code: def forward(self, x, outm=None):
      if self.resrgan_scale == 1:
          feat = pixel_unshuffle(x, scale=4)
      elif self.resrgan_scale == 2:
          feat = pixel_unshuffle(x, scale=2)
      else:
          feat = x
  
      return self.model(feat)
  
imports: from collections import OrderedDict
  import math
  import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the RRDBNet obj's underlying member method code with example usage: obj.forward(x, outm) and returns: self