code: def test_against_linear_mean(self, n_samples, atol):
      X = self.data_generator.random_point(n_points=n_samples)
  
      optimizer = GradientDescent()
      res = optimizer.minimize(self.estimator.space, X)
  
      expected = self.estimator.fit(X).estimate_
  
      self.assertAllClose(res, expected, atol=atol)
  
file_path: geomstats/tests/tests_geomstats/test_learning/test_exponential_barycenter.py
imports: import random
  import pytest
  from geomstats.geometry.special_euclidean import SpecialEuclidean
  from geomstats.geometry.special_orthogonal import SpecialOrthogonal
  from geomstats.learning.exponential_barycenter import ExponentialBarycenter, GradientDescent
  from geomstats.learning.frechet_mean import FrechetMean
  from geomstats.test.parametrizers import DataBasedParametrizer
  from geomstats.test_cases.learning._base import BaseEstimatorTestCase, MeanEstimatorMixinsTestCase
  from geomstats.test_cases.learning.exponential_barycenter import EuclideanGroup
  from .data.exponential_barycenter import AgainstFrechetMeanTestData, AgainstLinearMeanTestData, ExponentialBarycenterTestData
label_desc: Use image node_id 1 for calling the TestAgainstLinearMean obj's underlying member method code with example usage: obj.test_against_linear_mean(n_samples, atol) without return types