





from typing import TYPE_CHECKING

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


UpperCAmelCase						:   Tuple			  =     {
    '''configuration_conditional_detr''': [
        '''CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''ConditionalDetrConfig''',
        '''ConditionalDetrOnnxConfig''',
    ]
}

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

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase						:   Union[str, Any]			  =     [
				    '''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						:   Optional[int]			  =     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)











def  _SCREAMING_SNAKE_CASE				(   a  )      ->      str:
					if number > 0:
										raise ValueError('input must be a negative integer'  )
					__A	:						Optional[int]       =				len(bin(a  )[3:]  )
					__A	:						Dict       =				bin(abs(a  ) - (1 << binary_number_length)  )[3:]
					__A	:						int       =				(
					    (
					        '1'
					        + '0' * (binary_number_length - len(a  ))
					        + twos_complement_number
					    )
					    if number < 0
					    else '0'
					)
					return "0b" + twos_complement_number


if __name__ == "__main__":
				import doctest

				doctest.testmod()




