code: def logp_norm(self):
      sized_symbolic_logp = self.approx.sized_symbolic_logp
      if self.use_histogram:
          sized_symbolic_logp = graph_replace(
              sized_symbolic_logp,
              dict(
                  zip(
                      self.approx.symbolic_randoms,
                      self.approx.collect("histogram"),
                  )
              ),
              strict=False,
          )
      return (
          sized_symbolic_logp
          / self.approx.symbolic_normalizing_constant
      )
  
file_path: pymc/pymc/variational/stein.py
imports: import pytensor.tensor
  from pytensor.graph.replace import graph_replace
  from pymc.pytensorf import floatX
  from pymc.util import WithMemoization, locally_cachedmethod
  from pymc.variational.opvi import node_property
  from pymc.variational.test_functions import rbf
label_desc: Use image node_id 10 for calling the Stein obj's underlying member method code with example usage: obj.logp_norm() and returns: unknown