code: def testNormalWithSoftplusScale(self):
      mu = array_ops.zeros((10, 3))
      rho = array_ops.ones((10, 3)) * -2.0
      normal = normal_lib.NormalWithSoftplusScale(loc=mu, scale=rho)
      self.assertAllEqual(self.evaluate(mu), self.evaluate(normal.loc))
      self.assertAllEqual(
          self.evaluate(nn_ops.softplus(rho)),
          self.evaluate(normal.scale),
      )
  
imports: import importlib
  import math
  import numpy
  from tensorflow.python.eager import backprop
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gradients_impl
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.ops.distributions import kullback_leibler
  from tensorflow.python.ops.distributions import normal
  from tensorflow.python.platform import test
  from tensorflow.python.platform import tf_logging
label_desc: Use image node_id 8 for calling the NormalTest obj's underlying member method code with example usage: obj.testNormalWithSoftplusScale() without return types