Add dpnp.broadcast_shapes implementation

Author: ekomarova

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

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"]