code: def test_inflated_continuous_log_prob(self):
      spike_and_slab = inflated.Inflated(
          normal.Normal(loc=1.0, scale=2.0), inflated_loc_probs=0.1
      )
      self.assertEqual(
          self.evaluate(tf.math.log(0.1)),
          self.evaluate(spike_and_slab.log_prob(0.0)),
      )
      self.assertNear(
          self.evaluate(
              tf.math.log(0.9)
              + normal.Normal(loc=1.0, scale=2.0).log_prob(2.0)
          ),
          self.evaluate(spike_and_slab.log_prob(2.0)),
          1e-6,
      )
  
file_path: probability/tensorflow_probability/python/distributions/inflated_test.py
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import gamma
  from tensorflow_probability.python.distributions import inflated
  from tensorflow_probability.python.distributions import lognormal
  from tensorflow_probability.python.distributions import negative_binomial
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.experimental.util import trainable
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 3 for calling the DistributionsTest obj's underlying member method code with example usage: obj.test_inflated_continuous_log_prob() without return types