class_docstr: A compact VGG-style network structure for super-resolution.
  This class is copied from https://github.com/xinntao/Real-ESRGAN
class_docstr_tok: ["A","compact","VGG-style","network","structure","for","super-resolution",".","This","class","is","copied","from","https",":","\/\/github.com\/xinntao\/Real-ESRGAN"]
code: def forward(self, x):
      out = x
      for i in range(0, len(self.body)):
          out = self.body[i](out)
  
      out = self.upsampler(out)
      # add the nearest upsampled image, so that the network learns the residual
      base = F.interpolate(x, scale_factor=self.upscale, mode="nearest")
      out += base
      return out
  
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 SRVGGNetCompact obj's underlying member method code with example usage: obj.forward(x) and returns: out