update tests

Author: npolina4

dpnp/dpnp_iface_libmath.py

@@ -81,7 +81,7 @@ def erf(in_array1):
     x1_desc = dpnp.get_dpnp_descriptor(
         in_array1, copy_when_strides=False, copy_when_nondefault_queue=False
     )
-    if x1_desc and dpnp.is_cuda_backend(in_array1):
+    if x1_desc and not dpnp.is_cuda_backend(in_array1):
         return dpnp_erf(x1_desc).get_pyobj()
 
     result = create_output_descriptor_py(

dpnp/random/dpnp_random_state.py

@@ -82,8 +82,6 @@ def __init__(self, seed=None, device=None, sycl_queue=None):
             device=device, sycl_queue=sycl_queue
         )
 
-        dpnp.not_implemented_for_cuda_backend(self._sycl_queue)
-
         self._sycl_device = self._sycl_queue.sycl_device
 
         is_cpu = self._sycl_device.is_cpu

tests/skipped_tests_cuda.tbl

@@ -1,6 +1,7 @@
 import unittest
 
 import numpy
+import pytest
 
 from tests.helper import has_support_aspect64
 from tests.third_party.cupy import testing
@@ -9,6 +10,7 @@
 class TestArithmetic(unittest.TestCase):
     @testing.for_float_dtypes()
     @testing.numpy_cupy_allclose()
+    @pytest.mark.usefixtures("allow_fall_back_on_numpy")
     def test_modf_part1(self, xp, dtype):
         a = xp.array([-2.5, -1.5, -0.5, 0, 0.5, 1.5, 2.5], dtype=dtype)
         b, _ = xp.modf(a)
@@ -17,6 +19,7 @@ def test_modf_part1(self, xp, dtype):
 
     @testing.for_float_dtypes()
     @testing.numpy_cupy_allclose()
+    @pytest.mark.usefixtures("allow_fall_back_on_numpy")
     def test_modf_part2(self, xp, dtype):
         a = xp.array([-2.5, -1.5, -0.5, 0, 0.5, 1.5, 2.5], dtype=dtype)
         _, c = xp.modf(a)

tests/test_arithmetic.py

@@ -718,7 +718,7 @@ class TestTakeAlongAxis:
         ],
     )
     def test_argequivalent(self, func, argfunc, kwargs):
-        a = dpnp.random.random(size=(3, 4, 5))
+        a = dpnp.asarray(numpy.random.random(size=(3, 4, 5)))
 
         for axis in list(range(a.ndim)) + [None]:
             a_func = func(a, axis=axis, **kwargs)

tests/test_indexing.py

@@ -396,12 +396,15 @@ def test_elemwise_comparison(op, x1, x2, dtype):
     "sh2", [[12], [4, 8], [1, 8, 6]], ids=["(12,)", "(4, 8)", "(1, 8, 6)"]
 )
 def test_comparison_no_broadcast_with_shapes(op, sh1, sh2):
-    x1, x2 = dpnp.random.randn(*sh1), dpnp.random.randn(*sh2)
+    x1_np = numpy.random.randn(*sh1)
+    x2_np = numpy.random.randn(*sh2)
+    x1 = dpnp.asarray(x1_np)
+    x2 = dpnp.asarray(x2_np)
 
     # x1 OP x2
     with pytest.raises(ValueError):
         getattr(dpnp, op)(x1, x2)
-        getattr(numpy, op)(x1.asnumpy(), x2.asnumpy())
+        getattr(numpy, op)(x1_np, x2_np)
 
 
 @pytest.mark.parametrize(

tests/test_logic.py

@@ -45,6 +45,7 @@ def check_seed(self, dist_name, params):
         assert_allclose(a1, a2, rtol=1e-07, atol=0)
 
 
+@pytest.mark.usefixtures("allow_fall_back_on_numpy")
 @pytest.mark.parametrize(
     "func",
     [dpnp.random.chisquare, dpnp.random.rand, dpnp.random.randn],
@@ -61,6 +62,7 @@ def test_input_size(func):
     assert output_shape == res.shape
 
