code: def test_logsumexp():
      """Test the logsumexp implementation against the scipy baseline result."""
  
      # Example data
      x = np.arange(24).reshape((3, 4, 2)).astype(np.float32)
  
      # Tensorly tensor
      tensor = tl.tensor(x)
  
      # Compare against scipy baseline result
      for axis in [0, 1, 2]:
          # Run tensorly logsumexp
          tensorly_result = tl.logsumexp(tensor, axis=axis)
          scipy_result = special.logsumexp(x, axis=axis)
          assert_allclose(tensorly_result, scipy_result)
  
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 21 for calling a global function with example usage: test_logsumexp() without return types