class_docstr: spatial feature branch
class_docstr_tok: ["spatial","feature","branch"]
code: def forward(self, edges):
      feat = nd.concat(
          edges.src["pred_bbox"],
          edges.dst["pred_bbox"],
          edges.data["rel_bbox"],
          edges.data["pred_bbox_additional"],
      )
      out = self.mlp(feat)
      return {"spatial": out}
  
imports: import pickle
  import dgl
  import gluoncv
  import mxnet
  import numpy
  from dgl.nn.mxnet import GraphConv
  from dgl.utils import toindex
  from mxnet import nd
  from mxnet.gluon import nn
label_desc: Use image node_id 2 for calling the EdgeSpatial obj's underlying member method code with example usage: obj.forward(edges) and returns: dict