code: def test_debatchify_real_weighted_sum(self):
      k = operators.WeightedSum(
          bnns=(
              kernels.OneLayerBNN(width=50),
              kernels.OneLayerBNN(width=50),
          )
      )
      num_particles = 10
      init_seed = jax.random.PRNGKey(0)
  
      def _init(seed):
          return k.init(seed, jnp.ones(5))
  
      params = jax.vmap(_init)(
          jax.random.split(init_seed, num_particles)
      )
      debatched_params = training_util.debatchify_params(params)
      self.assertLen(debatched_params, 10)
      lp = k.log_prior(debatched_params[0])
      lp2 = k.log_prior(params)
      self.assertLess(lp2, lp)
  
imports: import chex
  import jax
  import jax.numpy
  import numpy
  from tensorflow_probability.python.experimental.autobnn import kernels
  from tensorflow_probability.python.experimental.autobnn import operators
  from tensorflow_probability.python.experimental.autobnn import training_util
  from tensorflow_probability.python.experimental.autobnn import util
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 11 for calling the TrainingUtilTest obj's underlying member method code with example usage: obj.test_debatchify_real_weighted_sum() and returns: k