code: def forward(self, z, y):
      zh = self.z_map(z)
      yh = self.y_map(y)
      zy = torch.cat((zh, yh), dim=1)  # Combine noise and labels.
      zyh = self.zy_map(zy)
      x = self.model(zyh)
      x = x.view(x.size(0), *img_dims)
      return x
  
file_path: gans-with-pytorch/cgan/cgan.py
imports: import argparse
  import torch
  from torch import nn, optim
  from torch.autograd.variable import Variable
  from torchvision import transforms, datasets
  from torch.utils.data import DataLoader
label_desc: Use image node_id 2 for calling the Generator obj's underlying member method code with example usage: obj.forward(z, y) and returns: x