code: def inner_product_derivative_matrix_test_data(self):
      base_points = [gs.array([0.6, -1.0]), gs.array([0.8, -0.8])]
      data = []
      for base_point in base_points:
          (
              expected_1,
              expected_2,
          ) = _expected_sphere_inner_product_derivativ_matrix(
              base_point
          )
          data.append(
              dict(
                  base_point=base_point,
                  expected_1=expected_1,
                  expected_2=expected_2,
              )
          )
      return self.generate_tests(data)
  
imports: import geomstats.backend
  from geomstats.test.data import TestData
  from .riemannian_metric import RiemannianMetricComparisonTestData, RiemannianMetricTestData
label_desc: Use image node_id 5 for calling the SphereIntrinsicMetricTestData obj's underlying member method code with example usage: obj.inner_product_derivative_matrix_test_data() and returns: self