code: def estimators(request):
      Metric = request.param
      space = SPDMatrices(n=2, equip=False).equip_with_metric(Metric)
      request.cls.estimator = RiemannianMinimumDistanceToMean(space)
  
file_path: geomstats/tests/tests_geomstats/test_learning/test_mdm.py
imports: import pytest
  from geomstats.geometry.spd_matrices import SPDAffineMetric, SPDEuclideanMetric, SPDLogEuclideanMetric, SPDMatrices
  from geomstats.learning.mdm import RiemannianMinimumDistanceToMean
  from geomstats.test.parametrizers import DataBasedParametrizer
  from geomstats.test_cases.learning.mdm import RiemannianMinimumDistanceToMeanTestCase
  from .data.mdm import RiemannianMinimumDistanceToMeanSPDEuclideanTestData, RiemannianMinimumDistanceToMeanSPDTestData
label_desc: Use image node_id 1 for calling a global function with example usage: estimators(request) without return types