code: def __init__(self, input_dim, hidden_dim, args):
      super(BaselineMLP, self).__init__()
      self.emb_model = GNNStack(input_dim, hidden_dim, hidden_dim, args)
      self.mlp = nn.Sequential(nn.Linear(2 * hidden_dim, 2))
  
imports: from functools import reduce
  import random
  import networkx
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  import torch_geometric.nn
  import torch_geometric.utils
  import utils
label_desc: Use image node_id 1 to create a new BaselineMLP object from inherited base classes: nn with example: obj = BaselineMLP(input_dim, hidden_dim, args)