code: def get_topk(self, outputs):
      # resize to image size
      outputs = [self.interpolate(x) for x in outputs]
      if len(outputs) == 3:
          tagmap = paddle.concat(
              (outputs[1].unsqueeze(4), outputs[2].unsqueeze(4)), axis=4
          )
      else:
          tagmap = outputs[1].unsqueeze(4)
  
      heatmap = outputs[0]
      N, J = 1, self.hrhrnet_head.num_joints
      heatmap_maxpool = self.pool(heatmap)
      # topk
      maxmap = heatmap * (heatmap == heatmap_maxpool)
      maxmap = maxmap.reshape([N, J, -1])
      heat_k, inds_k = maxmap.topk(self.max_num_people, axis=2)
  
      outputs = [heatmap, tagmap, heat_k, inds_k]
      return outputs
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from scipy.optimize import linear_sum_assignment
  from collections import abc, defaultdict
  import numpy
  import paddle
  from ppdet.core.workspace import register, create, serializable
  from .meta_arch import BaseArch
  from ..None import layers
  from ..keypoint_utils import transpred
label_desc: Use image node_id 6 for calling the HigherHRNet obj's underlying member method code with example usage: obj.get_topk(outputs) and returns: outputs