code: def __init__(
      self, num_features, hidden_channels, num_layers, num_classes
  ):
      super(SAGE, self).__init__()
      self.num_layers = num_layers
      self.convs = torch.nn.ModuleList()
      for i in range(num_layers):
          inc = outc = hidden_channels
          if i == 0:
              inc = num_features
          if i == num_layers - 1:
              outc = num_classes
          self.convs.append(SAGEConv(inc, outc))
  
imports: import os
  import random
  import numpy
  from tqdm import tqdm
  import pickle
  import torch
  import torch.nn.functional
  from torch_geometric.datasets import Planetoid
  import torch_geometric.transforms
  from torch_geometric.nn import GCNConv, GATConv, SAGEConv
  import logging
label_desc: Use image node_id 1 to create a new SAGE object from inherited base classes: torch.nn with example: obj = SAGE(num_features, hidden_channels, num_layers, num_classes)