code: def test_cuda_resampling():
      """Test CUDA resampling."""
      rng = np.random.RandomState(0)
      for window in ("boxcar", "triang"):
          for N in (997, 1000):  # one prime, one even
              a = rng.randn(2, N)
              for fro, to in ((1, 2), (2, 1), (1, 3), (3, 1)):
                  a1 = resample(
                      a,
                      fro,
                      to,
                      n_jobs=None,
                      npad="auto",
                      window=window,
                  )
                  a2 = resample(
                      a,
                      fro,
                      to,
                      n_jobs="cuda",
                      npad="auto",
                      window=window,
                  )
                  assert_allclose(a1, a2, rtol=1e-7, atol=1e-14)
      assert_array_almost_equal(a1, a2, 14)
      assert_array_equal(
          resample(np.zeros(2), 2, 1, n_jobs="cuda"), np.zeros(4)
      )
  
imports: import numpy
  import pytest
  from numpy.fft import fft, fftfreq
  from numpy.testing import assert_allclose, assert_almost_equal, assert_array_almost_equal, assert_array_equal, assert_array_less
  from scipy.signal import butter, freqz, sosfreqz
  from scipy.signal import resample
  from mne import Epochs, create_info
  from mne._fiff.pick import _DATA_CH_TYPES_SPLIT
  from mne.filter import _length_factors, _overlap_add_filter, _resample_stim_channels, _smart_pad, construct_iir_filter, create_filter, design_mne_c_filter, detrend, estimate_ringing_samples, filter_data, notch_filter, resample
  from mne.io import RawArray, read_raw_fif
  from mne.utils import catch_logging, requires_mne, run_subprocess, sum_squared
label_desc: Use image node_id 17 for calling a global function with example usage: test_cuda_resampling() without return types