 
+@pytest.mark.usefixtures("allow_fall_back_on_numpy")
 @pytest.mark.parametrize(
     "func",
     [
@@ -82,6 +84,7 @@ def test_input_shape(func):
     assert shape == res.shape
 
 
+@pytest.mark.usefixtures("allow_fall_back_on_numpy")
 @pytest.mark.parametrize(
     "func",
     [
@@ -104,6 +107,7 @@ def test_check_output(func):
     assert dpnp.all(res < 1)
 
 
+@pytest.mark.usefixtures("allow_fall_back_on_numpy")
 @pytest.mark.parametrize(
     "func",
     [
@@ -130,6 +134,7 @@ def test_seed(func):
     assert_allclose(a1, a2, rtol=1e-07, atol=0)
 
 
+@pytest.mark.usefixtures("allow_fall_back_on_numpy")
 def test_randn_normal_distribution():
     """
     Check the moments of the normal distribution sample obtained
@@ -667,6 +672,7 @@ def test_seed(self):
 
 
 @pytest.mark.skipif(not has_support_aspect64(), reason="Failed on Iris Xe")
+@pytest.mark.usefixtures("allow_fall_back_on_numpy")
 class TestDistributionsNormal(TestDistribution):
     def test_extreme_value(self):
         loc = 5
@@ -827,11 +833,13 @@ def test_seed(self):
         self.check_seed("rayleigh", {"scale": scale})
 
 
+@pytest.mark.usefixtures("allow_fall_back_on_numpy")
 class TestDistributionsStandardCauchy(TestDistribution):
     def test_seed(self):
         self.check_seed("standard_cauchy", {})
 
 
+@pytest.mark.usefixtures("allow_fall_back_on_numpy")
 class TestDistributionsStandardExponential(TestDistribution):
     def test_moments(self):
         shape = 0.8
@@ -867,6 +875,7 @@ def test_seed(self):
         self.check_seed("standard_gamma", {"shape": 0.0})
 
 
+@pytest.mark.usefixtures("allow_fall_back_on_numpy")
 class TestDistributionsStandardNormal(TestDistribution):
     def test_moments(self):
         expected_mean = 0.0
@@ -944,6 +953,7 @@ def test_seed(self):
 
 
 @pytest.mark.skipif(not has_support_aspect64(), reason="Failed on Iris Xe")
+@pytest.mark.usefixtures("allow_fall_back_on_numpy")
 class TestDistributionsUniform(TestDistribution):
     def test_extreme_value(self):
         low = 1.0
@@ -1070,6 +1080,7 @@ def test_seed(self):
         self.check_seed("zipf", {"a": a})
 
 
+@pytest.mark.usefixtures("allow_fall_back_on_numpy")
 class TestPermutationsTestShuffle:
     @pytest.mark.parametrize(
         "dtype",

tests/test_random.py

@@ -366,6 +366,7 @@ def test_complex(self, dtype):
         assert result.dtype == expected.dtype
 
 
+@pytest.mark.usefixtures("allow_fall_back_on_numpy")
 @pytest.mark.parametrize("kth", [0, 1], ids=["0", "1"])
 @pytest.mark.parametrize("dtype", get_all_dtypes(no_none=True))
 @pytest.mark.parametrize(

tests/test_sort.py

@@ -18,6 +18,7 @@
 )
 
 
+@pytest.mark.usefixtures("allow_fall_back_on_numpy")
 @pytest.mark.parametrize(
     "dtype", get_all_dtypes(no_none=True, no_bool=True, no_complex=True)
 )

tests/test_statistics.py

@@ -1190,6 +1190,7 @@ def test_out_2in_1out(func, data1, data2, device):
     assert_sycl_queue_equal(result.sycl_queue, x2.sycl_queue)
 
 
+@pytest.mark.usefixtures("allow_fall_back_on_numpy")
 @pytest.mark.parametrize(
     "device",
     valid_devices,