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Updated dpnp.vstack function #1595

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merged 4 commits into from
Oct 16, 2023
Merged

Updated dpnp.vstack function #1595

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ddaf637
Update dpnp.vstack function.
npolina4 Oct 13, 2023
34d9338
Returned skip for broadcast_arrays tests
npolina4 Oct 13, 2023
660bdc4
Merge branch 'master' into update_vstack
antonwolfy Oct 13, 2023
b0f2bf6
address comments
npolina4 Oct 13, 2023
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61 changes: 51 additions & 10 deletions dpnp/dpnp_iface_manipulation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1548,20 +1548,61 @@ def unique(ar, **kwargs):
return call_origin(numpy.unique, ar, **kwargs)


def vstack(tup):
def vstack(tup, *, dtype=None, casting="same_kind"):
"""
Stack arrays in sequence vertically (row wise).

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

"""
Returns
-------
out : dpnp.ndarray
The array formed by stacking the given arrays, will be at least 2-D.

Limitations
-----------
Each array in `tup` is supported as either :class:`dpnp.ndarray`
or :class:`dpctl.tensor.usm_ndarray`. Otherwise ``TypeError`` exception
will be raised.
Parameters `dtype` and `casting` are supported with default value.
Otherwise the function will be executed sequentially on CPU.

# TODO:
# `call_origin` cannot convert sequence of array to sequence of
# nparray
tup_new = []
for tp in tup:
tpx = dpnp.asnumpy(tp) if not isinstance(tp, numpy.ndarray) else tp
tup_new.append(tpx)
See Also
--------
:obj:`dpnp.concatenate` : Join a sequence of arrays along an existing axis.
:obj:`dpnp.stack` : Join a sequence of arrays along a new axis.
:obj:`dpnp.hstack` : Stack arrays in sequence horizontally (column wise).
:obj:`dpnp.dstack` : Stack arrays in sequence depth wise (along third axis).
:obj:`dpnp.column_stack` : Stack 1-D arrays as columns into a 2-D array.
:obj:`dpnp.block` : Assemble an nd-array from nested lists of blocks.
:obj:`dpnp.split` : Split array into a list of multiple sub-arrays of equal size.
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return call_origin(numpy.vstack, tup_new)
Examples
--------
>>> import dpnp as np
>>> a = np.array([1, 2, 3])
>>> b = np.array([4, 5, 6])
>>> np.vstack((a, b))
array([[1, 2, 3],
[4, 5, 6]])

>>> a = np.array([[1], [2], [3]])
>>> b = np.array([[4], [5], [6]])
>>> np.vstack((a, b))
array([[1],
[2],
[3],
[4],
[5],
[6]])

"""

if not hasattr(tup, "__getitem__"):
raise TypeError(
"Arrays to stack must be passed as a sequence type such as list or tuple."
)
arrs = dpnp.atleast_2d(*tup)
if not isinstance(arrs, list):
arrs = [arrs]
return dpnp.concatenate(arrs, axis=0, dtype=dtype, casting=casting)
4 changes: 1 addition & 3 deletions tests/skipped_tests.tbl
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Expand Up @@ -34,8 +34,6 @@ tests/third_party/cupy/fft_tests/test_fft.py::TestFftn_param_23_{axes=None, norm

tests/third_party/intel/test_zero_copy_test1.py::test_dpnp_interaction_with_dpctl_memory

tests/test_arraymanipulation.py::TestVstack::test_generator

tests/test_linalg.py::test_cond[-1-[[1, 2, 3], [4, 5, 6], [7, 8, 9]]]
tests/test_linalg.py::test_cond[1-[[1, 2, 3], [4, 5, 6], [7, 8, 9]]]
tests/test_linalg.py::test_cond[-2-[[1, 0, -1], [0, 1, 0], [1, 0, 1]]]
Expand Down Expand Up @@ -450,7 +448,6 @@ tests/third_party/cupy/manipulation_tests/test_dims.py::TestBroadcast_param_8_{s
tests/third_party/cupy/manipulation_tests/test_dims.py::TestBroadcast_param_8_{shapes=[(2, 0, 1, 1, 3), (2, 1, 0, 0, 3)]}::test_broadcast_arrays
tests/third_party/cupy/manipulation_tests/test_dims.py::TestBroadcast_param_9_{shapes=[(0, 1, 1, 3), (2, 1, 0, 0, 3)]}::test_broadcast
tests/third_party/cupy/manipulation_tests/test_dims.py::TestBroadcast_param_9_{shapes=[(0, 1, 1, 3), (2, 1, 0, 0, 3)]}::test_broadcast_arrays

tests/third_party/cupy/manipulation_tests/test_dims.py::TestInvalidBroadcast_param_0_{shapes=[(3,), (2,)]}::test_invalid_broadcast
tests/third_party/cupy/manipulation_tests/test_dims.py::TestInvalidBroadcast_param_0_{shapes=[(3,), (2,)]}::test_invalid_broadcast_arrays
tests/third_party/cupy/manipulation_tests/test_dims.py::TestInvalidBroadcast_param_1_{shapes=[(3, 2), (2, 3)]}::test_invalid_broadcast
Expand All @@ -459,6 +456,7 @@ tests/third_party/cupy/manipulation_tests/test_dims.py::TestInvalidBroadcast_par
tests/third_party/cupy/manipulation_tests/test_dims.py::TestInvalidBroadcast_param_2_{shapes=[(3, 2), (3, 4)]}::test_invalid_broadcast_arrays
tests/third_party/cupy/manipulation_tests/test_dims.py::TestInvalidBroadcast_param_3_{shapes=[(0,), (2,)]}::test_invalid_broadcast
tests/third_party/cupy/manipulation_tests/test_dims.py::TestInvalidBroadcast_param_3_{shapes=[(0,), (2,)]}::test_invalid_broadcast_arrays

