code: def testSequential(self):
      dist = jdlayers.Sequential(
          jdlayers.Affine(5, 3),
          tf.nn.softplus,
      )
      layer = dist.sample(
          seed=test_util.test_seed(sampler_type="stateless")
      )
      x = tf.ones([4, 3])
      y = layer(x)
      self.assertAllEqual([4, 5], y.shape)
      self.assertAllTrue(y > 0.0)
      self.assertAllEqual([], dist.log_prob(layer).shape)
  
imports: from absl.testing import parameterized
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import chain
  from tensorflow_probability.python.bijectors import real_nvp
  from tensorflow_probability.python.bijectors import scale
  from tensorflow_probability.python.bijectors import shift
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.distributions import joint_distribution_coroutine
  from tensorflow_probability.python.distributions import lognormal
  from tensorflow_probability.python.experimental.joint_distribution_layers import layers
  from tensorflow_probability.python.internal import custom_gradient
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 9 for calling the _JDLayersTestBase obj's underlying member method code with example usage: obj.testSequential() without return types