code: def distributions(self):
      return super().distributions() | {
          "dense": {
              "kernel": normal_lib.Normal(loc=0, scale=1),
              "bias": normal_lib.Normal(loc=0, scale=1),
          },
          "amplitude": lognormal_lib.LogNormal(loc=0, scale=1),
      }
  
file_path: probability/tensorflow_probability/python/experimental/autobnn/bnn_test.py
imports: from flax import linen
  import jax
  import jax.numpy
  from tensorflow_probability.python.experimental.autobnn import bnn
  from tensorflow_probability.substrates.jax.distributions import lognormal
  from tensorflow_probability.substrates.jax.distributions import normal
  from absl.testing import absltest
label_desc: Use image node_id 1 for calling the MyBNN obj's underlying member method code with example usage: obj.distributions() and returns: unknown