code: def _forward(self):
      feats = self.backbone(
          self.inputs
      )  # feats:[[batch_size, 40, 32, 24]]
  
      hrnet_outputs = self.final_conv(feats[0])
      res = soft_argmax(hrnet_outputs, self.num_joints)
      return res
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import paddle
  import numpy
  import math
  import cv2
  from ppdet.core.workspace import register, create
  from .meta_arch import BaseArch
  from ..keypoint_utils import transform_preds
  from ..None import layers
  from paddle.nn import functional
label_desc: Use image node_id 3 for calling the TinyPose3DHRHeatmapNet obj's underlying member method code with example usage: obj._forward() and returns: res