code: def fit_test_data(self):
      smoke_data = []
      for metric, estimator in zip(self.metrics, self.estimators):
          point = metric._space.random_point()
          points = gs.repeat(
              gs.expand_dims(point, 0), self.n_reps, axis=0
          )
  
          datum = dict(estimator=estimator, X=points, expected=point)
          smoke_data.append(datum)
  
      return smoke_data
  
imports: import geomstats.backend
  from geomstats.geometry.stratified.graph_space import ExhaustiveAligner, GraphSpace, _GeodesicToPointAligner
  from geomstats.learning.aac import _AACGGPCA, _AACFrechetMean, _AACRegression
  from geomstats.test.data import TestData
  from geomstats.test.test_case import np_backend
label_desc: Use image node_id 2 for calling the _TrivialMeanData obj's underlying member method code with example usage: obj.fit_test_data() and returns: smoke_data