






'''simple docstring'''





from typing import TYPE_CHECKING

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


snake_case__      :	List[Any]       	=      {
    """configuration_mobilenet_v2""": [
        """MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """MobileNetV2Config""",
        """MobileNetV2OnnxConfig""",
    ],
}

try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__      :	str       	=      ["""MobileNetV2FeatureExtractor"""]
 snake_case__      :	List[Any]       	=      ["""MobileNetV2ImageProcessor"""]


try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 snake_case__      :	Union[str, Any]       	=      [
     """MOBILENET_V2_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """MobileNetV2ForImageClassification""",
     """MobileNetV2ForSemanticSegmentation""",
     """MobileNetV2Model""",
     """MobileNetV2PreTrainedModel""",
     """load_tf_weights_in_mobilenet_v2""",
 ]


if TYPE_CHECKING:
 from .configuration_mobilenet_va import (
     MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP,
     MobileNetVaConfig,
     MobileNetVaOnnxConfig,
 )

 try:
  if not is_vision_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .feature_extraction_mobilenet_va import MobileNetVaFeatureExtractor
  from .image_processing_mobilenet_va import MobileNetVaImageProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_mobilenet_va import (
      MOBILENET_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
      MobileNetVaForImageClassification,
      MobileNetVaForSemanticSegmentation,
      MobileNetVaModel,
      MobileNetVaPreTrainedModel,
      load_tf_weights_in_mobilenet_va,
  )


else:
 import sys

 snake_case__      :	Tuple       	=      _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)













from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
 if not (is_transformers_available() and is_torch_available()):
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 from ...utils.dummy_torch_and_transformers_objects import (
     ImageTextPipelineOutput,
     UniDiffuserPipeline,
 )
else:
 from .modeling_text_decoder import UniDiffuserTextDecoder
 from .modeling_uvit import UniDiffuserModel, UTransformeraDModel
 from .pipeline_unidiffuser import ImageTextPipelineOutput, UniDiffuserPipeline





