code: def __init__(self, in_dim, out_dim):
      super().__init__()
      self.in_dim = in_dim
      self.out_dim = out_dim
      self.weight = self.create_parameter(
          [in_dim * 2, out_dim],
          default_initializer=nn.initializer.XavierUniform(),
      )
      self.bias = self.create_parameter(
          [out_dim],
          is_bias=True,
          default_initializer=nn.initializer.Assign([0] * out_dim),
      )
  
      self.aggregator = MeanAggregator()
  
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 1 to create a new GraphConv object from inherited base classes: nn with example: obj = GraphConv(in_dim, out_dim)