code: def __init__(self, block, num_blocks, num_classes=10):
      super(ResNet, self).__init__()
      self.in_planes = 64
  
      self.conv1 = nn.Conv2d(
          3, 64, kernel_size=3, stride=1, padding=1, bias=False
      )
      self.bn1 = nn.BatchNorm2d(64)
      self.layer1 = self._make_layer(block, 64, num_blocks[0], stride=1)
      self.layer2 = self._make_layer(
          block, 128, num_blocks[1], stride=2
      )
      self.layer3 = self._make_layer(
          block, 256, num_blocks[2], stride=2
      )
      self.layer4 = self._make_layer(
          block, 512, num_blocks[3], stride=2
      )
      self.linear = nn.Linear(512 * block.expansion, num_classes)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 1 to create a new ResNet object from inherited base classes: nn with example: obj = ResNet(block, num_blocks, num_classes)