code: def postprocess(self, outputs: Sequence[Any]):
      outputs = tuple(outputs.values())
      # todo: we should perform dtype conversion based on the
      # dtype of the outputs of the original keras model
      outputs = convert_all(outputs, types="tf", dtypes=tf.float32)
      if len(outputs) == 1:
          outputs = outputs[0]
      return outputs
  
imports: import os
  from bigdl.nano.utils.common import SafePickle
  from pathlib import Path
  from typing import Sequence, Any, Union, Dict
  from tempfile import TemporaryDirectory
  import numpy
  import tensorflow
  from bigdl.nano.utils.common import invalidInputError
  from bigdl.nano.utils.tf import try_fake_inference
  from bigdl.nano.utils.tf import convert_all, tensors_to_numpy
  from bigdl.nano.tf.model import KerasOptimizedModel
  from ..core.model import OpenVINOModel
  from ..core.utils import save
  from .utils import export
  from .dataloader import KerasOpenVINODataLoader
  from .metric import KerasOpenVINOMetric
label_desc: Use image node_id 4 for calling the KerasOpenVINOModel obj's underlying member method code with example usage: obj.postprocess(outputs) and returns: outputs