code: def test_distance_symmetry_property_in_gpu():
      if not cuda.is_available():  # pragma: no cover
          pytest.skip("Skipping Tests No GPUs Available")
  
      # This test function raises an error if the distance between a subsequence
      # and another one does not satisfy the symmetry property.
      seed = 332
      np.random.seed(seed)
      T = np.random.uniform(-1000.0, 1000.0, [64])
      m = 3
  
      i, j = 2, 10
      # M_T, Σ_T = core.compute_mean_std(T, m)
      # Σ_T[i] is `650.912209452633`
      # Σ_T[j] is `722.0717285148525`
  
      # This test raises an error if arithmetic operation in ...
      # ... `gpu_stump._compute_and_update_PI_kernel` does not
      # generates the same result if values of variable for mean and std
      # are swapped.
  
      T_A = T[i : i + m]
      T_B = T[j : j + m]
  
      mp_AB = stumpy.gpu_stump(T_A, m, T_B)
      mp_BA = stumpy.gpu_stump(T_B, m, T_A)
  
      d_ij = mp_AB[0, 0]
      d_ji = mp_BA[0, 0]
  
      comp = d_ij - d_ji
      ref = 0.0
  
      npt.assert_almost_equal(comp, ref, decimal=15)
  
file_path: stumpy/tests/test_precision.py
imports: import functools
  from unittest.mock import patch
  import naive
  import numpy
  import numpy.testing
  import pytest
  from numba import cuda
  import stumpy
  from stumpy import config, core
label_desc: Use image node_id 5 for calling a global function with example usage: test_distance_symmetry_property_in_gpu() without return types