code: def batch_p_dist(x, y, p=2):
      """
      calculate pairwise p_dist, the first index of x and y are batch
      return [x.shape[0], y.shape[0]]
      """
      x = x.unsqueeze(1)
      diff = x - y
      return paddle.norm(diff, p=p, axis=list(range(2, diff.dim())))
  
file_path: PaddleDetection/ppdet/modeling/assigners/uniform_assigner.py
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from ppdet.core.workspace import register
  from ppdet.modeling.bbox_utils import batch_bbox_overlaps
  from ppdet.modeling.transformers import bbox_xyxy_to_cxcywh
label_desc: Use image node_id 1 for calling a global function with example usage: batch_p_dist(x, y, p) and returns: paddle