code: def _init_weights(self):
      bias_cls = bias_init_with_prob(0.01)
      for cls_, reg_ in zip(self.pred_cls, self.pred_reg):
          constant_(cls_.weight)
          constant_(cls_.bias, bias_cls)
          constant_(reg_.weight)
          constant_(reg_.bias, 1.0)
  
      proj = paddle.linspace(
          self.reg_range[0], self.reg_range[1] - 1, self.reg_channels
      ).reshape([1, self.reg_channels, 1, 1])
      self.proj_conv.weight.set_value(proj)
      self.proj_conv.weight.stop_gradient = True
      if self.eval_size:
          anchor_points, stride_tensor = self._generate_anchors()
          self.anchor_points = anchor_points
          self.stride_tensor = stride_tensor
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from ppdet.core.workspace import register
  from paddle import ParamAttr
  from paddle.nn.initializer import KaimingNormal
  from paddle.nn.initializer import Normal, Constant
  from ..bbox_utils import batch_distance2bbox
  from ..losses import GIoULoss
  from ..initializer import bias_init_with_prob, constant_, normal_
  from ..assigners.utils import generate_anchors_for_grid_cell
  from ppdet.modeling.backbones.cspresnet import ConvBNLayer, RepVggBlock
  from ppdet.modeling.ops import get_static_shape, get_act_fn
  from ppdet.modeling.layers import MultiClassNMS
label_desc: Use image node_id 3 for calling the PPYOLOEHead obj's underlying member method code with example usage: obj._init_weights() without return types