docs: def _build_prior(self, unconstrained_tensor, constrained_tensor):
          """
          Build a tensorflow representation of the prior density.
          The log Jacobian is included.
          """
          if not misc.is_tensor(unconstrained_tensor):
              raise GPflowError("Unconstrained input must be a tensor.")
  
          if not misc.is_tensor(constrained_tensor):
              raise GPflowError("Constrained input must be a tensor.")
  
          prior_name = 'prior'
  
          if self.prior is None:
              return tf.constant(0.0, settings.float_type, name=prior_name)
  
          log_jacobian = self.transform.log_jacobian_tensor(unconstrained_tensor)
          logp_var = self.prior.logp(constrained_tensor)
          return tf.squeeze(tf.add(logp_var, log_jacobian, name=prior_name))