code: def test_create_heatmaps(self):
      reference_scale = 195
      target_landmarks = torch.randint(0, 255, (1, 68, 2)).type(
          torch.float
      )  # simulated dataset
      bb = create_bounding_box(target_landmarks)
      centers = torch.stack(
          [
              bb[:, 2] - (bb[:, 2] - bb[:, 0]) / 2.0,
              bb[:, 3] - (bb[:, 3] - bb[:, 1]) / 2.0,
          ],
          dim=1,
      )
      centers[:, 1] = (
          centers[:, 1] - (bb[:, 3] - bb[:, 1]) * 0.12
      )  # Not sure where 0.12 comes from
      scales = (
          bb[:, 2] - bb[:, 0] + bb[:, 3] - bb[:, 1]
      ) / reference_scale
      heatmaps = create_target_heatmap(
          target_landmarks, centers, scales
      )
      preds = get_preds_fromhm(
          heatmaps.numpy(),
          centers.squeeze().numpy(),
          scales.squeeze().numpy(),
      )[1]
  
      assert np.allclose(preds, target_landmarks, atol=5)
  
file_path: face-alignment/test/test_utils.py
imports: import sys
  import unittest
  from face_alignment.utils import *
  import numpy
  import torch
label_desc: Use image node_id 4 for calling the Tester obj's underlying member method code with example usage: obj.test_create_heatmaps() without return types