class_docstr: Simplified version of original basic residual block. This is used in
  `SCNet <https://arxiv.org/abs/2012.10150>`_.
  
  - Norm layer is now optional
  - Last ReLU in forward function is removed
class_docstr_tok: ["Simplified","version","of","original","basic","residual","block",".","This","is","used","in","`","SCNet","<","https",":","\/\/arxiv.org\/abs\/2012.10150",">","`","_",".","-","Norm","layer","is","now","optional","-","Last","ReLU","in","forward","function","is","removed"]
code: def __init__(
      self,
      inplanes: int,
      planes: int,
      stride: int = 1,
      dilation: int = 1,
      downsample: Optional[Sequential] = None,
      style: ConfigType = "pytorch",
      with_cp: bool = False,
      conv_cfg: OptConfigType = None,
      norm_cfg: ConfigType = dict(type="BN"),
      dcn: OptConfigType = None,
      plugins: OptConfigType = None,
      init_cfg: OptMultiConfig = None,
  ) -> None:
      super().__init__(init_cfg=init_cfg)
      assert dcn is None, "Not implemented yet."
      assert plugins is None, "Not implemented yet."
      assert not with_cp, "Not implemented yet."
      self.with_norm = norm_cfg is not None
      with_bias = True if norm_cfg is None else False
      self.conv1 = build_conv_layer(
          conv_cfg,
          inplanes,
          planes,
          3,
          stride=stride,
          padding=dilation,
          dilation=dilation,
          bias=with_bias,
      )
      if self.with_norm:
          self.norm1_name, norm1 = build_norm_layer(
              norm_cfg, planes, postfix=1
          )
          self.add_module(self.norm1_name, norm1)
      self.conv2 = build_conv_layer(
          conv_cfg, planes, planes, 3, padding=1, bias=with_bias
      )
      if self.with_norm:
          self.norm2_name, norm2 = build_norm_layer(
              norm_cfg, planes, postfix=2
          )
          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
  
file_path: mmdetection/mmdet/models/layers/res_layer.py
imports: from typing import Optional
  from mmcv.cnn import build_conv_layer, build_norm_layer
  from mmengine.model import BaseModule, Sequential
  from torch import Tensor
  from torch import nn
  from mmdet.utils import ConfigType, OptConfigType, OptMultiConfig
label_desc: Use image node_id 1 to create a new SimplifiedBasicBlock object from inherited base classes: BaseModule with example: obj = SimplifiedBasicBlock(inplanes, planes, stride, dilation, downsample, style, with_cp, conv_cfg, norm_cfg, dcn, plugins, init_cfg)