






"""simple docstring"""



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


_UpperCamelCase		:  Optional[Any]						=		{
    'configuration_conditional_detr': [
        'CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'ConditionalDetrConfig',
        'ConditionalDetrOnnxConfig',
    ]
}

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _UpperCamelCase		:  List[str]						=		['ConditionalDetrFeatureExtractor']
    _UpperCamelCase		:  List[str]						=		['ConditionalDetrImageProcessor']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _UpperCamelCase		:  str						=		[
        'CONDITIONAL_DETR_PRETRAINED_MODEL_ARCHIVE_LIST',
        'ConditionalDetrForObjectDetection',
        'ConditionalDetrForSegmentation',
        'ConditionalDetrModel',
        'ConditionalDetrPreTrainedModel',
    ]


if TYPE_CHECKING:
    from .configuration_conditional_detr import (
        CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP,
        ConditionalDetrConfig,
        ConditionalDetrOnnxConfig,
    )

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_conditional_detr import ConditionalDetrFeatureExtractor
        from .image_processing_conditional_detr import ConditionalDetrImageProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_conditional_detr import (
            CONDITIONAL_DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
            ConditionalDetrForObjectDetection,
            ConditionalDetrForSegmentation,
            ConditionalDetrModel,
            ConditionalDetrPreTrainedModel,
        )

else:
    import sys

    _UpperCamelCase		:  Tuple						=		_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)










"""simple docstring"""



def 						_SCREAMING_SNAKE_CASE (    __snake_case			:  int = 4_00_00_00    ):





  '''simple docstring'''





  lowercase							    =       []
  lowercase    ,     lowercase							    =       0, 1
  while b <= n:
    if b % 2 == 0:
      even_fibs.append(__snake_case    )
    lowercase    ,     lowercase							    =       b, a + b
  return sum(__snake_case    )


if __name__ == "__main__":
    print(F'''{solution() = }''')


