old_contents: import torch
  import torch.nn as nn
  import torch.nn.init as init
  from numpy.random import normal
  from numpy.linalg import svd
  from math import sqrt
  
  
  class Net(nn.Module):
      def __init__(self, upscale_factor):
          super(Net, self).__init__()
  
          self.relu = nn.ReLU()
          self.conv1 = nn.Conv2d(1, 64, (5, 5), (1, 1), (2, 2))
          self.conv2 = nn.Conv2d(64, 64, (3, 3), (1, 1), (1, 1))
          self.conv3 = nn.Conv2d(64, 32, (3, 3), (1, 1), (1, 1))
          self.conv4 = nn.Conv2d(32, upscale_factor ** 2, (3, 3), (1, 1), (1, 1))
          self.pixel_shuffle = nn.PixelShuffle(upscale_factor)
  
          self._initialize_weights()
  
      def forward(self, x):
          x = self.relu(self.conv1(x))
          x = self.relu(self.conv2(x))
          x = self.relu(self.conv3(x))
          x = self.pixel_shuffle(self.conv4(x))
          return x
  
      def _initialize_weights(self):
          init.orthogonal(self.conv1.weight, init.gain('relu'))
          init.orthogonal(self.conv2.weight, init.gain('relu'))
          init.orthogonal(self.conv3.weight, init.gain('relu'))
          init.orthogonal(self.conv4.weight)
  
new_contents: import torch
  import torch.nn as nn
  import torch.nn.init as init
  
  
  class Net(nn.Module):
      def __init__(self, upscale_factor):
          super(Net, self).__init__()
  
          self.relu = nn.ReLU()
          self.conv1 = nn.Conv2d(1, 64, (5, 5), (1, 1), (2, 2))
          self.conv2 = nn.Conv2d(64, 64, (3, 3), (1, 1), (1, 1))
          self.conv3 = nn.Conv2d(64, 32, (3, 3), (1, 1), (1, 1))
          self.conv4 = nn.Conv2d(32, upscale_factor ** 2, (3, 3), (1, 1), (1, 1))
          self.pixel_shuffle = nn.PixelShuffle(upscale_factor)
  
          self._initialize_weights()
  
      def forward(self, x):
          x = self.relu(self.conv1(x))
          x = self.relu(self.conv2(x))
          x = self.relu(self.conv3(x))
          x = self.pixel_shuffle(self.conv4(x))
          return x
  
      def _initialize_weights(self):
          init.orthogonal(self.conv1.weight, init.gain('relu'))
          init.orthogonal(self.conv2.weight, init.gain('relu'))
          init.orthogonal(self.conv3.weight, init.gain('relu'))
          init.orthogonal(self.conv4.weight)
  
subject: Remove unused imports in SR example (#190)