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1 change: 1 addition & 0 deletions CHANGELOG.md
Original file line number Diff line number Diff line change
Expand Up @@ -22,6 +22,7 @@ This release is compatible with NumPy 2.4.5.
* Replaced `.pxi` includes in `dpnp.tensor` with modular `.pxd`/`.pyx` Cython imports [#2913](https://github.com/IntelPython/dpnp/pull/2913)
* Reimplemented `dpnp.eye` and `dpnp.tensor.eye` with a branchless kernel [gh-2937](https://github.com/IntelPython/dpnp/pull/2937)
* Cleaned up Python bindings for indexing functions, renaming `usm_ndarray_take` and `usm_ndarray_put` to `py_take` and `py_put` and refactoring validation [gh-2935](https://github.com/IntelPython/dpnp/pull/2935)
* Changed `dpnp.broadcast_arrays` and `dpnp.tensor.broadcast_arrays` to return a tuple instead of a list, aligning with NumPy 2.x behavior and 2025.12 version of the Python array API standard [#2944](https://github.com/IntelPython/dpnp/pull/2944)

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What do you mean by NumPy 2.x? Is it known where it will be done? NumPy 2.5? Then should explicitly state that.


### Deprecated

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12 changes: 6 additions & 6 deletions dpnp/dpnp_iface_manipulation.py
Original file line number Diff line number Diff line change
Expand Up @@ -1060,8 +1060,8 @@ def broadcast_arrays(*args, subok=False):

Returns
-------
out : list of dpnp.ndarray
A list of arrays which are views on the original arrays from `args`.
out : tuple of dpnp.ndarray
A tuple of arrays which are views on the original arrays from `args`.

Limitations
-----------
Expand All @@ -1078,20 +1078,20 @@ def broadcast_arrays(*args, subok=False):
>>> x = np.array([[1, 2, 3]])
>>> y = np.array([[4], [5]])
>>> np.broadcast_arrays(x, y)
[array([[1, 2, 3],
(array([[1, 2, 3],
[1, 2, 3]]), array([[4, 4, 4],
[5, 5, 5]])]
[5, 5, 5]]))

"""

if subok is not False:
raise NotImplementedError(f"subok={subok} is currently not supported")

if len(args) == 0:
return []
return ()

usm_arrays = dpt.broadcast_arrays(*[dpnp.get_usm_ndarray(a) for a in args])
return [dpnp_array._create_from_usm_ndarray(a) for a in usm_arrays]
return tuple(dpnp_array._create_from_usm_ndarray(a) for a in usm_arrays)


def broadcast_shapes(*args):
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6 changes: 3 additions & 3 deletions dpnp/tensor/_manipulation_functions.py
Original file line number Diff line number Diff line change
Expand Up @@ -228,8 +228,8 @@ def broadcast_arrays(*args):
broadcasted.

Returns:
List[usm_ndarray]:
A list of broadcasted arrays. Each array
tuple[usm_ndarray, ...]:
A tuple of broadcasted arrays. Each array
must have the same shape. Each array must have the same `dtype`,
`device` and `usm_type` attributes as its corresponding input
array.
Expand All @@ -245,7 +245,7 @@ def broadcast_arrays(*args):
if all(X.shape == shape for X in args):
return args

return [broadcast_to(X, shape) for X in args]
return tuple(broadcast_to(X, shape) for X in args)


def broadcast_to(X, /, shape):
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2 changes: 1 addition & 1 deletion dpnp/tests/test_arraymanipulation.py
Original file line number Diff line number Diff line change
Expand Up @@ -289,7 +289,7 @@ def test_incompatible_shapes_raise_valueerror(self, shapes):
self.assert_broadcast_arrays_raise(input_shapes[::-1])

def test_broadcast_arrays_empty_input(self):

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Missed to update dpnp/tests/third_party/cupy/manipulation_tests/test_dims.py with the latest changed (including new test added there for that use case)

assert dpnp.broadcast_arrays() == []
assert dpnp.broadcast_arrays() == ()

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Seems we don't have an explicit type assertion in any tensor or dpnp tests, excluding use case with empty input.


def test_subok_error(self):
x = dpnp.ones(4)
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