code: def __init__(self, in_planes, out_planes, kernel=3, stride=1):
      super(ConvBNRelu, self).__init__()
      self.conv = nn.Conv2D(
          in_planes,
          out_planes,
          kernel_size=kernel,
          stride=stride,
          padding=kernel // 2,
          bias_attr=False,
      )
      self.bn = SyncBatchNorm(out_planes, data_format="NCHW")
      self.relu = nn.ReLU()
  
imports: import math
  import paddle
  import paddle.nn
  from paddleseg.utils import utils
  from paddleseg.cvlibs import manager, param_init
  from paddleseg.models.layers.layer_libs import SyncBatchNorm
label_desc: Use image node_id 1 to create a new ConvBNRelu object from inherited base classes: nn with example: obj = ConvBNRelu(in_planes, out_planes, kernel, stride)