



import os
from pathlib import Path

def 	SCREAMING_SNAKE_CASE_							(	)  ->     Dict:
   from torch.utils.cpp_extension import load

   _A      =       Path(_snake_case				).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'''	,   _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'''

def    a__							(							lowercase   :	str )						->						int:





     """simple docstring"""

     assert column_title.isupper()
     _UpperCamelCase							       =			0
     _UpperCamelCase							       =			len(lowercase ) - 1
     _UpperCamelCase							       =			0

     while index >= 0:
          _UpperCamelCase							       =			(ord(column_title[index] ) - 64) * pow(26,   lowercase )
          answer += value
          power += 1
          index -= 1

     return answer


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

   testmod()



