code: def __init__(
      self, in_channels, hidden_channels, out_channels, num_layers
  ):
      super().__init__()
  
      self.convs = torch.nn.ModuleList()
      self.convs.append(CuGraphSAGEConv(in_channels, hidden_channels))
      for _ in range(num_layers - 1):
          conv = CuGraphSAGEConv(hidden_channels, hidden_channels)
          self.convs.append(conv)
  
      self.lin = nn.Linear(hidden_channels, out_channels)
  
imports: from ogb.nodeproppred import NodePropPredDataset
  import time
  import argparse
  import gc
  import torch
  import numpy
  from torch_geometric.nn import CuGraphSAGEConv
  import torch.nn
  import torch.nn.functional
  import torch.distributed
  import torch.multiprocessing
  from torch.nn.parallel import DistributedDataParallel
  from typing import List
label_desc: Use image node_id 1 to create a new CuGraphSAGE object from inherited base classes: nn with example: obj = CuGraphSAGE(in_channels, hidden_channels, out_channels, num_layers)