code: def __init__(self, in_feats, dim_h, dim_z):
      super(MLPA, self).__init__()
  
      self.gcn_mean = torch.nn.Sequential(
          torch.nn.Linear(in_feats, dim_h),
          torch.nn.ReLU(),
          torch.nn.Linear(dim_h, dim_z),
      )
  
file_path: DIG/dig/fairgraph/method/Graphair/aug_module.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  import pyro
  from .GCN import GCN_Body
label_desc: Use image node_id 1 to create a new MLPA object from inherited base classes: torch.nn with example: obj = MLPA(in_feats, dim_h, dim_z)