Unskip linalg tests due to fix in gh-2212

Author: vlad-perevezentsev

dpnp/tests/test_linalg.py

@@ -331,7 +331,6 @@ def test_complex(self, dtype, shape, p):
         expected = numpy.linalg.cond(a, p=p)
         assert_dtype_allclose(result, expected)
 
-    @pytest.mark.skipif(is_cuda_device(), reason="SAT-7589")
     @pytest.mark.parametrize(
         "p", [None, -dpnp.inf, -2, -1, 1, 2, dpnp.inf, "fro"]
     )
@@ -1820,9 +1819,6 @@ class TestLstsq:
         ],
     )
     def test_lstsq(self, a_shape, b_shape, dtype):
-        if is_cuda_device():
-            if a_shape == (2, 4):
-                pytest.skip("SAT-7589")
         a_np = numpy.random.rand(*a_shape).astype(dtype)
         b_np = numpy.random.rand(*b_shape).astype(dtype)
 
@@ -2197,9 +2193,6 @@ def test_1D_complex(self, dtype, ord, axis, keepdims):
     )
     @pytest.mark.parametrize("keepdims", [True, False])
     def test_2D(self, dtype, ord, axis, keepdims):
-        if is_cuda_device():
-            if ord in [-2, 2, "nuc"] and axis == None:
-                pytest.skip("SAT-7589")
         a = generate_random_numpy_array((3, 5), dtype)
         ia = dpnp.array(a)
         if (axis in [-1, 0, 1] and ord in ["nuc", "fro"]) or (
@@ -2225,9 +2218,6 @@ def test_2D(self, dtype, ord, axis, keepdims):
     )
     @pytest.mark.parametrize("keepdims", [True, False])
     def test_2D_complex(self, dtype, ord, axis, keepdims):
-        if is_cuda_device():
-            if ord in [-2, 2, "nuc"] and axis == None:
-                pytest.skip("SAT-7589")
         x1 = numpy.random.uniform(-5, 5, 15)
         x2 = numpy.random.uniform(-5, 5, 15)
         a = numpy.array(x1 + 1j * x2, dtype=dtype).reshape(3, 5)
@@ -2257,9 +2247,6 @@ def test_2D_complex(self, dtype, ord, axis, keepdims):
     )
     @pytest.mark.parametrize("keepdims", [True, False])
     def test_ND(self, dtype, ord, axis, keepdims):
-        if is_cuda_device():
-            if ord in [-2, 2, "nuc"] and axis == (0, 1):
-                pytest.skip("SAT-7589")
         a = generate_random_numpy_array((2, 3, 4, 5), dtype)
         ia = dpnp.array(a)
         if (axis in [-1, 0, 1] and ord in ["nuc", "fro"]) or (
@@ -2291,9 +2278,6 @@ def test_ND(self, dtype, ord, axis, keepdims):
     )
     @pytest.mark.parametrize("keepdims", [True, False])
     def test_ND_complex(self, dtype, ord, axis, keepdims):
-        if is_cuda_device():
-            if ord in [-2, 2, "nuc"] and axis == (0, 1):
-                pytest.skip("SAT-7589")
         x1 = numpy.random.uniform(-5, 5, 120)
         x2 = numpy.random.uniform(-5, 5, 120)
         a = numpy.array(x1 + 1j * x2, dtype=dtype).reshape(2, 3, 4, 5)
@@ -2327,9 +2311,6 @@ def test_ND_complex(self, dtype, ord, axis, keepdims):
     )
     @pytest.mark.parametrize("keepdims", [True, False])
     def test_usm_ndarray(self, dtype, ord, axis, keepdims):
-        if is_cuda_device():
-            if ord in [-2, 2, "nuc"] and axis in [(0, 1), (-2, -1)]:
-                pytest.skip("SAT-7589")
         a = numpy.array(numpy.random.uniform(-5, 5, 120), dtype=dtype).reshape(
             2, 3, 4, 5
         )
@@ -2407,9 +2388,6 @@ def test_strided_ND(self, axis, stride):
     )
     @pytest.mark.parametrize("keepdims", [True, False])
     def test_matrix_norm(self, ord, keepdims):
-        if is_cuda_device():
-            if ord in [-2, 2, "nuc"]:
-                pytest.skip("SAT-7589")
         a = numpy.array(numpy.random.uniform(-5, 5, 15)).reshape(3, 5)
         ia = dpnp.array(a)
 
