






from ..utils import DummyObject, requires_backends
class    a   (			metaclass=lowercase__       ):



      """simple docstring"""


      a  :			Dict								=     ['torch', 'transformers', 'k_diffusion']
      def __init__(				self :      Dict		,				*__lowercase :      Optional[Any]		,				**__lowercase :      Optional[Any] )							->				Tuple:
        requires_backends(self		,				["""torch""", """transformers""", """k_diffusion"""] )
      @classmethod
      def      UpperCAmelCase				(				cls :      List[str]		,				*__lowercase :      Optional[Any]		,				**__lowercase :      List[str] )							->				Optional[Any]:
        requires_backends(cls		,				["""torch""", """transformers""", """k_diffusion"""] )




      @classmethod
      def      UpperCAmelCase				(				cls :      Dict		,				*__lowercase :      Optional[Any]		,				**__lowercase :      int )							->				Optional[int]:
        requires_backends(cls		,				["""torch""", """transformers""", """k_diffusion"""] )










from typing import TYPE_CHECKING

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


a		:	Any      					=			{
    "configuration_deta": ["DETA_PRETRAINED_CONFIG_ARCHIVE_MAP", "DetaConfig"],
}

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a		:	Optional[int]      					=			["DetaImageProcessor"]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a		:	Tuple      					=			[
           "DETA_PRETRAINED_MODEL_ARCHIVE_LIST",
           "DetaForObjectDetection",
           "DetaModel",
           "DetaPreTrainedModel",
       ]


if TYPE_CHECKING:
       from .configuration_deta import DETA_PRETRAINED_CONFIG_ARCHIVE_MAP, DetaConfig

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .image_processing_deta import DetaImageProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_deta import (
                  DETA_PRETRAINED_MODEL_ARCHIVE_LIST,
                  DetaForObjectDetection,
                  DetaModel,
                  DetaPreTrainedModel,
              )

else:
       import sys

       a		:	Any      					=			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


