code: def _init_weights(self):
      bias_cls = bias_init_with_prob(0.01)
      bias_reg = paddle.full([5], math.log(5.0), dtype=self._dtype)
      bias_reg[:2] = 0.0
      bias_reg[-1] = bias_cls
      for cls_, reg_ in zip(self.conv_cls, self.conv_reg):
          constant_(cls_[-1].weight)
          constant_(cls_[-1].bias, bias_cls)
          constant_(reg_[-1].weight)
          reg_[-1].bias.set_value(bias_reg)
  
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
  import math
  import numpy
  from ..initializer import bias_init_with_prob, constant_
  from ..backbones.csp_darknet import BaseConv, DWConv
  from ..losses import IouLoss
  from ppdet.modeling.assigners.simota_assigner import SimOTAAssigner
  from ppdet.modeling.bbox_utils import bbox_overlaps
  from ppdet.modeling.layers import MultiClassNMS
label_desc: Use image node_id 3 for calling the YOLOXHead obj's underlying member method code with example usage: obj._init_weights() without return types