code: def __init__(
      self,
      in_channels,
      out_channels,
      kernel_size,
      stride,
      groups=1,
      use_act=True,
  ):
      super().__init__()
      self.use_act = use_act
      self.conv = Conv2D(
          in_channels,
          out_channels,
          kernel_size,
          stride,
          padding=(kernel_size - 1) // 2,
          groups=groups,
          bias_attr=False,
      )
      self.bn = BatchNorm2D(
          out_channels,
          weight_attr=ParamAttr(regularizer=L2Decay(0.0)),
          bias_attr=ParamAttr(regularizer=L2Decay(0.0)),
      )
      if self.use_act:
          self.act = ReLU()
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle.nn.initializer import KaimingNormal, Constant
  from paddle.nn import Conv2D, BatchNorm2D, ReLU, AdaptiveAvgPool2D, MaxPool2D
  from paddle.regularizer import L2Decay
  from paddle import ParamAttr
label_desc: Use image node_id 1 to create a new ConvBNAct object from inherited base classes: nn with example: obj = ConvBNAct(in_channels, out_channels, kernel_size, stride, groups, use_act)