code: def forward(self, x):
      # x = self.conv0(x)
      x = self.conv1(x)
      x = self.bn1(x)
      x = self.relu(x)
      x = F.max_pool2d(x, kernel_size=3, stride=2, padding=1)
  
      x = self.layer1(x)  # 64, 64x64
  
      x = self.layer2(x)  # 128, 32x32
      flat2 = make_max_flat(x)  ##make_avg_flat
  
      x = self.layer3(x)  # 256, 16x16
      flat3 = make_max_flat(x)
  
      x = self.layer4(x)  # 512,  8x8
      flat4 = make_max_flat(x)
  
      # x = torch.cat([flat2,flat3,flat4,],1)
      # x = self.fc(x)
      x = self.fc2(flat2) + self.fc3(flat3) + self.fc4(flat4)
  
      logit = x
      prob = torch.sigmoid(logit)
      return logit, prob
  
imports: import os
  import math
  import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 3 for calling the PyResNet obj's underlying member method code with example usage: obj.forward(x) and returns: logit,  prob