code: def __init__(
      self,
      in_channels,
      out_channels,
      kernel_size=3,
      stride=1,
      padding=1,
      dilation=1,
      groups=1,
      norm_layer=nn.BatchNorm2d,
      bias=False,
      **kwargs,
  ):
      super(_ConvBNReLU, self).__init__()
      self.conv = nn.Conv2d(
          in_channels,
          out_channels,
          kernel_size,
          stride,
          padding,
          dilation,
          groups,
          bias,
      )
      self.bn = norm_layer(out_channels)
      self.relu = nn.ReLU(True)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from pywick.models.segmentation.da_basenets.resnet import resnet18
label_desc: Use image node_id 1 to create a new _ConvBNReLU object from inherited base classes: nn with example: obj = _ConvBNReLU(in_channels, out_channels, kernel_size, stride, padding, dilation, groups, norm_layer, bias)