code: def __init__(
      self,
      inplanes,
      planes,
      stride=1,
      dilation=1,
      downsample=None,
      style="pytorch",
      with_cp=False,
      conv_cfg=None,
      norm_cfg=dict(type="BN"),
      dcn=None,
      plugins=None,
      init_cfg=None,
  ):
      super(BasicBlock, self).__init__(init_cfg)
      assert dcn is None, "Not implemented yet."
      assert plugins is None, "Not implemented yet."
  
      self.norm1_name, norm1 = build_norm_layer(
          norm_cfg, planes, postfix=1
      )
      self.norm2_name, norm2 = build_norm_layer(
          norm_cfg, planes, postfix=2
      )
  
      self.conv1 = build_conv_layer(
          conv_cfg,
          inplanes,
          planes,
          3,
          stride=stride,
          padding=dilation,
          dilation=dilation,
          bias=False,
      )
      self.add_module(self.norm1_name, norm1)
      self.conv2 = build_conv_layer(
          conv_cfg, planes, planes, 3, padding=1, bias=False
      )
      self.add_module(self.norm2_name, norm2)
  
      self.relu = nn.ReLU(inplace=True)
      self.downsample = downsample
      self.stride = stride
      self.dilation = dilation
      self.with_cp = with_cp
  
imports: import warnings
  import torch.nn
  import torch.utils.checkpoint
  from mmcv.cnn import build_conv_layer, build_norm_layer, build_plugin_layer
  from mmengine.model import BaseModule
  from torch.nn.modules.batchnorm import _BatchNorm
  from mmdet.registry import MODELS
  from ..layers import ResLayer
label_desc: Use image node_id 1 to create a new BasicBlock object from inherited base classes: BaseModule with example: obj = BasicBlock(inplanes, planes, stride, dilation, downsample, style, with_cp, conv_cfg, norm_cfg, dcn, plugins, init_cfg)