



'''simple docstring'''



from typing import TYPE_CHECKING

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


_lowercase       :						Tuple						={
    "configuration_deformable_detr": ["DEFORMABLE_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP", "DeformableDetrConfig"],
}

try:
				if not is_vision_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_lowercase       :						Optional[int]						=["DeformableDetrFeatureExtractor"]
				_lowercase       :						List[Any]						=["DeformableDetrImageProcessor"]

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_lowercase       :						Dict						=[
				    "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

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









from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCAmelCase :				List[Any]							={"""configuration_qdqbert""": ["""QDQBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """QDQBertConfig"""]}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase :				Dict							=[
	    """QDQBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """QDQBertForMaskedLM""",
	    """QDQBertForMultipleChoice""",
	    """QDQBertForNextSentencePrediction""",
	    """QDQBertForQuestionAnswering""",
	    """QDQBertForSequenceClassification""",
	    """QDQBertForTokenClassification""",
	    """QDQBertLayer""",
	    """QDQBertLMHeadModel""",
	    """QDQBertModel""",
	    """QDQBertPreTrainedModel""",
	    """load_tf_weights_in_qdqbert""",
	]


if TYPE_CHECKING:
	from .configuration_qdqbert import QDQBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, QDQBertConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_qdqbert import (
		    QDQBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    QDQBertForMaskedLM,
		    QDQBertForMultipleChoice,
		    QDQBertForNextSentencePrediction,
		    QDQBertForQuestionAnswering,
		    QDQBertForSequenceClassification,
		    QDQBertForTokenClassification,
		    QDQBertLayer,
		    QDQBertLMHeadModel,
		    QDQBertModel,
		    QDQBertPreTrainedModel,
		    load_tf_weights_in_qdqbert,
		)


else:
	import sys

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