cuda=_A				,		extra_include_paths=[str(_A    )]				,		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





from __future__ import annotations
def     UpperCAmelCase_       (						_A    ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__   =   len(_A    ) // 2

     # choose the middle 3 elements
     SCREAMING_SNAKE_CASE__   =   lst[m - 1 : m + 2]

     # if middle element is peak
     if three[1] > three[0] and three[1] > three[2]:
          return three[1]

     # if increasing, recurse on right
     elif three[0] < three[2]:
          if len(lst[:m]    ) == 2:
               m -= 1
          return peak(lst[m:]    )

     # decreasing
     else:
          if len(lst[:m]    ) == 2:
               m += 1
          return peak(lst[:m]    )


if __name__ == "__main__":
       import doctest

       doctest.testmod()


