code: def forward(self, x):
      conv1_out = self.conv1(x)
      conv2_out = self.conv2(conv1_out)
      conv3_out = self.conv3(conv2_out)
      res = conv3_out.view(conv3_out.size(0), -1)
      out = self.dense(res)
      # return torch.nn.functional.log_softmax(out, dim=1)
      return out
  
file_path: AdvBox/tutorials/mnist_model_pytorch.py
imports: from __future__ import print_function
  from __future__ import division
  from builtins import range
  from past.utils import old_div
  import os
  import torch
  import torchvision
  from torch.autograd import Variable
  import torch.utils.data.dataloader
label_desc: Use image node_id 2 for calling the Net obj's underlying member method code with example usage: obj.forward(x) and returns: out