code: def test_gpu_stimp(T, m):
      if not cuda.is_available():  # pragma: no cover
          pytest.skip("Skipping Tests No GPUs Available")
  
      if T.ndim > 1:
          T = T.copy()
          T = T[0]
      n = 3
      seed = np.random.randint(100000)
  
      np.random.seed(seed)
      ref = stumpy.gpu_aamp_stimp(T, m)
      for i in range(n):
          ref.update()
  
      np.random.seed(seed)
      cmp = stumpy.gpu_stimp(T, m, normalize=False)
      for i in range(n):
          cmp.update()
  
      # Compare raw pan
      ref_PAN = ref._PAN
      cmp_PAN = cmp._PAN
  
      naive.replace_inf(ref_PAN)
      naive.replace_inf(cmp_PAN)
  
      npt.assert_almost_equal(ref_PAN, cmp_PAN)
  
      # Compare transformed pan
      npt.assert_almost_equal(ref.PAN_, cmp.PAN_)
  
imports: import naive
  import numpy
  import numpy.testing
  from dask.distributed import Client, LocalCluster
  from numba import cuda
  import stumpy
  from stumpy.maamp import maamp_multi_distance_profile
  from stumpy.mstump import multi_distance_profile
  import pytest
label_desc: Use image node_id 28 for calling a global function with example usage: test_gpu_stimp(T, m) without return types