code: def testModelNumClasses(self):
      # Builds a graph.
      class_variable_name = "class_variable_name"
      v0 = tf.Variable(
          [[1, 2, 3]], dtype=tf.int32, name="class_variable_name"
      )
      v1 = tf.Variable(
          [[[1], [2]], [[3], [4]], [[5], [6]]],
          dtype=tf.float32,
          name="v1",
      )
      init_all_op = tf.compat.v1.initialize_all_variables()
      save = tf.compat.v1.train.Saver(
          {class_variable_name: v0, "v1": v1}
      )
      save_path = test_utils.test_tmpfile("ckpt_for_debug_classes")
      with tf.compat.v1.Session() as sess:
          sess.run(init_all_op)
          # Saves a checkpoint.
          save.save(sess, save_path)
  
          # If you pass in the correct class_variable_name, you'll find the number
          # of classes.
          self.assertEqual(
              3,
              dv_utils.model_num_classes(
                  save_path, class_variable_name
              ),
          )
          # If the class variable name doesn't existin the checkpoint, return None.
          self.assertEqual(
              None,
              dv_utils.model_num_classes(save_path, "non-existent-var"),
          )
          # If the checkpoint doesn't exist, return none.
          self.assertIsNone(
              dv_utils.model_num_classes(None, class_variable_name)
          )
  
imports: from absl.testing import absltest
  from absl.testing import parameterized
  import tensorflow
  from deepvariant import dv_utils
  from tensorflow.python.platform import gfile
  from third_party.nucleus.io import tfrecord
  from third_party.nucleus.protos import variants_pb2
  from third_party.nucleus.testing import test_utils
  from tensorflow.core.example import example_pb2
label_desc: Use image node_id 3 for calling the TFUtilsTest obj's underlying member method code with example usage: obj.testModelNumClasses() without return types