code: def __init__(self, in_dim, out_dim):
      super(MLP, self).__init__()
      self.fcs = nn.Sequential(
          nn.Linear(in_dim, out_dim),
          nn.PReLU(),
          nn.Linear(out_dim, out_dim),
          nn.PReLU(),
          nn.Linear(out_dim, out_dim),
          nn.PReLU(),
      )
      self.linear_shortcut = nn.Linear(in_dim, out_dim)
  
file_path: dgl/examples/pytorch/mvgrl/graph/model.py
imports: import torch
  import torch.nn
  from dgl.nn.pytorch import GraphConv
  from dgl.nn.pytorch.glob import SumPooling
  from utils import local_global_loss_
label_desc: Use image node_id 1 to create a new MLP object from inherited base classes: nn with example: obj = MLP(in_dim, out_dim)