code: def __init__(self, num_channels, scale=1.0):
      super(L2NormScale, self).__init__()
      self.scale = self.create_parameter(
          attr=ParamAttr(
              initializer=paddle.nn.initializer.Constant(scale)
          ),
          shape=[num_channels],
      )
  
imports: from __future__ import division
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle import ParamAttr
  from paddle.nn import Conv2D, MaxPool2D
  from ppdet.core.workspace import register, serializable
  from ..shape_spec import ShapeSpec
label_desc: Use image node_id 1 to create a new L2NormScale object from inherited base classes: nn with example: obj = L2NormScale(num_channels, scale)