code: def keypointrcnn_inference(x, boxes):
      # type: (Tensor, List[Tensor]) -> Tuple[List[Tensor], List[Tensor]]
      kp_probs = []
      kp_scores = []
  
      boxes_per_image = [box.size(0) for box in boxes]
      x2 = x.split(boxes_per_image, dim=0)
  
      for xx, bb in zip(x2, boxes):
          kp_prob, scores = heatmaps_to_keypoints(xx, bb)
          kp_probs.append(kp_prob)
          kp_scores.append(scores)
  
      return kp_probs, kp_scores
  
imports: from typing import Dict, List, Optional, Tuple
  import torch
  import torch.nn.functional
  import torchvision
  from torch import nn, Tensor
  from torchvision.ops import boxes, roi_align
  from .None import _utils
label_desc: Use image node_id 10 for calling a global function with example usage: keypointrcnn_inference(x, boxes) and returns: kp_probs,  kp_scores