code: def __init__(
      self,
      depth,
      stage=3,
      stride=2,
      dilation=1,
      style="pytorch",
      norm_cfg=dict(type="BN", requires_grad=True),
      norm_eval=True,
      with_cp=False,
      dcn=None,
  ):
      super(ResLayer, self).__init__()
      self.norm_eval = norm_eval
      self.norm_cfg = norm_cfg
      self.stage = stage
      self.fp16_enabled = False
      block, stage_blocks = ResNet.arch_settings[depth]
      stage_block = stage_blocks[stage]
      planes = 64 * 2**stage
      inplanes = 64 * 2 ** (stage - 1) * block.expansion
  
      res_layer = _ResLayer(
          block,
          inplanes,
          planes,
          stage_block,
          stride=stride,
          dilation=dilation,
          style=style,
          with_cp=with_cp,
          norm_cfg=self.norm_cfg,
          dcn=dcn,
      )
      self.add_module(f"layer{stage + 1}", res_layer)
  
file_path: insightface/detection/scrfd/mmdet/models/roi_heads/shared_heads/res_layer.py
imports: import torch.nn
  from mmcv.cnn import constant_init, kaiming_init
  from mmcv.runner import auto_fp16, load_checkpoint
  from mmdet.models.backbones import ResNet
  from mmdet.models.builder import SHARED_HEADS
  from mmdet.models.utils import ResLayer
  from mmdet.utils import get_root_logger
label_desc: Use image node_id 1 to create a new ResLayer object from inherited base classes: nn with example: obj = ResLayer(depth, stage, stride, dilation, style, norm_cfg, norm_eval, with_cp, dcn)