code: def _init_weights(self):
      for p in self.parameters():
          if p.dim() > 1:
              init.xavier_uniform_(p)
  
      bias_init = init.bias_init_with_prob(0.01)
      init.constant_(self.fc_cls.bias, bias_init)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import copy
  import paddle
  from paddle import nn
  from ppdet.core.workspace import register
  from ppdet.modeling import initializer
  from .roi_extractor import RoIAlign
  from ..bbox_utils import delta2bbox_v2
  from ..cls_utils import _get_class_default_kwargs
  from ..layers import MultiHeadAttention
label_desc: Use image node_id 2 for calling the DIIHead obj's underlying member method code with example usage: obj._init_weights() without return types