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change dimension values
Otherwise Intel OpenCL gets its integer arithmetic wrong.
1 parent 77c1977 commit bb03c86

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test/test_arraycontext.py

Lines changed: 10 additions & 10 deletions
Original file line numberDiff line numberDiff line change
@@ -468,7 +468,7 @@ def test_actx_ravel(actx_factory):
468468
actx = actx_factory()
469469
rng = default_rng()
470470
ndim = rng.integers(low=1, high=6)
471-
shape = tuple(rng.integers(2, 7, ndim))
471+
shape = tuple(rng.integers(2, 8, ndim))
472472

473473
assert_close_to_numpy(actx, lambda _np, ary: _np.ravel(ary),
474474
(rng.random(shape),))
@@ -715,7 +715,7 @@ def test_array_equal(actx_factory):
715715
def test_array_context_einsum_array_manipulation(actx_factory, spec):
716716
actx = actx_factory()
717717

718-
mat = actx.from_numpy(np.random.randn(10, 10))
718+
mat = actx.from_numpy(np.random.randn(16, 16))
719719
res = actx.to_numpy(actx.einsum(spec, mat,
720720
tagged=(FirstAxisIsElementsTag())))
721721
ans = np.einsum(spec, actx.to_numpy(mat))
@@ -730,8 +730,8 @@ def test_array_context_einsum_array_manipulation(actx_factory, spec):
730730
def test_array_context_einsum_array_matmatprods(actx_factory, spec):
731731
actx = actx_factory()
732732

733-
mat_a = actx.from_numpy(np.random.randn(5, 5))
734-
mat_b = actx.from_numpy(np.random.randn(5, 5))
733+
mat_a = actx.from_numpy(np.random.randn(16, 16))
734+
mat_b = actx.from_numpy(np.random.randn(16, 16))
735735
res = actx.to_numpy(actx.einsum(spec, mat_a, mat_b,
736736
tagged=(FirstAxisIsElementsTag())))
737737
ans = np.einsum(spec, actx.to_numpy(mat_a), actx.to_numpy(mat_b))
@@ -744,9 +744,9 @@ def test_array_context_einsum_array_matmatprods(actx_factory, spec):
744744
def test_array_context_einsum_array_tripleprod(actx_factory, spec):
745745
actx = actx_factory()
746746

747-
mat_a = actx.from_numpy(np.random.randn(7, 5))
748-
mat_b = actx.from_numpy(np.random.randn(5, 7))
749-
vec = actx.from_numpy(np.random.randn(7))
747+
mat_a = actx.from_numpy(np.random.randn(16, 4))
748+
mat_b = actx.from_numpy(np.random.randn(4, 16))
749+
vec = actx.from_numpy(np.random.randn(16))
750750
res = actx.to_numpy(actx.einsum(spec, mat_a, mat_b, vec,
751751
tagged=(FirstAxisIsElementsTag())))
752752
ans = np.einsum(spec,
@@ -1481,7 +1481,7 @@ def _twice(x):
14811481

14821482
actx = actx_factory()
14831483
ones = actx.thaw(actx.freeze(
1484-
actx.zeros(shape=(10, 4), dtype=np.float64) + 1
1484+
actx.zeros(shape=(16, 4), dtype=np.float64) + 1
14851485
))
14861486
np.testing.assert_allclose(actx.to_numpy(_twice(ones)),
14871487
actx.to_numpy(actx.compile(_twice)(ones)))
@@ -1572,11 +1572,11 @@ def test_compile_anonymous_function(actx_factory):
15721572
actx = actx_factory()
15731573
f = actx.compile(lambda x: 2*x+40)
15741574
np.testing.assert_allclose(
1575-
actx.to_numpy(f(1+actx.zeros((10, 4), "float64"))),
1575+
actx.to_numpy(f(1+actx.zeros((16, 4), "float64"))),
15761576
42)
15771577
f = actx.compile(partial(lambda x: 2*x+40))
15781578
np.testing.assert_allclose(
1579-
actx.to_numpy(f(1+actx.zeros((10, 4), "float64"))),
1579+
actx.to_numpy(f(1+actx.zeros((16, 4), "float64"))),
15801580
42)
15811581

15821582

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