code: def dlogp(self):
      logp = self.logp_norm.sum()
      grad = pt.grad(logp, self.approx_symbolic_matrices)
  
      def flatten2(tensor):
          return tensor.flatten(2)
  
      return pt.concatenate(list(map(flatten2, grad)), -1)
  
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 4 for calling the Stein obj's underlying member method code with example usage: obj.dlogp() and returns: pt, tensor