code: def __init__(self, in_channels, hidden_channels):
      super().__init__()
      self.convs = torch.nn.ModuleList(
          [
              SAGEConv(in_channels, hidden_channels),
              SAGEConv(hidden_channels, hidden_channels),
              SAGEConv(hidden_channels, hidden_channels),
          ]
      )
  
      self.activations = torch.nn.ModuleList()
      self.activations.extend(
          [
              torch.nn.PReLU(hidden_channels),
              torch.nn.PReLU(hidden_channels),
              torch.nn.PReLU(hidden_channels),
          ]
      )
  
file_path: pytorch_geometric/examples/infomax_inductive.py
imports: import os.path
  import torch
  from tqdm import tqdm
  from torch_geometric.datasets import Reddit
  from torch_geometric.loader import NeighborLoader
  from torch_geometric.nn import DeepGraphInfomax, SAGEConv
label_desc: Use image node_id 1 to create a new Encoder object from inherited base classes: torch.nn with example: obj = Encoder(in_channels, hidden_channels)