





'''simple docstring'''
import os
from pathlib import Path
def 				lowercase__   (   ) ->      str:



       """simple docstring"""






       from torch.utils.cpp_extension import load

       __UpperCamelCase       =  Path(__lowercase     ).resolve().parent.parent.parent / 'kernels' / 'deformable_detr'
       __UpperCamelCase       =  [
           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'				,  __lowercase				,  with_cuda=__lowercase				,  extra_include_paths=[str(__lowercase     )]				,  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 typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a__							:							List[Any] ={
    '''configuration_timesformer''': ['''TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TimesformerConfig'''],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    a__							:							Optional[int] =[
        '''TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''TimesformerModel''',
        '''TimesformerForVideoClassification''',
        '''TimesformerPreTrainedModel''',
    ]

if TYPE_CHECKING:
    from .configuration_timesformer import TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, TimesformerConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_timesformer import (
            TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
            TimesformerForVideoClassification,
            TimesformerModel,
            TimesformerPreTrainedModel,
        )

else:
    import sys

    a__							:							Optional[int] =_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
