code: def test_predict_for_imageset(self):
      model = self.create_image_model()
      image_set = self.create_image_set(with_label=False)
  
      predict_dataset = TFDataset.from_image_set(
          image_set,
          image=(tf.float32, [224, 224, 3]),
          batch_per_thread=1,
      )
      results = model.predict(predict_dataset).get_predict().collect()
      assert all(r[1] is not None for r in results)
  
imports: import pytest
  from pyspark.ml.linalg import DenseVector
  from bigdl.dllib.feature.common import ChainedPreprocessing, FeatureSet
  from bigdl.dllib.feature.image import *
  from bigdl.orca.test_zoo_utils import ZooTestCase
  from bigdl.dllib.keras.optimizers import Adam
  from bigdl.orca.tfpark import TFNet, TFOptimizer
  import tensorflow
  import numpy
  import os
  from bigdl.orca.tfpark import KerasModel, TFDataset
label_desc: Use image node_id 12 for calling the TestTFDataset obj's underlying member method code with example usage: obj.test_predict_for_imageset() without return types