code: def test_metric_norm_factor_gradient(
      self, expected_norm_factor, expected_norm_factor_gradient, atol
  ):
      (
          norm_factor,
          norm_factor_gradient,
      ) = self.model.space.metric.norm_factor_gradient(
          self.model.variances
      )
  
      self.assertAllClose(norm_factor, expected_norm_factor, atol=atol)
      self.assertAllClose(
          norm_factor_gradient, expected_norm_factor_gradient, atol=atol
      )
  
file_path: geomstats/geomstats/test_cases/learning/expectation_maximization.py
imports: import pytest
  import geomstats.backend
  from geomstats.test.test_case import TestCase
  from geomstats.test_cases.learning._base import BaseEstimatorTestCase
label_desc: Use image node_id 4 for calling the GaussianMixtureModelTestCase obj's underlying member method code with example usage: obj.test_metric_norm_factor_gradient(expected_norm_factor, expected_norm_factor_gradient, atol) without return types