code: def __init__(self, in_size, hidden_size, out_size):
      super().__init__()
      self.layers = nn.ModuleList()
      # Three-layer GraphSAGE-mean.
      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, out_size, "mean"))
      self.dropout = nn.Dropout(0.5)
      self.hidden_size = hidden_size
      self.out_size = out_size
      # Set the dtype for the layers manually.
      self.set_layer_dtype(torch.float32)
  
imports: import argparse
  import time
  import dgl.graphbolt
  import dgl.nn
  import torch
  import torch.nn
  import torch.nn.functional
  import torchmetrics.functional
  from tqdm import tqdm
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, out_size)