code: def __init__(
      self,
      in_chs,
      skip_chs,
      mid_chs,
      out_chs,
      is_first,
      stride,
      dilation=1,
  ):
      super(SelecSlsBlock, self).__init__()
      self.stride = stride
      self.is_first = is_first
      assert stride in [1, 2]
  
      # Process input with 4 conv blocks with the same number of input and output channels
      self.conv1 = conv_bn(
          in_chs, mid_chs, 3, stride, dilation=dilation
      )
      self.conv2 = conv_bn(mid_chs, mid_chs, 1)
      self.conv3 = conv_bn(mid_chs, mid_chs // 2, 3)
      self.conv4 = conv_bn(mid_chs // 2, mid_chs, 1)
      self.conv5 = conv_bn(mid_chs, mid_chs // 2, 3)
      self.conv6 = conv_bn(
          2 * mid_chs + (0 if is_first else skip_chs), out_chs, 1
      )
  
imports: from typing import List
  import torch
  import torch.nn
  import torch.nn.functional
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import create_classifier
  from ._builder import build_model_with_cfg
  from ._registry import register_model, generate_default_cfgs
label_desc: Use image node_id 1 to create a new SelecSlsBlock object from inherited base classes: nn with example: obj = SelecSlsBlock(in_chs, skip_chs, mid_chs, out_chs, is_first, stride, dilation)