


from typing import TYPE_CHECKING

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


UpperCAmelCase__     			=							{
    '''configuration_deformable_detr''': ['''DEFORMABLE_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DeformableDetrConfig'''],
}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase__     			=							['''DeformableDetrFeatureExtractor''']
  UpperCAmelCase__     			=							['''DeformableDetrImageProcessor''']

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase__     			=							[
      '''DEFORMABLE_DETR_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''DeformableDetrForObjectDetection''',
      '''DeformableDetrModel''',
      '''DeformableDetrPreTrainedModel''',
  ]


if TYPE_CHECKING:
  from .configuration_deformable_detr import DEFORMABLE_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP, DeformableDetrConfig

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_deformable_detr import DeformableDetrFeatureExtractor
    from .image_processing_deformable_detr import DeformableDetrImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_deformable_detr import (
        DEFORMABLE_DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
        DeformableDetrForObjectDetection,
        DeformableDetrModel,
        DeformableDetrPreTrainedModel,
    )

else:
  import sys

  UpperCAmelCase__     			=							_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





from ..utils import DummyObject, requires_backends







class    lowerCamelCase__     ( metaclass=lowerCAmelCase):
     SCREAMING_SNAKE_CASE__       =    ['''tensorflow_text''']





     def __init__(self	,  *UpperCAmelCase	,  **UpperCAmelCase )  ->     Any:
      requires_backends(self	,  ['''tensorflow_text'''] )

