






'''simple docstring'''







import os
from pathlib import Path





def 		_UpperCAmelCase   (							):
				from torch.utils.cpp_extension import load

				a_		:  Any											=      Path(_A      ).resolve().parent.parent.parent / "kernels" / "deformable_detr"
				a_		:  Optional[int]											=      [
				    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












'''simple docstring'''







from __future__ import annotations





def 		_UpperCAmelCase   (							__A							:   list[int]      ):
				a_		:  int											=      len(__A      ) // 2

				# choose the middle 3 elements
				a_		:  Dict											=      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()




