Improve logic of dpnp.outer()

dpnp/dpnp_iface_linearalgebra.py

@@ -40,6 +40,7 @@
 """
 
 
+from dpnp.dpnp_array import dpnp_array
 from dpnp.dpnp_algo import *
 from dpnp.dpnp_utils import *
 import dpnp
@@ -312,10 +313,15 @@ def outer(x1, x2, **kwargs):
 
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
-    x2_desc = dpnp.get_dpnp_descriptor(x2, copy_when_nondefault_queue=False)
-    if x1_desc and x2_desc and not kwargs:
-        return dpnp_outer(x1_desc, x2_desc).get_pyobj()
+    if not kwargs:
+        if isinstance(x1, dpnp_array) and isinstance(x2, dpnp_array):
+            ravel = lambda x: x.flatten() if x.ndim > 1 else x
+            return ravel(x1)[:, None] * ravel(x2)[None, :]
+
+        x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
+        x2_desc = dpnp.get_dpnp_descriptor(x2, copy_when_nondefault_queue=False)
+        if x1_desc and x2_desc:
+            return dpnp_outer(x1_desc, x2_desc).get_pyobj()
 
     return call_origin(numpy.outer, x1, x2, **kwargs)
 

tests/skipped_tests_gpu.tbl

@@ -286,7 +286,7 @@ tests/third_party/cupy/linalg_tests/test_einsum.py::TestEinSumError::test_too_fe
 tests/third_party/cupy/linalg_tests/test_einsum.py::TestEinSumError::test_too_many_dimension3
 tests/third_party/cupy/linalg_tests/test_einsum.py::TestListArgEinSumError::test_dim_mismatch3
 tests/third_party/cupy/linalg_tests/test_einsum.py::TestListArgEinSumError::test_too_many_dims3
-tests/third_party/cupy/linalg_tests/test_product.py::TestProduct::test_outer
+
 tests/third_party/cupy/linalg_tests/test_product.py::TestProduct::test_reversed_outer
 tests/third_party/cupy/linalg_tests/test_product.py::TestProduct::test_reversed_vdot
 tests/third_party/cupy/manipulation_tests/test_basic.py::TestCopytoFromScalar_param_7_{dst_shape=(0,), src=3.2}::test_copyto_where
@@ -347,8 +347,6 @@ tests/third_party/cupy/sorting_tests/test_sort.py::TestPartition_param_2_{extern
 tests/third_party/cupy/statistics_tests/test_correlation.py::TestCov::test_cov_empty
 tests/third_party/cupy/statistics_tests/test_meanvar.py::TestMeanVar::test_external_mean_axis
 
-tests/third_party/cupy/linalg_tests/test_product.py::TestProduct::test_multidim_outer
-
 tests/third_party/cupy/sorting_tests/test_sort.py::TestPartition_param_3_{external=True, length=20000}::test_partition_axis
 tests/third_party/cupy/sorting_tests/test_sort.py::TestPartition_param_3_{external=True, length=20000}::test_partition_negative_axis
 tests/third_party/cupy/sorting_tests/test_sort.py::TestPartition_param_3_{external=True, length=20000}::test_partition_none_axis

