code: def __init__(
      self,
      in_dim,
      num_layers,
      hidden,
      conv_type=ConvType.GEMB,
      use_virtual_node=False,
      node_update_type=NodeUpdateType.RESIDUAL,
      layer_norm=False,
  ):
      super(AugEncoder, self).__init__()
      self.embedding = torch.nn.Sequential(
          torch.nn.Linear(in_dim, hidden)
      )
      self.convs = torch.nn.ModuleList()
      for _ in range(num_layers):
          if conv_type == ConvType.GEMB:
              self.convs.append(
                  GEMBConv(
                      hidden,
                      [hidden * 2, hidden * 2],
                      [hidden * 2],
                      node_update_type,
                      layer_norm,
                  )
              )
          elif conv_type == ConvType.GIN:
              self.convs.append(
                  GINConv(
                      Sequential(
                          Linear(hidden, hidden),
                          ReLU(),
                          Linear(hidden, hidden),
                          ReLU(),
                          BN(hidden),
                      ),
                      train_eps=True,
                  )
              )
  
      self.use_virtual_node = use_virtual_node
      if use_virtual_node:
          self.virtual_init = torch.nn.Embedding(1, hidden)
          self.virtual_mlps = torch.nn.ModuleList()
          for _ in range(num_layers):
              self.virtual_mlps.append(
                  Sequential(
                      Linear(hidden, hidden),
                      ReLU(),
                      Linear(hidden, hidden),
                  )
              )
  
file_path: DIG/dig/auggraph/method/GraphAug/aug/aug_encoder.py
imports: import torch
  from torch.nn import Linear, Sequential, ReLU, BatchNorm1d
  from torch_geometric.nn import GINConv
  from torch_scatter import scatter
  from ..constants import *
label_desc: Use image node_id 1 to create a new AugEncoder object from inherited base classes: torch.nn with example: obj = AugEncoder(in_dim, num_layers, hidden, conv_type, use_virtual_node, node_update_type, layer_norm)