class_docstr: A BNN that always predicts 1.
class_docstr_tok: ["A","BNN","that","always","predicts","1","."]
code: def __call__(self, inputs, deterministic=True):
      out_shape = inputs.shape[:-1] + (
          self.likelihood_model.num_outputs(),
      )
      return jnp.ones(shape=out_shape)
  
imports: from flax import linen
  from flax.linen import initializers
  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 tensorflow_probability.substrates.jax.distributions import student_t
  from tensorflow_probability.substrates.jax.distributions import uniform
label_desc: Use image node_id 2 for calling the IdentityBNN obj's underlying member method code with example usage: obj.__call__(inputs, deterministic) and returns: jnp