code: def test_degenerate_scalar_mask(self):
      d0 = masked.Masked(
          normal.Normal(0.0, 1.0),
          validity_mask=False,
          validate_args=True,
      )
      d1 = masked.Masked(
          normal.Normal(0.0, 1.0),
          validity_mask=True,
          validate_args=True,
      )
      stream = test_util.test_seed_stream()
      self.assertAllEqual(
          d0.sample(seed=stream()), d0.sample(seed=stream())
      )
      self.assertNotAllEqual(
          d1.sample(seed=stream()), d1.sample(seed=stream())
      )
      self.assertAllEqual(0.0, d0.log_prob(123.0))
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.distributions import gamma
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import log_prob_ratio
  from tensorflow_probability.python.distributions import lognormal
  from tensorflow_probability.python.distributions import masked
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import relaxed_onehot_categorical
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 5 for calling the MaskedTest obj's underlying member method code with example usage: obj.test_degenerate_scalar_mask() without return types