tests/test_outer.py

@@ -0,0 +1,77 @@
+import unittest
+from tests.third_party.cupy import testing
+
+import dpnp as dp
+import numpy as np
+
+from numpy.testing import assert_raises
+
+
+class TestOuter(unittest.TestCase):
+
+    @testing.for_all_dtypes()
+    @testing.numpy_cupy_allclose()
+    def test_two_vectors(self, xp, dtype):
+        a = xp.ones((10, ), dtype=dtype)
+        b = xp.linspace(-2, 2, 5, dtype=dtype)
+
+        return xp.outer(a, b)
+
+    @testing.for_all_dtypes()
+    @testing.numpy_cupy_allclose()
+    def test_two_matrix(self, xp, dtype):
+        a = xp.ones((10, 10, 10), dtype=dtype)
+        b = xp.full(shape=(3, 7), fill_value=42, dtype=dtype)
+
+        return xp.outer(a, b)
+
+    @testing.for_all_dtypes()
+    @testing.numpy_cupy_allclose()
+    def test_the_same_vector(self, xp, dtype):
+        a = xp.full(shape=(100, ), fill_value=7, dtype=dtype)
+        return xp.outer(a, a)
+
+    @testing.for_all_dtypes()
+    @testing.numpy_cupy_allclose()
+    def test_the_same_matrix(self, xp, dtype):
+        a = xp.arange(27, dtype=dtype).reshape(3, 3, 3)
+        return xp.outer(a, a)
+
+
+class TestScalarOuter(unittest.TestCase):
+
+    @unittest.skip("A scalar isn't currently supported as input")
+    @testing.for_all_dtypes()
+    @testing.numpy_cupy_allclose()
+    def test_first_is_scalar(self, xp, dtype):
+        scalar = xp.int64(4)
+        a = xp.arange(5**3, dtype=dtype).reshape(5, 5, 5)
+        return xp.outer(scalar, a)
+
+    @unittest.skip("A scalar isn't currently supported as input")
+    @testing.for_all_dtypes()
+    @testing.numpy_cupy_allclose()
+    def test_second_is_scalar(self, xp, dtype):
+        scalar = xp.int32(7)
+        a = xp.arange(5**3, dtype=dtype).reshape(5, 5, 5)
+        return xp.outer(a, scalar)
+
+    @unittest.skip("A scalar isn't currently supported as input")
+    @testing.numpy_cupy_array_equal()
+    def test_both_inputs_as_scalar(self, xp):
+        a = xp.int64(4)
+        b = xp.int32(17)
+        return xp.outer(a, b)
+
+
+class TestListOuter(unittest.TestCase):
+
+    def test_list(self):
+        a = np.arange(27).reshape(3, 3, 3)
+        b: list[list[list[int]]] = a.tolist()
+        dp_a = dp.array(a)
+
+        with assert_raises(NotImplementedError):
+            dp.outer(b, dp_a)
+            dp.outer(dp_a, b)
+            dp.outer(b, b)

tests/test_sycl_queue.py

@@ -180,6 +180,9 @@ def test_1in_1out(func, data, device):
         pytest.param("fmod",
                      [-3., -2., -1., 1., 2., 3.],
                      [2., 2., 2., 2., 2., 2.]),
+        pytest.param("matmul",
+                     [[1., 0.], [0., 1.]],
+                     [[4., 1.], [1., 2.]]),
         pytest.param("maximum",
                      [2., 3., 4.],
                      [1., 5., 2.]),
@@ -189,6 +192,9 @@ def test_1in_1out(func, data, device):
         pytest.param("multiply",
                      [0., 1., 2., 3., 4., 5., 6., 7., 8.],
                      [0., 1., 2., 0., 1., 2., 0., 1., 2.]),
+        pytest.param("outer",
+                     [0., 1., 2., 3., 4., 5.],
+                     [0., 1., 2., 0.]),
         pytest.param("power",
                      [0., 1., 2., 3., 4., 5.],
                      [1., 2., 3., 3., 2., 1.]),
@@ -198,9 +204,6 @@ def test_1in_1out(func, data, device):
         pytest.param("subtract",
                      [0., 1., 2., 3., 4., 5., 6., 7., 8.],
                      [0., 1., 2., 0., 1., 2., 0., 1., 2.]),
-        pytest.param("matmul",
-                     [[1., 0.], [0., 1.]],
-                     [[4., 1.], [1., 2.]]),
     ],
 )
 @pytest.mark.parametrize("device",
@@ -217,10 +220,8 @@ def test_2in_1out(func, data1, data2, device):
 
     numpy.testing.assert_array_equal(result, expected)
 
-    expected_queue = x1.get_array().sycl_queue
-    result_queue = result.get_array().sycl_queue
-
-    assert_sycl_queue_equal(result_queue, expected_queue)
+    assert_sycl_queue_equal(result.sycl_queue, x1.sycl_queue)
+    assert_sycl_queue_equal(result.sycl_queue, x2.sycl_queue)
 
 
 @pytest.mark.parametrize(