code: def setUp(self):
      super(LogNormalSoftplusTest, self).setUp()
      self.dtype = np.float32
      s = 0.75
      self.model = family.LogNormalSoftplus(s)
      self.expected = family.CustomExponentialFamily(
          lambda mean: lognormal.LogNormal(
              tf.math.log(mean) - 0.5 * s**2, s
          ),
          tf.nn.softplus,
      )
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import bernoulli
  from tensorflow_probability.python.distributions import binomial
  from tensorflow_probability.python.distributions import gamma
  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.distributions import poisson
  from tensorflow_probability.python.glm import family
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 1 for calling the LogNormalSoftplusTest obj's underlying member method code with example usage: obj.setUp() without return types