code: def __init__(
      self,
      in_channels,
      out_channels,
      ksize,
      stride,
      groups=1,
      bias=False,
      act="silu",
  ):
      super(BaseConv, self).__init__()
      self.conv = nn.Conv2D(
          in_channels,
          out_channels,
          kernel_size=ksize,
          stride=stride,
          padding=(ksize - 1) // 2,
          groups=groups,
          bias_attr=bias,
      )
      self.bn = nn.BatchNorm2D(
          out_channels,
          weight_attr=ParamAttr(regularizer=L2Decay(0.0)),
          bias_attr=ParamAttr(regularizer=L2Decay(0.0)),
      )
  
      self._init_weights()
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle import ParamAttr
  from paddle.regularizer import L2Decay
  from ppdet.core.workspace import register, serializable
  from ppdet.modeling.initializer import conv_init_
  from ..shape_spec import ShapeSpec
label_desc: Use image node_id 1 to create a new BaseConv object from inherited base classes: nn with example: obj = BaseConv(in_channels, out_channels, ksize, stride, groups, bias, act)