code: def test_regularization_loss(self) -> None:
      criterion = PMSNLoss()
      mean_anchor_probs = torch.Tensor([0.1, 0.3, 0.6])
      loss = criterion.regularization_loss(
          mean_anchor_probs=mean_anchor_probs
      )
      norm = 1 / (1**0.25) + 1 / (2**0.25) + 1 / (3**0.25)
      t0 = 1 / (1**0.25) / norm
      t1 = 1 / (2**0.25) / norm
      t2 = 1 / (3**0.25) / norm
      loss = criterion.regularization_loss(
          mean_anchor_probs=mean_anchor_probs
      )
      expected_loss = (
          t0 * math.log(t0 / 0.1)
          + t1 * math.log(t1 / 0.3)
          + t2 * math.log(t2 / 0.6)
      )
      assert loss == pytest.approx(expected_loss)
  
file_path: lightly/tests/loss/test_PMSNLoss.py
imports: import math
  import unittest
  import pytest
  import torch
  from torch import Tensor
  from lightly.loss import pmsn_loss
  from lightly.loss.pmsn_loss import PMSNCustomLoss, PMSNLoss
label_desc: Use image node_id 1 for calling the TestPMSNLoss obj's underlying member method code with example usage: obj.test_regularization_loss() without return types