code: def get_para_bias_attr(l2_decay, k):
      if l2_decay > 0:
          regularizer = paddle.regularizer.L2Decay(l2_decay)
          stdv = 1.0 / math.sqrt(k * 1.0)
          initializer = nn.initializer.Uniform(-stdv, stdv)
      else:
          regularizer = None
          initializer = None
      weight_attr = ParamAttr(
          regularizer=regularizer, initializer=initializer
      )
      bias_attr = ParamAttr(
          regularizer=regularizer, initializer=initializer
      )
      return [weight_attr, bias_attr]
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  import paddle
  import paddle.nn
  from paddle import ParamAttr
  import paddle.nn.functional
  import numpy
  from .rec_att_head import AttentionGRUCell
label_desc: Use image node_id 1 for calling a global function with example usage: get_para_bias_attr(l2_decay, k) and returns: list