from typing import TYPE_CHECKING

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


_SCREAMING_SNAKE_CASE     =     {"""configuration_detr""": ["""DETR_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DetrConfig""", """DetrOnnxConfig"""]}

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _SCREAMING_SNAKE_CASE     =     ["""DetrFeatureExtractor"""]
     _SCREAMING_SNAKE_CASE     =     ["""DetrImageProcessor"""]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _SCREAMING_SNAKE_CASE     =     [
         """DETR_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """DetrForObjectDetection""",
         """DetrForSegmentation""",
         """DetrModel""",
         """DetrPreTrainedModel""",
     ]


if TYPE_CHECKING:
     from .configuration_detr import DETR_PRETRAINED_CONFIG_ARCHIVE_MAP, DetrConfig, DetrOnnxConfig

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .feature_extraction_detr import DetrFeatureExtractor
          from .image_processing_detr import DetrImageProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_detr import (
              DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
              DetrForObjectDetection,
              DetrForSegmentation,
              DetrModel,
              DetrPreTrainedModel,
          )

else:
     import sys

     _SCREAMING_SNAKE_CASE     =     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



from ..utils import DummyObject, requires_backends
class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Tuple            =				["torch", "transformers", "invisible_watermark"]





							def __init__(					self    :  Any	,					*_UpperCAmelCase    :  Optional[Any]	,					**_UpperCAmelCase    :  List[str]							)		->						Tuple:



											"""simple docstring"""


											requires_backends(self	,					['torch', 'transformers', 'invisible_watermark']							)





							@classmethod
							def      a__					(					cls    :  str	,					*_UpperCAmelCase    :  List[str]	,					**_UpperCAmelCase    :  Optional[Any]							)		->						Union[str, Any]:



											"""simple docstring"""


											requires_backends(cls	,					['torch', 'transformers', 'invisible_watermark']							)





							@classmethod
							def      a__					(					cls    :  List[Any]	,					*_UpperCAmelCase    :  List[Any]	,					**_UpperCAmelCase    :  Union[str, Any]							)		->						str:



											"""simple docstring"""


											requires_backends(cls	,					['torch', 'transformers', 'invisible_watermark']							)






class       A__  (		metaclass=lowerCAmelCase__							):
							lowerCAmelCase__						:		Tuple            =				["torch", "transformers", "invisible_watermark"]





							def __init__(					self    :  Dict	,					*_UpperCAmelCase    :  Optional[int]	,					**_UpperCAmelCase    :  Any							)		->						Union[str, Any]:



											"""simple docstring"""


											requires_backends(self	,					['torch', 'transformers', 'invisible_watermark']							)





							@classmethod
							def      a__					(					cls    :  List[str]	,					*_UpperCAmelCase    :  Union[str, Any]	,					**_UpperCAmelCase    :  Optional[Any]							)		->						Optional[int]:



											"""simple docstring"""


											requires_backends(cls	,					['torch', 'transformers', 'invisible_watermark']							)





							@classmethod
							def      a__					(					cls    :  Tuple	,					*_UpperCAmelCase    :  List[Any]	,					**_UpperCAmelCase    :  Tuple							)		->						Any:



											"""simple docstring"""


											requires_backends(cls	,					['torch', 'transformers', 'invisible_watermark']							)





