

'''simple docstring'''

import os
from pathlib import Path




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

 UpperCAmelCase       :	Dict											= Path(__lowercase	).resolve().parent.parent.parent / 'kernels' / 'deformable_detr'
 UpperCAmelCase       :	List[Any]											= [
     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__)
