code: def forward(self, g):
      import dgl
  
      h = g.ndata[config.FEATURE]
      h = self.rgcn(g, h)
      with g.local_scope():  # create a local scope to hold onto hidden layer 'h'
          g.ndata["h"] = h
          # Calculate graph representation by average readout.
          hg = 0
          for ntype in g.ntypes:
              hg = hg + dgl.mean_nodes(g, "h", ntype=ntype)
          return self.classify(hg)
  
imports: from typing import TYPE_CHECKING, Any
  from .None import constants
  import logging
label_desc: Use image node_id 2 for calling the HeteroClassifier obj's underlying member method code with example usage: obj.forward(g) and returns: self