code: def test_training_for_feature_set(self):
      model = self.create_image_model()
      feature_set = self.create_train_features_Set()
      training_dataset = TFDataset.from_feature_set(
          feature_set,
          features=(tf.float32, [224, 224, 3]),
          labels=(tf.int32, [1]),
          batch_size=8,
      )
      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 9 for calling the TestTFDataset obj's underlying member method code with example usage: obj.test_training_for_feature_set() without return types