@@ -2951,9 +2929,6 @@ def check_decomposition(
         ids=["(2, 2)", "(3, 4)", "(5, 3)", "(16, 16)"],
     )
     def test_svd(self, dtype, shape):
-        if is_cuda_device():
-            if shape == (3, 4):
-                pytest.skip("SAT-7589")
         a = numpy.arange(shape[0] * shape[1], dtype=dtype).reshape(shape)
         dp_a = dpnp.array(a)
 
@@ -3023,9 +2998,6 @@ class TestSvdvals:
         ids=["(3, 5)", "(4, 2)", "(2, 3, 3)", "(3, 5, 2)"],
     )
     def test_svdvals(self, dtype, shape):
-        if is_cuda_device():
-            if shape == (3, 5):
-                pytest.skip("SAT-7589")
         a = numpy.arange(numpy.prod(shape), dtype=dtype).reshape(shape)
         dp_a = dpnp.array(a)
 
@@ -3096,9 +3068,6 @@ def check_types_shapes(self, dp_B, np_B):
         ],
     )
     def test_pinv(self, dtype, shape):
-        if is_cuda_device():
-            if shape in [(3, 4), (2, 2, 4)]:
-                pytest.skip("SAT-7589")
         # Set seed_value=81 to prevent
         # random generation of the input singular matrix
         a = generate_random_numpy_array(shape, dtype, seed_value=81)

dpnp/tests/test_sycl_queue.py

@@ -16,7 +16,6 @@
     assert_dtype_allclose,
     generate_random_numpy_array,
     get_all_dtypes,
-    is_cuda_device,
     is_win_platform,
 )
 
@@ -1807,9 +1806,6 @@ def test_matrix_rank(data, tol, device):
     ids=["-1", "0", "1", "(0, 1)", "(-2, -1)", "None"],
 )
 def test_norm(device, ord, axis):
-    if is_cuda_device():
-        if axis in [(0, 1), (-2, -1)] and ord in [-2, 2, "nuc"]:
-            pytest.skip("SAT-7589")
     a = numpy.arange(120).reshape(2, 3, 4, 5)
     ia = dpnp.array(a, device=device)
     if (axis in [-1, 0, 1] and ord in ["nuc", "fro"]) or (
@@ -1909,9 +1905,6 @@ def test_qr(shape, mode, device):
     ],
 )
 def test_svd(shape, full_matrices, compute_uv, device):
-    if is_cuda_device():
-        if shape in [(1, 4), (2, 2, 3)]:
-            pytest.skip("SAT-7589")
     dtype = dpnp.default_float_type(device)
 
     count_elems = numpy.prod(shape)
@@ -2518,9 +2511,6 @@ def test_slogdet(shape, is_empty, device):
     ids=[device.filter_string for device in valid_devices],
 )
 def test_pinv(shape, hermitian, rcond_as_array, device):
-    if is_cuda_device():
-        if shape == (2, 2, 3):
-            pytest.skip("SAT-7589")
     dtype = dpnp.default_float_type(device)
     # Set seed_value=81 to prevent
     # random generation of the input singular matrix

dpnp/tests/test_usm_type.py

@@ -546,9 +546,6 @@ def test_meshgrid(usm_type_x, usm_type_y):
     ids=["-1", "0", "1", "(0, 1)", "(-2, -1)", "None"],
 )
 def test_norm(usm_type, ord, axis):
-    if is_cuda_device():
-        if axis in [(0, 1), (-2, -1)] and ord in [-2, 2, "nuc"]:
-            pytest.skip("SAT-7589")
     ia = dp.arange(120, usm_type=usm_type).reshape(2, 3, 4, 5)
     if (axis in [-1, 0, 1] and ord in ["nuc", "fro"]) or (
         isinstance(axis, tuple) and ord == 3
@@ -1458,9 +1455,6 @@ def test_inv(shape, is_empty, usm_type):
     ],
 )
 def test_svd(usm_type, shape, full_matrices_param, compute_uv_param):
-    if is_cuda_device():
-        if shape in [(1, 4), (2, 2, 3)]:
-            pytest.skip("SAT-7589")
     x = dp.ones(shape, usm_type=usm_type)
 
