class_docstr: A base class for both generator and the discriminator.
  Provides a common weight initialization scheme.
class_docstr_tok: ["A","base","class","for","both","generator","and","the","discriminator",".","Provides","a","common","weight","initialization","scheme","."]
code: def forward(self, x):
      return x
  
imports: import argparse
  import os
  import random
  import warnings
  from pathlib import Path
  import torch
  import torch.nn
  import torch.optim
  import torch.utils.data
  from ignite.contrib.handlers import ProgressBar
  from ignite.engine import Engine, Events
  from ignite.handlers import ModelCheckpoint, Timer
  from ignite.metrics import RunningAverage
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: x