code: def testCheckpoint(self):
      model = self._define_model(
          "sequential", self.data_dim, self.num_hidden
      )
      self.evaluate([v.initializer for v in model.weights])
      checkpoint = tf.train.Checkpoint(model=model)
      model_dir = tempfile.mkdtemp()
      checkpoint.save(file_prefix=model_dir)
  
imports: import tempfile
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.internal import tf_keras
  from tensorflow_probability.python.layers import weight_norm
label_desc: Use image node_id 14 for calling the WeightNormTest obj's underlying member method code with example usage: obj.testCheckpoint() without return types