code: def forward(
      self, x, with_latent=False, fake_relu=False, no_relu=False
  ):
      assert (
          not no_relu
      ), "no_relu not yet supported for this architecture"
      out = F.relu(self.bn1(self.conv1(x)))
      out = self.layer1(out)
      out = self.layer2(out)
      out = self.layer3(out)
      out = self.layer4(out, fake_relu=fake_relu)
      out = F.avg_pool2d(out, 4)
      pre_out = out.view(out.size(0), -1)
      final = self.linear(pre_out)
      if with_latent:
          return final, pre_out
      return final
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from ..tools.custom_modules import SequentialWithArgs, FakeReLU
label_desc: Use image node_id 3 for calling the ResNet obj's underlying member method code with example usage: obj.forward(x, with_latent, fake_relu, no_relu) and returns: final, final,  pre_out