code: def __init__(
      self, num_input=512, num_state=128, num_node=64, normalize=False
  ):
      super(GruModule, self).__init__()
      self.normalize = normalize
      self.num_state = num_state
      self.num_node = num_node
      self.reduction_dim = nn.Conv2D(
          num_input, num_state, kernel_size=1
      )
      self.projection_mat = nn.Conv2D(
          num_input, num_node, kernel_size=1
      )
      self.gcn = GCN(num_state=self.num_state, num_node=self.num_node)
      self.extend_dim = nn.Conv2D(
          self.num_state, num_input, kernel_size=1, bias_attr=False
      )
      self.extend_bn = layers.SyncBatchNorm(num_input, epsilon=1e-4)
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager
  from paddleseg.models import layers
  from paddleseg.utils import utils
label_desc: Use image node_id 1 to create a new GruModule object from inherited base classes: nn with example: obj = GruModule(num_input, num_state, num_node, normalize)