code: def _run_on_loss(self, net, param_init_net, param, grad=None):
      output_blob = net.NextScopedBlob(param + "_l2_regularization")
      net.LpNorm([param], [output_blob], p=2)
      net.Scale([output_blob], [output_blob], scale=self.reg_lambda)
      return output_blob
  
imports: from caffe2.python import core, utils
  import numpy
label_desc: Use image node_id 2 for calling the L2Norm obj's underlying member method code with example usage: obj._run_on_loss(net, param_init_net, param, grad) and returns: output_blob