code: def xavier(self, channels, filter_size):
      stdv = (3.0 / (filter_size**2 * channels)) ** 0.5
      param_attr = fluid.param_attr.ParamAttr(
          initializer=fluid.initializer.Uniform(-stdv, stdv)
      )
      return param_attr
  
file_path: AdvBox/tutorials/image_classification/googlenet.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from builtins import object
  import paddle
  import paddle.fluid
label_desc: Use image node_id 3 for calling the GoogleNet obj's underlying member method code with example usage: obj.xavier(channels, filter_size) and returns: param_attr