code: def _init_weights(self):
      bias_cls = bias_init_with_prob(0.01)
      bias_angle = [10.0] + [1.0] * self.angle_max
      for cls_, reg_, angle_ in zip(
          self.pred_cls, self.pred_reg, self.pred_angle
      ):
          normal_(cls_.weight, std=0.01)
          constant_(cls_.bias, bias_cls)
          normal_(reg_.weight, std=0.01)
          constant_(reg_.bias)
          constant_(angle_.weight)
          vector_(angle_.bias, bias_angle)
  
      angle_proj = paddle.linspace(
          0, self.angle_max, self.angle_max + 1
      )
      self.angle_proj = angle_proj * self.half_pi_bin
      self.angle_proj_conv.weight.set_value(
          self.angle_proj.reshape([1, self.angle_max + 1, 1, 1])
      )
      self.angle_proj_conv.weight.stop_gradient = True
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from ppdet.core.workspace import register
  from ..losses import ProbIoULoss
  from ..initializer import bias_init_with_prob, constant_, normal_, vector_
  from ppdet.modeling.backbones.cspresnet import ConvBNLayer
  from ppdet.modeling.ops import get_static_shape, get_act_fn, anchor_generator
  from ppdet.modeling.layers import MultiClassNMS
label_desc: Use image node_id 3 for calling the PPYOLOERHead obj's underlying member method code with example usage: obj._init_weights() without return types