code: def forward(self, features, A):
      b, n, d = features.shape
      assert d == self.in_dim
      agg_feats = self.aggregator(features, A)
      cat_feats = paddle.concat([features, agg_feats], axis=2)
      out = paddle.einsum("bnd,df->bnf", cat_feats, self.weight)
      out = F.relu(out + self.bias)
      return out
  
file_path: PaddleOCR/ppocr/modeling/heads/gcn.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import paddle
  import paddle.nn
  import paddle.nn.functional
label_desc: Use image node_id 2 for calling the GraphConv obj's underlying member method code with example usage: obj.forward(features, A) and returns: out