code: def forward(self, input):
      if input.is_cuda and self.ngpu > 1:
          output = nn.parallel.data_parallel(
              self.main, input, range(self.ngpu)
          )
      else:
          output = self.main(input)
  
      return output.view(-1, 1).squeeze(1)
  
imports: from __future__ import print_function
  import argparse
  import os
  import random
  import torch
  import torch.nn
  import torch.nn.parallel
  import torch.backends.cudnn
  import torch.optim
  import torch.utils.data
  import torchvision.datasets
  import torchvision.transforms
  import torchvision.utils
label_desc: Use image node_id 2 for calling the Discriminator obj's underlying member method code with example usage: obj.forward(input) and returns: output