code: def convert_output(output):
      if type(output) is JTensor:
          return output.to_ndarray()
      elif len(output) == 1:
          return KerasNet.convert_output(output[0])
      else:
          return [KerasNet.convert_output(x) for x in output]
  
imports: import zoo.pipeline.api.autograd
  from zoo.feature.image import ImageSet
  from zoo.feature.text import TextSet
  from zoo.feature.common import FeatureSet
  from zoo.pipeline.api.keras.base import ZooKerasLayer
  from zoo.pipeline.api.keras.utils import *
  from bigdl.nn.layer import Layer
  from zoo.common.utils import callZooFunc
label_desc: Use image node_id 15 for calling the KerasNet obj's underlying member method code with example usage: obj.convert_output(output) and returns: output, KerasNet, unknown