code: def __init__(
      self, in_channels, out_channels, stride=1, downsample=None
  ):
      super(ResidualBlock, self).__init__()
      self.conv1 = conv3x3(in_channels, out_channels, stride)
      self.bn1 = nn.BatchNorm2d(out_channels)
      self.relu = nn.ReLU(inplace=True)
      self.conv2 = conv3x3(out_channels, out_channels)
      self.bn2 = nn.BatchNorm2d(out_channels)
      self.downsample = downsample
  
file_path: pytorch-tutorial/tutorials/02-intermediate/deep_residual_network/main.py
imports: import torch
  import torch.nn
  import torchvision
  import torchvision.transforms
label_desc: Use image node_id 1 to create a new ResidualBlock object from inherited base classes: nn with example: obj = ResidualBlock(in_channels, out_channels, stride, downsample)