


'''simple docstring'''

import os
from pathlib import Path






def __UpperCamelCase   (			)      ->     Optional[Any]:







					'''simple docstring'''






					from torch.utils.cpp_extension import load

					_a						=		Path(__lowerCamelCase				).resolve().parent.parent.parent / "kernels" / "deformable_detr"
					_a						=		[
					    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"      ,  __lowerCamelCase      ,  with_cuda=__lowerCamelCase      ,  extra_include_paths=[str(__lowerCamelCase				)]      ,  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 collections import defaultdict

from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst






def __UpperCamelCase   (			)      ->     Tuple:







     '''simple docstring'''






     _a			,			_a						=		9, 14  # noqa: F841
     _a						=		[
         [0, 1, 4],
         [0, 7, 8],
         [1, 2, 8],
         [7, 8, 7],
         [7, 6, 1],
         [2, 8, 2],
         [8, 6, 6],
         [2, 3, 7],
         [2, 5, 4],
         [6, 5, 2],
         [3, 5, 14],
         [3, 4, 9],
         [5, 4, 10],
         [1, 7, 11],
     ]

     _a						=		defaultdict(__lowerCamelCase				)
     for nodea, nodea, cost in edges:
          adjancency[nodea].append([nodea, cost]				)
          adjancency[nodea].append([nodea, cost]				)

     _a						=		mst(__lowerCamelCase				)

     _a						=		[
         [7, 6, 1],
         [2, 8, 2],
         [6, 5, 2],
         [0, 1, 4],
         [2, 5, 4],
         [2, 3, 7],
         [0, 7, 8],
         [3, 4, 9],
     ]

     for answer in expected:
          _a						=		tuple(answer[:2]				)
          _a						=		tuple(edge[::-1]				)
          assert edge in result or reverse in result

