code: def _init_prior_embeddings(self):
      self.prior_embeddings = nn.Embedding(self.num_priors, 3)
      bottom_priors_nums = self.num_priors * 3 // 4
      left_priors_nums, _ = self.num_priors // 8, self.num_priors // 8
      strip_size = 0.5 / (left_priors_nums // 2 - 1)
      bottom_strip_size = 1 / (bottom_priors_nums // 4 + 1)
  
      with paddle.no_grad():
          for i in range(left_priors_nums):
              self.prior_embeddings.weight[i, 0] = i // 2 * strip_size
              self.prior_embeddings.weight[i, 1] = 0.0
              self.prior_embeddings.weight[i, 2] = (
                  0.16 if i % 2 == 0 else 0.32
              )
  
          for i in range(
              left_priors_nums, left_priors_nums + bottom_priors_nums
          ):
              self.prior_embeddings.weight[i, 0] = 0.0
              self.prior_embeddings.weight[i, 1] = (
                  (i - left_priors_nums) // 4 + 1
              ) * bottom_strip_size
              self.prior_embeddings.weight[i, 2] = 0.2 * (i % 4 + 1)
  
          for i in range(
              left_priors_nums + bottom_priors_nums, self.num_priors
          ):
              self.prior_embeddings.weight[i, 0] = (
                  (i - left_priors_nums - bottom_priors_nums)
                  // 2
                  * strip_size
              )
              self.prior_embeddings.weight[i, 1] = 1.0
              self.prior_embeddings.weight[i, 2] = (
                  0.68 if i % 2 == 0 else 0.84
              )
  
imports: import math
  import paddle
  import numpy
  import paddle.nn
  import paddle.nn.functional
  from ppdet.core.workspace import register
  from ppdet.modeling.initializer import normal_
  from ppdet.modeling.lane_utils import Lane
  from ppdet.modeling.losses import line_iou
  from ppdet.modeling.clrnet_utils import ROIGather, LinearModule, SegDecoder
label_desc: Use image node_id 5 for calling the CLRHead obj's underlying member method code with example usage: obj._init_prior_embeddings() without return types