code: def _forward(
      self, x, with_latent=False, fake_relu=False, no_relu=False
  ):
      x = self.conv1(x)
      x = self.bn1(x)
      x = self.relu(x)
      x = self.maxpool(x)
  
      x = self.layer1(x)
      x = self.layer2(x)
      x = self.layer3(x)
      x = self.layer4(x, fake_relu=fake_relu, no_relu=no_relu)
  
      x = self.avgpool(x)
      pre_out = torch.flatten(x, 1)
      final = self.fc(pre_out)
      if with_latent:
          return final, pre_out
      return final
  
imports: import torch
  import torch.nn
  from torch.hub import load_state_dict_from_url
  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