code: def _bbox_decode(self, points, pred_dist, pred_angle, stride_tensor):
      # predict vector to x, y, w, h, angle
      b, l = pred_angle.shape[:2]
      xy, wh = paddle.split(pred_dist, 2, axis=-1)
      xy = xy * stride_tensor + points
      wh = (F.elu(wh) + 1.0) * stride_tensor
      angle = F.softmax(
          pred_angle.reshape([b, l, 1, self.angle_max + 1])
      ).matmul(self.angle_proj)
      return paddle.concat([xy, wh, angle], axis=-1)
  
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 8 for calling the PPYOLOERHead obj's underlying member method code with example usage: obj._bbox_decode(points, pred_dist, pred_angle, stride_tensor) and returns: paddle