code: def __init__(
      self, input_channels, hidden_channels, output_channels, num_layers
  ):
      super(NGNN_GCNConv, self).__init__()
      self.conv = GraphConv(input_channels, hidden_channels)
      self.fc = Linear(hidden_channels, hidden_channels)
      self.fc2 = Linear(hidden_channels, output_channels)
      self.num_layers = num_layers
  
file_path: dgl/examples/pytorch/ogb/ngnn_seal/models.py
imports: import math
  import torch
  import torch.nn.functional
  from dgl.nn import GraphConv, SortPooling
  from torch.nn import Conv1d, Embedding, Linear, MaxPool1d, ModuleList
label_desc: Use image node_id 1 to create a new NGNN_GCNConv object from inherited base classes: torch.nn with example: obj = NGNN_GCNConv(input_channels, hidden_channels, output_channels, num_layers)