code: def func_out_allclose_test_data(self):
      # TODO: verify dtype
      smoke_data = [
          dict(
              func_name="array_from_sparse",
              kwargs={
                  "indices": [(0,)],
                  "data": [1.0],
                  "target_shape": (2,),
              },
              expected=gs.array([1.0, 0.0]),
          ),
          dict(
              func_name="array_from_sparse",
              kwargs={
                  "indices": [(0, 0), (0, 1), (1, 2)],
                  "data": [1.0, 2.0, 3.0],
                  "target_shape": (2, 3),
              },
              expected=gs.array([[1.0, 2.0, 0], [0, 0, 3.0]]),
          ),
          dict(
              func_name="array_from_sparse",
              kwargs={
                  "indices": [(0, 1, 1), (1, 1, 1)],
                  "data": [1.0, 2.0],
                  "target_shape": (2, 2, 2),
              },
              expected=gs.array(
                  [[[0.0, 0.0], [0.0, 1.0]], [[0.0, 0.0], [0.0, 2.0]]]
              ),
          ),
          dict(
              func_name="mat_from_diag_triu_tril",
              args=(gs.ones(2), gs.array([2.0]), gs.array([3.0])),
              expected=gs.array([[1.0, 2.0], [3.0, 1.0]]),
          ),
          dict(
              func_name="mat_from_diag_triu_tril",
              args=(
                  gs.ones(3),
                  gs.array([2.0, 3.0, 4.0]),
                  gs.array([5.0, 6.0, 7.0]),
              ),
              expected=gs.array(
                  [[1.0, 2.0, 3.0], [5.0, 1.0, 4.0], [6.0, 7.0, 1.0]]
              ),
          ),
          # TODO: add (proper) vectorization test
          dict(
              func_name="mat_from_diag_triu_tril",
              args=(
                  gs.ones((2, 2)),
                  gs.array([[2.0], [2.0]]),
                  gs.array([[3.0], [3.0]]),
              ),
              expected=gs.repeat(
                  gs.expand_dims(gs.array([[1.0, 2.0], [3.0, 1.0]]), 0),
                  2,
                  axis=0,
              ),
          ),
          dict(
              func_name="linalg.logm",
              args=[
                  gs.array(
                      [
                          [2.0, 0.0, 0.0],
                          [0.0, 3.0, 0.0],
                          [0.0, 0.0, 4.0],
                      ]
                  )
              ],
              expected=gs.array(
                  [
                      [0.693147180, 0.0, 0.0],
                      [0.0, 1.098612288, 0.0],
                      [0.0, 0.0, 1.38629436],
                  ]
              ),
          ),
          dict(
              func_name="linalg.logm",
              args=[
                  gs.array(
                      [
                          [1.0, 0.0, 0.0],
                          [0.0, 5.0, 0.0],
                          [0.0, 0.0, 6.0],
                      ]
                  )
              ],
              expected=gs.array(
                  [
                      [0.0, 0.0, 0.0],
                      [0.0, 1.609437912, 0.0],
                      [0.0, 0.0, 1.79175946],
                  ]
              ),
          ),
          dict(
              func_name="linalg.expm",
              args=[
                  gs.array(
                      [
                          [2.0, 0.0, 0.0],
                          [0.0, 3.0, 0.0],
                          [0.0, 0.0, 4.0],
                      ],
                  )
              ],
              expected=gs.array(
                  [
                      [7.38905609, 0.0, 0.0],
                      [0.0, 20.0855369, 0.0],
                      [0.0, 0.0, 54.5981500],
                  ]
              ),
          ),
          # TODO: uncomment or delete?
          # dict(
          #     func_name="linalg.expm",
          #     args=[gs.array([[1.0, 0.0, 0.0], [0.0, 5.0, 0.0], [0.0, 0.0, 6.0]])],
          #     expected=gs.array(
          #         [
          #             [2.718281828, 0.0, 0.0],
          #             [0.0, 148.413159, 0.0],
          #             [0.0, 0.0, 403.42879349],
          #         ],
          #     ),
          # ),
      ]
      smoke_data += self._take_data()
  
      return self.generate_tests(smoke_data)
  
file_path: geomstats/tests/tests_geomstats/test_backend/data/backend.py
imports: import geomstats.backend
  from geomstats.geometry.matrices import Matrices
  from geomstats.geometry.spd_matrices import SPDMatrices
  from geomstats.geometry.special_orthogonal import SpecialOrthogonal
  from geomstats.geometry.symmetric_matrices import SymmetricMatrices
  from geomstats.test.data import TestData
label_desc: Use image node_id 11 for calling the BackendTestData obj's underlying member method code with example usage: obj.func_out_allclose_test_data() and returns: self