code: def forward(self, X):
      # input to first hidden layer
      X = self.hidden1(X)
      X = self.act1(X)
      # second hidden layer
      X = self.hidden2(X)
      X = self.act2(X)
      # third hidden layer and output
      X = self.hidden3(X)
      X = self.act3(X)
      return X
  
file_path: BigDL/python/orca/tutorial/xshards/ionosphere.py
imports: from torch.nn import Linear
  from torch.nn import ReLU
  from torch.nn import Sigmoid
  from torch.nn import Module
  from torch.optim import SGD
  from torch.nn import BCELoss
  from torch.nn.init import kaiming_uniform_
  from torch.nn.init import xavier_uniform_
  import bigdl.orca.data.pandas
  from bigdl.orca import init_orca_context, stop_orca_context
  from bigdl.orca.learn.pytorch import Estimator
  from bigdl.orca.learn.metrics import Accuracy
  from bigdl.orca.data.transformer import StringIndexer
label_desc: Use image node_id 2 for calling the MLP obj's underlying member method code with example usage: obj.forward(X) and returns: X