code: def __init__(self, in_size, hidden_size):
      super().__init__()
      self.layers = nn.ModuleList()
      self.layers.append(dglnn.SAGEConv(in_size, hidden_size, "mean"))
      self.layers.append(
          dglnn.SAGEConv(hidden_size, hidden_size, "mean")
      )
      self.layers.append(
          dglnn.SAGEConv(hidden_size, hidden_size, "mean")
      )
      self.hidden_size = hidden_size
      self.predictor = nn.Sequential(
          nn.Linear(hidden_size, hidden_size),
          nn.ReLU(),
          nn.Linear(hidden_size, hidden_size),
          nn.ReLU(),
          nn.Linear(hidden_size, 1),
      )
  
imports: import argparse
  import time
  from functools import partial
  import dgl.graphbolt
  import dgl.nn
  import torch
  import torch.nn
  import torch.nn.functional
  import tqdm
  from ogb.linkproppred import Evaluator
label_desc: Use image node_id 1 to create a new SAGE object from inherited base classes: nn with example: obj = SAGE(in_size, hidden_size)