code: def test_training_for_imageset(self):
      model = self.create_image_model()
      image_set = self.create_image_set(with_label=True)
      training_dataset = TFDataset.from_image_set(
          image_set,
          image=(tf.float32, [224, 224, 3]),
          label=(tf.int32, [1]),
          batch_size=4,
      )
      model.fit(training_dataset)
  
imports: import pytest
  from pyspark.ml.linalg import DenseVector
  from zoo.feature.common import ChainedPreprocessing, FeatureSet
  from zoo.feature.image import *
  from test.zoo.pipeline.utils.test_utils import ZooTestCase
  from zoo.pipeline.api.keras.optimizers import Adam
  from zoo.tfpark import TFNet, TFOptimizer
  import tensorflow
  import numpy
  import os
  from zoo.tfpark import KerasModel, TFDataset
label_desc: Use image node_id 8 for calling the TestTFDataset obj's underlying member method code with example usage: obj.test_training_for_imageset() without return types