code: def __init__(self, in_dim, out_dim):
      super(MLP, self).__init__()
      self.main = [
          nn.Linear(in_dim, 2 * in_dim),
          nn.BatchNorm1D(2 * in_dim),
          nn.ReLU(),
      ]
      self.main.append(nn.Linear(2 * in_dim, out_dim))
      self.main = nn.Sequential(*self.main)
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  import pgl
  import pgl.nn
  from pgl.nn import functional
  from mol_encoder import AtomEncoder, BondEncoder
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)