code: def test_can_instantiate_and_compress(self):
      prior = deep_factorized.NoisyDeepFactorized(batch_shape=(4, 4))
      em = universal.UniversalBatchedEntropyModel(
          prior, coding_rank=3, compression=True
      )
      x = tf.random.stateless_normal((3, 8, 4, 4), seed=(0, 0))
      bitstring = em.compress(x)
      em(x)
      x_hat = em.decompress(bitstring, (8,))
      # Quantization noise should be between -.5 and .5
      u = x - x_hat
      self.assertAllLessEqual(tf.abs(u), 0.5)
  
imports: from absl.testing import parameterized
  import scipy.stats
  import tensorflow
  import tensorflow_probability
  from tensorflow_compression.python.distributions import deep_factorized
  from tensorflow_compression.python.distributions import uniform_noise
  from tensorflow_compression.python.entropy_models import universal
label_desc: Use image node_id 1 for calling the UniversalBatchedEntropyModelTest obj's underlying member method code with example usage: obj.test_can_instantiate_and_compress() without return types