code: def forward(self, x):
      output = self.l1(x)
      output = self.relu(output)
      output = self.l2(output)
      return output.view(-1)
  
imports: import pytest
  import pytorch_lightning
  import torch
  import torch.nn
  import torch.nn.functional
  from sklearn.datasets import load_diabetes
  from torch.utils.data import Dataset
  from torchvision import transforms
  from torchvision.datasets import MNIST
  import nni
  import nni.nas.evaluator.pytorch.lightning
  from nni.nas.evaluator import FunctionalEvaluator, Evaluator
  from nni.nas.space import RawFormatModelSpace
label_desc: Use image node_id 2 for calling the FCNet obj's underlying member method code with example usage: obj.forward(x) and returns: output