code: def _forward_test(self):
      feats = self.backbone.forward_features(self.inputs["image"])
      output_heatmap = self.head(feats)
  
      if self.flip_test:
          img_flipped = self.inputs["image"].flip(3)
          features_flipped = self.backbone.forward_features(img_flipped)
          output_flipped_heatmap = self.head.inference_model(
              features_flipped, self.flip_test
          )
  
          output_heatmap = (
              output_heatmap + output_flipped_heatmap
          ) * 0.5
  
      imshape = (
          (self.inputs["im_shape"].numpy())[:, ::-1]
          if "im_shape" in self.inputs
          else None
      )
      center = (
          self.inputs["center"].numpy()
          if "center" in self.inputs
          else np.round(imshape / 2.0)
      )
      scale = (
          self.inputs["scale"].numpy()
          if "scale" in self.inputs
          else imshape / 200.0
      )
  
      result = self.post_process(
          output_heatmap.cpu().numpy(), center, scale
      )
  
      return result
  
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, serializable
  from .meta_arch import BaseArch
  from ..keypoint_utils import transform_preds
  from ..None import layers
label_desc: Use image node_id 4 for calling the VitPose_TopDown obj's underlying member method code with example usage: obj._forward_test() and returns: result