code: def __init__(
      self,
      in_dim,
      num_classes,
      hid_dim=64,
      edges=None,
      num_layers=2,
      activation=None,
      step_size=0.02,
  ):
      super(CAREGNN, self).__init__()
      self.in_dim = in_dim
      self.hid_dim = hid_dim
      self.num_classes = num_classes
      self.edges = edges
      self.num_layers = num_layers
      self.activation = activation
      self.step_size = step_size
  
      self.layers = nn.ModuleList()
  
      if self.num_layers == 1:
          # Single layer
          self.layers.append(
              CAREConv(
                  self.in_dim,
                  self.num_classes,
                  self.num_classes,
                  self.edges,
                  activation=self.activation,
                  step_size=self.step_size,
              )
          )
  
      else:
          # Input layer
          self.layers.append(
              CAREConv(
                  self.in_dim,
                  self.hid_dim,
                  self.num_classes,
                  self.edges,
                  activation=self.activation,
                  step_size=self.step_size,
              )
          )
  
          # Hidden layers with n - 2 layers
          for i in range(self.num_layers - 2):
              self.layers.append(
                  CAREConv(
                      self.hid_dim,
                      self.hid_dim,
                      self.num_classes,
                      self.edges,
                      activation=self.activation,
                      step_size=self.step_size,
                  )
              )
  
          # Output layer
          self.layers.append(
              CAREConv(
                  self.hid_dim,
                  self.num_classes,
                  self.num_classes,
                  self.edges,
                  activation=self.activation,
                  step_size=self.step_size,
              )
          )
  
imports: import dgl
  import dgl.function
  import numpy
  import torch
  import torch.nn
label_desc: Use image node_id 1 to create a new CAREGNN object from inherited base classes: nn with example: obj = CAREGNN(in_dim, num_classes, hid_dim, edges, num_layers, activation, step_size)