class_docstr: ResidualBlock
  introduced in: https://arxiv.org/abs/1512.03385
  recommended architecture: http://torch.ch/blog/2016/02/04/resnets.html
class_docstr_tok: ["ResidualBlock","introduced","in",":","https",":","\/\/arxiv.org\/abs\/1512.03385","recommended","architecture",":","http",":","\/\/torch.ch\/blog\/2016\/02\/04\/resnets.html"]
code: def __init__(self, channels):
      super(ResidualBlock, self).__init__()
      self.conv1 = ConvLayer(
          channels, channels, kernel_size=3, stride=1
      )
      self.in1 = torch.nn.InstanceNorm2d(channels, affine=True)
      self.conv2 = ConvLayer(
          channels, channels, kernel_size=3, stride=1
      )
      self.in2 = torch.nn.InstanceNorm2d(channels, affine=True)
      self.relu = torch.nn.ReLU()
  
file_path: ignite/examples/fast_neural_style/transformer_net.py
imports: import torch
label_desc: Use image node_id 1 to create a new ResidualBlock object from inherited base classes: torch.nn with example: obj = ResidualBlock(channels)