Merge master into move_tests_folder

Author: vlad-perevezentsev

.github/workflows/conda-package.yml

@@ -19,54 +19,6 @@ env:
   RERUN_TESTS_ON_FAILURE: 'true'
   RUN_TESTS_MAX_ATTEMPTS: 2
   TEST_ENV_NAME: 'test'
-  TEST_SCOPE: >-
-      dpnp.tests.test_absolute
-      dpnp.tests.test_amin_amax
-      dpnp.tests.test_arithmetic
-      dpnp.tests.test_arraycreation
-      dpnp.tests.test_arraymanipulation
-      dpnp.tests.test_arraypad
-      dpnp.tests.test_bitwise
-      dpnp.tests.test_copy
-      dpnp.tests.test_counting
-      dpnp.tests.test_fft
-      dpnp.tests.test_fill
-      dpnp.tests.test_flat
-      dpnp.tests.test_histogram
-      dpnp.tests.test_indexing
-      dpnp.tests.test_linalg
-      dpnp.tests.test_logic
-      dpnp.tests.test_manipulation
-      dpnp.tests.test_mathematical
-      dpnp.tests.test_mixins
-      dpnp.tests.test_nanfunctions
-      dpnp.tests.test_ndarray
-      dpnp.tests.test_outer
-      dpnp.tests.test_product
-      dpnp.tests.test_random_state
-      dpnp.tests.test_search
-      dpnp.tests.test_sort
-      dpnp.tests.test_special
-      dpnp.tests.test_statistics
-      dpnp.tests.test_sum
-      dpnp.tests.test_sycl_queue
-      dpnp.tests.test_umath
-      dpnp.tests.test_usm_type
-      dpnp.tests.third_party.cupy.core_tests
-      dpnp.tests.third_party.cupy.fft_tests
-      dpnp.tests.third_party.cupy.creation_tests
-      dpnp.tests.third_party.cupy.indexing_tests
-      dpnp.tests.third_party.cupy.lib_tests
-      dpnp.tests.third_party.cupy.linalg_tests
-      dpnp.tests.third_party.cupy.logic_tests
-      dpnp.tests.third_party.cupy.manipulation_tests
-      dpnp.tests.third_party.cupy.math_tests
-      dpnp.tests.third_party.cupy.padding_tests
-      dpnp.tests.third_party.cupy.sorting_tests
-      dpnp.tests.third_party.cupy.statistics_tests.test_histogram
-      dpnp.tests.third_party.cupy.statistics_tests.test_meanvar
-      dpnp.tests.third_party.cupy.test_ndim
-      dpnp.tests.third_party.cupy.test_type_routines
   VER_JSON_NAME: 'version.json'
   VER_SCRIPT1: "import json; f = open('version.json', 'r'); j = json.load(f); f.close(); "
   VER_SCRIPT2: "d = j['dpnp'][0]; print('='.join((d[s] for s in ('version', 'build'))))"

.github/workflows/generate_coverage.yaml

@@ -109,7 +109,7 @@ jobs:
             conda activate coverage
             [ -f /opt/intel/oneapi/setvars.sh ] && source /opt/intel/oneapi/setvars.sh
             git clean -fxd
-            python scripts/gen_coverage.py --pytest-opts="--ignore dpnp/tests/test_random.py" --verbose
+            python scripts/gen_coverage.py --verbose
 
       - name: Total number of coverage attempts
         run: |

dpnp/dpnp_iface_manipulation.py

@@ -63,6 +63,7 @@
     "atleast_2d",
     "atleast_3d",
     "broadcast_arrays",
+    "broadcast_shapes",
     "broadcast_to",
     "can_cast",
     "column_stack",
@@ -967,6 +968,41 @@ def broadcast_arrays(*args, subok=False):
     return [dpnp_array._create_from_usm_ndarray(a) for a in usm_arrays]
 
 
+def broadcast_shapes(*args):
+    """
+    Broadcast the input shapes into a single shape.
+
+    For full documentation refer to :obj:`numpy.broadcast_shapes`.
+
+    Parameters
+    ----------
+    *args : tuples of ints, or ints
+        The shapes to be broadcast against each other.
+
+    Returns
+    -------
+    tuple
+        Broadcasted shape.
+
+    See Also
+    --------
+    :obj:`dpnp.broadcast_arrays` : Broadcast any number of arrays against
+                                   each other.
+    :obj:`dpnp.broadcast_to` : Broadcast an array to a new shape.
+
+    Examples
+    --------
+    >>> import dpnp as np
+    >>> np.broadcast_shapes((1, 2), (3, 1), (3, 2))
+    (3, 2)
+    >>> np.broadcast_shapes((6, 7), (5, 6, 1), (7,), (5, 1, 7))
+    (5, 6, 7)
+
+    """
+
+    return numpy.broadcast_shapes(*args)
+
+
 # pylint: disable=redefined-outer-name
 def broadcast_to(array, /, shape, subok=False):
     """

dpnp/dpnp_iface_mathematical.py

@@ -994,8 +994,7 @@ def cross(a, b, axisa=-1, axisb=-1, axisc=-1, axis=None):
     a_shape = a.shape
     b_shape = b.shape
 
-    # TODO: replace with dpnp.broadcast_shapes once implemented
-    res_shape = numpy.broadcast_shapes(a_shape[:-1], b_shape[:-1])
+    res_shape = dpnp.broadcast_shapes(a_shape[:-1], b_shape[:-1])
     if a_shape[:-1] != res_shape:
         a = dpnp.broadcast_to(a, res_shape + (a_shape[-1],))
         a_shape = a.shape

dpnp/tests/test_manipulation.py

@@ -332,6 +332,31 @@ def test_no_copy(self):
         assert_array_equal(b, a)
 
 
+class TestBroadcast:
+    @pytest.mark.parametrize(
+        "shape",
+        [
+            [(1,), (3,)],
+            [(1, 3), (3, 3)],
+            [(3, 1), (3, 3)],
+            [(1, 3), (3, 1)],
+            [(1, 1), (3, 3)],
+            [(1, 1), (1, 3)],
+            [(1, 1), (3, 1)],
+            [(1, 0), (0, 0)],
+            [(0, 1), (0, 0)],
+            [(1, 0), (0, 1)],
+            [(1, 1), (0, 0)],
+            [(1, 1), (1, 0)],
+            [(1, 1), (0, 1)],
+        ],
+    )
+    def test_broadcast_shapes(self, shape):
+        expected = numpy.broadcast_shapes(*shape)
+        result = dpnp.broadcast_shapes(*shape)
+        assert_equal(result, expected)
+
+
 class TestDelete:
     @pytest.mark.parametrize(
         "obj", [slice(0, 4, 2), 3, [2, 3]], ids=["slice", "int", "list"]