code: def __init__(self, in_ch=3, out_ch=3, dirate=1):
      super(REBNCONV, self).__init__()
  
      self.conv_s1 = nn.Conv2D(
          in_ch, out_ch, 3, padding=1 * dirate, dilation=1 * dirate
      )
      self.bn_s1 = nn.BatchNorm2D(out_ch)
      self.relu_s1 = nn.ReLU()
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager
  from paddleseg.models import layers
  from paddleseg.utils import utils
label_desc: Use image node_id 1 to create a new REBNCONV object from inherited base classes: nn with example: obj = REBNCONV(in_ch, out_ch, dirate)