code: def test_sum():
      rng = tl.check_random_state(0)
      tensor = tl.tensor(rng.random_sample((5, 6, 7)))
      all_kwargs = [
          {},
          {"axis": 1},
          {"axis": 1, "keepdims": True},
          {"axis": 1, "keepdims": False},
          {"keepdims": True},
          {"keepdims": False},
          {"axis": None, "keepdims": True},
          {"axis": (0, 2), "keepdims": True},
          {"axis": (0, 2), "keepdims": False},
          {"axis": (0, 2)},
      ]
      for kwargs in all_kwargs:
          np.testing.assert_allclose(
              tl.to_numpy(tl.sum(tensor, **kwargs)),
              np.sum(tl.to_numpy(tensor), **kwargs),
              rtol=1e-5,  # Single precision
              err_msg=f"Sum not same as numpy with kwargs: {kwargs}",
          )
  
imports: from concurrent.futures import ThreadPoolExecutor
  import pytest
  from time import time
  import numpy
  from scipy.linalg import svd
  from scipy import special
  import tensorly
  from ..None import backend
  from ..testing import assert_allclose, assert_array_equal, assert_equal, assert_, assert_array_almost_equal, assert_raises
  from tensorly.tenalg.svd import SVD_FUNS, svd_interface
label_desc: Use image node_id 19 for calling a global function with example usage: test_sum() without return types