code: def __init__(self, noise_size=100, feature_size=784, hidden_size=128):
      super(LSGAN_MLP, self).__init__()
      self.noise_size = noise_size
      self.feature_size = feature_size
      self.hidden_size = hidden_size
  
      # Generative Net
      self.gen_net_fc_0 = layer.Linear(self.hidden_size)
      self.gen_net_relu_0 = layer.ReLU()
      self.gen_net_fc_1 = layer.Linear(self.feature_size)
      self.gen_net_sigmoid_1 = layer.Sigmoid()
  
      # Discriminative Net
      self.dis_net_fc_0 = layer.Linear(self.hidden_size)
      self.dis_net_relu_0 = layer.ReLU()
      self.dis_net_fc_1 = layer.Linear(1)
      self.mse_loss = layer.MeanSquareError()
  
file_path: singa/examples/gan/model/lsgan_mlp.py
imports: from singa import layer
  from singa import model
  from singa import autograd
label_desc: Use image node_id 1 to create a new LSGAN_MLP object from inherited base classes: model with example: obj = LSGAN_MLP(noise_size, feature_size, hidden_size)