class_docstr: Pre-activation version of the BasicBlock.
class_docstr_tok: ["Pre-activation","version","of","the","BasicBlock","."]
code: def forward(self, x):
      out = F.relu(self.bn1(x))
      shortcut = self.shortcut(x) if hasattr(self, "shortcut") else x
      out = self.conv1(out)
      out = self.conv2(F.relu(self.bn2(out)))
      out += shortcut
      return out
  
imports: import math
  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 art.estimators.classification import PyTorchClassifier
  from art.data_generators import PyTorchDataGenerator
  from art.defences.trainer import AdversarialTrainerFBFPyTorch
  from art.utils import load_cifar10
  from art.attacks.evasion import ProjectedGradientDescent
label_desc: Use image node_id 2 for calling the PreActBlock obj's underlying member method code with example usage: obj.forward(x) and returns: out