class_docstr: ResNet model.
class_docstr_tok: ["ResNet","model","."]
code: def __init__(self):
      datasets = ["cifar10", "imagenet"]
      err_str = "Dataset {} is not supported"
      assert cfg.TRAIN.DATASET in datasets, err_str.format(
          cfg.TRAIN.DATASET
      )
      assert cfg.TEST.DATASET in datasets, err_str.format(
          cfg.TEST.DATASET
      )
      super(ResNet, self).__init__()
      if "cifar" in cfg.TRAIN.DATASET:
          self._construct_cifar()
      else:
          self._construct_imagenet()
      self.apply(init_weights)
  
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 1 to create a new ResNet object from inherited base classes: Module with example: obj = ResNet()