code: def forward(self, x):
      out = self.conv1(x)
      out = self.layer1(out)
      out = self.layer2(out)
      out = self.layer3(out)
      out = self.layer4(out)
      out = F.relu(self.bn(out))
      out = F.avg_pool2d(out, 4)
      out = out.view(out.size(0), -1)
      out = self.linear(out)
      return out
  
imports: from PIL import Image
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  import torchvision.transforms
  from torch.utils.data import Dataset, DataLoader
  from torch.optim.lr_scheduler import MultiStepLR
  from art.estimators.classification import PyTorchClassifier
  from art.data_generators import PyTorchDataGenerator
  from art.defences.trainer import AdversarialTrainerAWPPyTorch
  from art.utils import load_cifar10
  from art.attacks.evasion import ProjectedGradientDescent
label_desc: Use image node_id 3 for calling the PreActResNet obj's underlying member method code with example usage: obj.forward(x) and returns: out