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, aggr="mean")
      )
      for _ in range(num_layers - 2):
          conv = CuGraphSAGEConv(
              hidden_channels, hidden_channels, aggr="mean"
          )
          self.convs.append(conv)
  
      self.convs.append(
          CuGraphSAGEConv(hidden_channels, out_channels, aggr="mean")
      )
  
      self._trim = TrimToLayer()
  
file_path: cugraph/benchmarks/cugraph/standalone/bulk_sampling/models/pyg/models_cugraph_pyg.py
imports: import torch
  from cugraph_pyg.nn.conv import SAGEConv
  import torch.nn
  import torch.nn.functional
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)