code: def __init__(
      self,
      in_channels,
      out_channels,
      kernel_size,
      stride=1,
      padding=0,
      dilation=1,
      groups=1,
      bias=True,
      padding_mode="zeros",
      inplace=True,
  ):
      super().__init__()
      self.conv = nn.Conv2D(
          in_channels=in_channels,
          out_channels=out_channels,
          kernel_size=kernel_size,
          stride=stride,
          padding=padding,
          dilation=dilation,
          groups=groups,
          bias_attr=bias,
          padding_mode=padding_mode,
      )
      self.bn = nn.BatchNorm2D(out_channels)
      self.relu = nn.ReLU()
  
imports: from paddle import nn
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, bias, padding_mode, inplace)