     if compute_uv_param:
@@ -1529,9 +1523,6 @@ def test_matrix_rank(data, tol, usm_type):
     ],
 )
 def test_pinv(shape, hermitian, usm_type):
-    if is_cuda_device():
-        if shape == (2, 2, 3):
-            pytest.skip("SAT-7589")
     a_np = generate_random_numpy_array(shape, hermitian=hermitian)
     a = dp.array(a_np, usm_type=usm_type)
 

dpnp/tests/third_party/cupy/linalg_tests/test_norms.py

@@ -4,7 +4,7 @@
 import pytest
 
 import dpnp as cupy
-from dpnp.tests.helper import is_cpu_device, is_cuda_device
+from dpnp.tests.helper import is_cpu_device
 from dpnp.tests.third_party.cupy import testing
 
 
@@ -63,12 +63,6 @@ class TestNorm(unittest.TestCase):
     @testing.numpy_cupy_allclose(rtol=1e-3, atol=1e-4, type_check=False)
     # since dtype of sum is different in dpnp and NumPy, type_check=False
     def test_norm(self, xp, dtype):
-        if (
-            is_cuda_device()
-            and self.shape == (1, 2)
-            and self.ord in [-2, 2, "nuc"]
-        ):
-            pytest.skip("SAT-7589")
         a = testing.shaped_arange(self.shape, xp, dtype)
         res = xp.linalg.norm(a, self.ord, self.axis, self.keepdims)
         if xp == numpy and not isinstance(res, numpy.ndarray):

dpnp/tests/third_party/cupy/linalg_tests/test_solve.py

@@ -7,7 +7,6 @@
 from dpnp.tests.helper import (
     assert_dtype_allclose,
     has_support_aspect64,
-    is_cuda_device,
 )
 from dpnp.tests.third_party.cupy import testing
 from dpnp.tests.third_party.cupy.testing import _condition
@@ -246,23 +245,17 @@ def check_x(self, a_shape, rcond, dtype):
 
     def test_pinv(self):
         self.check_x((3, 3), rcond=1e-15)
-        # skip case where n < m on CUDA (SAT-7589)
-        if not is_cuda_device():
-            self.check_x((2, 4), rcond=1e-15)
+        self.check_x((2, 4), rcond=1e-15)
         self.check_x((3, 2), rcond=1e-15)
 
         self.check_x((4, 4), rcond=0.3)
-        # SAT-7589
-        if not is_cuda_device():
-            self.check_x((2, 5), rcond=0.5)
+        self.check_x((2, 5), rcond=0.5)
         self.check_x((5, 3), rcond=0.6)
 
-    @pytest.mark.skipif(is_cuda_device(), reason="SAT-7589")
     def test_pinv_batched(self):
         self.check_x((2, 3, 4), rcond=1e-15)
         self.check_x((2, 3, 4, 5), rcond=1e-15)
 
-    @pytest.mark.skipif(is_cuda_device(), reason="SAT-7589")
     def test_pinv_batched_vector_rcond(self):
         self.check_x((2, 3, 4), rcond=[0.2, 0.8])
         self.check_x((2, 3, 4, 5), rcond=[[0.2, 0.9, 0.1], [0.7, 0.2, 0.5]])
@@ -313,7 +306,6 @@ def check_invalid_shapes(self, a_shape, b_shape):
         with pytest.raises(cupy.linalg.LinAlgError):
             cupy.linalg.lstsq(a, b, rcond=None)
 
-    @pytest.mark.skipif(is_cuda_device(), reason="SAT-7589")
     def test_lstsq_solutions(self):
         # Compares numpy.linalg.lstsq and cupy.linalg.lstsq solutions for:
         #   a shapes range from (3, 3) to (5, 3) and (3, 5)