code: def __init__(
      self,
      in_channels,
      out_channels,
      kernel_size,
      bias_attr=False,
      **kwargs,
  ):
      super().__init__()
      self.conv = nn.Conv2D(
          in_channels,
          out_channels,
          kernel_size,
          bias_attr=bias_attr,
          **kwargs,
      )
      self.bn = nn.BatchNorm2D(out_channels)
      self.relu = nn.ReLU()
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg import utils
  from paddleseg.cvlibs import manager
  from paddleseg.models import layers
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, bias_attr)