class_docstr: ResNet model.
class_docstr_tok: ["ResNet","model","."]
code: def _construct_cifar(self):
      err_str = "Model depth should be of the format 6n + 2 for cifar"
      assert (cfg.MODEL.DEPTH - 2) % 6 == 0, err_str
      d = int((cfg.MODEL.DEPTH - 2) / 6)
      self.stem = ResStemCifar(3, 16)
      self.s1 = ResStage(16, 16, stride=1, d=d)
      self.s2 = ResStage(16, 32, stride=2, d=d)
      self.s3 = ResStage(32, 64, stride=2, d=d)
      self.head = ResHead(64, cfg.MODEL.NUM_CLASSES)
  
imports: from pycls.core.config import cfg
  from pycls.models.blocks import activation, conv2d, conv2d_cx, gap2d, gap2d_cx, init_weights, linear, linear_cx, norm2d, norm2d_cx, pool2d, pool2d_cx
  from torch.nn import Module
label_desc: Use image node_id 2 for calling the ResNet obj's underlying member method code with example usage: obj._construct_cifar() without return types