code: def test_laplace_tail_mass_for_small_inputs(self):
      prior = deep_factorized.NoisyDeepFactorized(batch_shape=(1,))
      em1 = universal.UniversalBatchedEntropyModel(
          prior, coding_rank=1, compression=True, laplace_tail_mass=1e-3
      )
      em2 = universal.UniversalBatchedEntropyModel(
          prior, coding_rank=1, compression=True
      )
      x = tf.linspace(-10.0, 10.0, 50)
      _, bits1 = em1(x[..., None])
      _, bits2 = em2(x[..., None])
      self.assertAllClose(bits1, bits2, rtol=0.01, atol=0.05)
  
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 5 for calling the UniversalBatchedEntropyModelTest obj's underlying member method code with example usage: obj.test_laplace_tail_mass_for_small_inputs() without return types