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1 change: 1 addition & 0 deletions CHANGELOG.md
Original file line number Diff line number Diff line change
Expand Up @@ -30,6 +30,7 @@ This release is compatible with NumPy 2.5.
### Removed

* Removed support for arrays of 2-dimensional vectors in `dpnp.cross`, which now requires (arrays of) 3-dimensional vectors and raises `ValueError` otherwise [#2950](https://github.com/IntelPython/dpnp/pull/2950)
* Removed `dpnp.row_stack` in favor of `dpnp.vstack` [#2956](https://github.com/IntelPython/dpnp/pull/2956)

### Fixed

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1 change: 0 additions & 1 deletion doc/reference/array-manipulation.rst
Original file line number Diff line number Diff line change
Expand Up @@ -95,7 +95,6 @@ Joining arrays
hstack
dstack
column_stack
row_stack


Splitting arrays
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2 changes: 0 additions & 2 deletions dpnp/__init__.py
Original file line number Diff line number Diff line change
Expand Up @@ -217,7 +217,6 @@
roll,
rollaxis,
rot90,
row_stack,
shape,
size,
split,
Expand Down Expand Up @@ -720,7 +719,6 @@
"roll",
"rollaxis",
"rot90",
"row_stack",
"shape",
"size",
"split",
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6 changes: 0 additions & 6 deletions dpnp/dpnp_iface_manipulation.py
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Expand Up @@ -4606,9 +4606,6 @@ def vstack(tup, *, dtype=None, casting="same_kind"):
"""
Stack arrays in sequence vertically (row wise).

:obj:`dpnp.row_stack` is an alias for :obj:`dpnp.vstack`.
They are the same function.

For full documentation refer to :obj:`numpy.vstack`.

Parameters
Expand Down Expand Up @@ -4670,6 +4667,3 @@ def vstack(tup, *, dtype=None, casting="same_kind"):
if not isinstance(arrs, list):
arrs = [arrs]
return dpnp.concatenate(arrs, axis=0, dtype=dtype, casting=casting)


row_stack = vstack
29 changes: 0 additions & 29 deletions dpnp/tests/third_party/cupy/manipulation_tests/test_join.py
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Expand Up @@ -525,32 +525,3 @@ def test_stack_casting(self, xp, dtype1, dtype2, casting):
b = testing.shaped_arange((3, 4), xp, dtype1)
# may raise TypeError or ComplexWarning
return xp.stack((a, b), dtype=dtype2, casting=casting)

@pytest.mark.filterwarnings("ignore::DeprecationWarning")
@testing.with_requires("numpy>=2.0")
@testing.for_all_dtypes(name="dtype1")
@testing.for_all_dtypes(name="dtype2")
@testing.numpy_cupy_array_equal(type_check=has_support_aspect64())
def test_row_stack(self, xp, dtype1, dtype2):
a = testing.shaped_arange((4, 3), xp, dtype1)
b = testing.shaped_arange((3,), xp, dtype2)
c = testing.shaped_arange((2, 3), xp, dtype1)
return xp.row_stack((a, b, c))

def test_row_stack_wrong_ndim1(self):
a = cupy.zeros(())
b = cupy.zeros((3,))
with pytest.raises(ValueError): # pytest.warns(DeprecationWarning):
cupy.row_stack((a, b))

def test_row_stack_wrong_ndim2(self):
a = cupy.zeros((3, 2, 3))
b = cupy.zeros((3, 2))
with pytest.raises(ValueError): # pytest.warns(DeprecationWarning):
cupy.row_stack((a, b))

def test_row_stack_wrong_shape(self):
a = cupy.zeros((3, 2))
b = cupy.zeros((4, 3))
with pytest.raises(ValueError): # pytest.warns(DeprecationWarning):
cupy.row_stack((a, b))
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