code: def forward(self, graph):
      h = graph.ndata["feat"]
      h = self.dropout(h)
      for i, conv in enumerate(self.convs):
          h = conv(graph, h)
          if i != self.num_layers - 1:
              h = h.relu()
              h = self.dropout(h)
      return F.log_softmax(h, dim=-1)
  
imports: import numpy
  from tqdm import tqdm
  import pickle
  import torch
  import torch.nn.functional
  from dgl.data import CoraGraphDataset, PubmedGraphDataset, CiteseerGraphDataset
  from dgl.nn.pytorch import GraphConv, GATConv, SAGEConv
  import logging
label_desc: Use image node_id 2 for calling the SAGE obj's underlying member method code with example usage: obj.forward(graph) and returns: F