code: def __init__(self, feat_len):
      super(GCN, self).__init__()
      self.bn0 = BatchNorm1D(feat_len, affine=False)
      self.conv1 = GraphConv(feat_len, 512)
      self.conv2 = GraphConv(512, 256)
      self.conv3 = GraphConv(256, 128)
      self.conv4 = GraphConv(128, 64)
      self.classifier = nn.Sequential(
          nn.Linear(64, 32), nn.PReLU(32), nn.Linear(32, 2)
      )
  
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 GCN object from inherited base classes: nn with example: obj = GCN(feat_len)