update tests as poc, they pass

mne/tests/test_filter.py

@@ -16,6 +16,7 @@
 from scipy.signal import resample as sp_resample
 
 from mne import Epochs, create_info
+from mne.cuda import get_shared_mem
 from mne._fiff.pick import _DATA_CH_TYPES_SPLIT
 from mne.filter import (
     _length_factors,
@@ -408,6 +409,10 @@ def test_resample_scipy():
             err_msg = f"{N}: {window}"
             x_2_sp = sp_resample(x, 2 * N, window=window)
             for n_jobs in n_jobs_test:
+                if n_jobs == "cuda":
+                    tmp = x
+                    x = get_shared_mem(x.shape)
+                    x[:] = tmp
                 x_2 = resample(x, 2, 1, npad=0, window=window, n_jobs=n_jobs)
                 assert_allclose(x_2, x_2_sp, atol=1e-12, err_msg=err_msg)
             new_len = int(round(len(x) * (1.0 / 2.0)))
@@ -421,6 +426,12 @@ def test_resample_scipy():
 def test_n_jobs(n_jobs):
     """Test resampling against SciPy."""
     x = np.random.RandomState(0).randn(4, 100)
+
+    if n_jobs == "cuda":
+        tmp = x
+        x = get_shared_mem(x.shape)
+        x[:] = tmp
+
     y1 = resample(x, 2, 1, n_jobs=None)
     y2 = resample(x, 2, 1, n_jobs=n_jobs)
     assert_allclose(y1, y2)
@@ -846,6 +857,8 @@ def test_cuda_resampling():
             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)
+                x = get_shared_mem(a.shape)
+                x[:] = a 
                 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)