
"""simple docstring"""


import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import Audio, ClassLabel, Features
from .base import TaskTemplate







@dataclass(frozen=_lowercase     )
class 					lowerCAmelCase_					(   _lowercase     ):



						'''simple docstring'''


						_lowerCamelCase:     str   =     field(default='''audio-classification'''		,       metadata={'''include_in_asdict_even_if_is_default''': True}     )
						_lowerCamelCase:     ClassVar[Features]   =     Features({'''audio''': Audio()}     )
						_lowerCamelCase:     ClassVar[Features]   =     Features({'''labels''': ClassLabel}     )
						_lowerCamelCase:     str   =     "audio"
						_lowerCamelCase:     str   =     "labels"


						def     _SCREAMING_SNAKE_CASE   (			self  :   List[Any]	,A_  :   int   )  -> Tuple:
							if self.label_column not in features:
								raise ValueError(F'Column {self.label_column} is not present in features.'   )
							if not isinstance(features[self.label_column]	,A_   ):
								raise ValueError(F'Column {self.label_column} is not a ClassLabel.'   )
							A     = copy.deepcopy(self   )
							A     = self.label_schema.copy()
							A     = features[self.label_column]
							A     = label_schema
							return task_template




						@property
						def     _SCREAMING_SNAKE_CASE   (			self  :   Any   )  -> Dict[str, str]:
							return {
							    self.audio_column: "audio",
							    self.label_column: "labels",
							}




"""simple docstring"""






import os
from pathlib import Path




def 			snake_case		(		)						->				Tuple:
  from torch.utils.cpp_extension import load

  _snake_case   	=      Path(lowerCAmelCase_	).resolve().parent.parent.parent / '''kernels''' / '''deformable_detr'''
  _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'''  ,						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