tests/third_party/cupy/manipulation_tests/test_shape.py::TestRavel::test_ravel2
tests/third_party/cupy/manipulation_tests/test_shape.py::TestRavel::test_ravel3
tests/third_party/cupy/manipulation_tests/test_shape.py::TestRavel::test_external_ravel
Expand Down
1 change: 0 additions & 1 deletion tests/skipped_tests_gpu.tbl
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Expand Up @@ -210,7 +210,6 @@ tests/third_party/cupy/random_tests/test_distributions.py::TestDistributionsMult
tests/third_party/cupy/random_tests/test_distributions.py::TestDistributionsMultivariateNormal_param_3_{d=4, shape=(3, 2)}::test_normal

tests/third_party/intel/test_zero_copy_test1.py::test_dpnp_interaction_with_dpctl_memory
tests/test_arraymanipulation.py::TestVstack::test_generator

tests/test_linalg.py::test_cond[-1-[[1, 2, 3], [4, 5, 6], [7, 8, 9]]]
tests/test_linalg.py::test_cond[1-[[1, 2, 3], [4, 5, 6], [7, 8, 9]]]
Expand Down
11 changes: 3 additions & 8 deletions tests/test_arraymanipulation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -583,35 +583,30 @@ class TestVstack:
def test_non_iterable(self):
assert_raises(TypeError, dpnp.vstack, 1)

@pytest.mark.usefixtures("allow_fall_back_on_numpy")
def test_empty_input(self):
assert_raises(ValueError, dpnp.vstack, ())
assert_raises(TypeError, dpnp.vstack, ())

@pytest.mark.usefixtures("allow_fall_back_on_numpy")
def test_0D_array(self):
a = dpnp.array(1)
b = dpnp.array(2)
res = dpnp.vstack([a, b])
desired = dpnp.array([[1], [2]])
assert_array_equal(res, desired)

@pytest.mark.usefixtures("allow_fall_back_on_numpy")
def test_1D_array(self):
a = dpnp.array([1])
b = dpnp.array([2])
res = dpnp.vstack([a, b])
desired = dpnp.array([[1], [2]])
assert_array_equal(res, desired)

@pytest.mark.usefixtures("allow_fall_back_on_numpy")
def test_2D_array(self):
a = dpnp.array([[1], [2]])
b = dpnp.array([[1], [2]])
res = dpnp.vstack([a, b])
desired = dpnp.array([[1], [2], [1], [2]])
assert_array_equal(res, desired)

@pytest.mark.usefixtures("allow_fall_back_on_numpy")
def test_2D_array2(self):
a = dpnp.array([1, 2])
b = dpnp.array([1, 2])
Expand All @@ -620,8 +615,8 @@ def test_2D_array2(self):
assert_array_equal(res, desired)

def test_generator(self):
with assert_warns(FutureWarning):
dpnp.vstack((numpy.arange(3) for _ in range(2)))
with pytest.raises(TypeError):
dpnp.vstack((dpnp.arange(3) for _ in range(2)))


class TestAtleast1d:
Expand Down
18 changes: 3 additions & 15 deletions tests/third_party/cupy/manipulation_tests/test_join.py
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Original file line number Diff line number Diff line change
Expand Up @@ -312,27 +312,24 @@ def test_hstack_casting(self, xp, dtype1, dtype2, casting):
# may raise TypeError or ComplexWarning
return xp.hstack((a, b), dtype=dtype2, casting=casting)

@pytest.mark.skip("dpnp.vstack() is not implemented yet")
@testing.numpy_cupy_array_equal()
def test_vstack_vectors(self, xp):
a = xp.arange(3)
b = xp.arange(2, -1, -1)
return xp.vstack((a, b))

@pytest.mark.skip("dpnp.vstack() is not implemented yet")
@testing.numpy_cupy_array_equal()
def test_vstack_single_element(self, xp):
a = xp.arange(3)
return xp.vstack((a,))

@pytest.mark.skip("dpnp.vstack() is not implemented yet")
def test_vstack_wrong_ndim(self):
a = cupy.empty((3,))
b = cupy.empty((3, 1))
with pytest.raises(ValueError):
cupy.vstack((a, b))

@pytest.mark.skip("dpnp.vstack() is not implemented yet")
@pytest.mark.usefixtures("allow_fall_back_on_numpy")
@testing.with_requires("numpy>=1.24.0")
@testing.for_all_dtypes_combination(names=["dtype1", "dtype2"])
@testing.numpy_cupy_array_equal(accept_error=TypeError)
Expand All @@ -341,18 +338,9 @@ def test_vstack_dtype(self, xp, dtype1, dtype2):
b = testing.shaped_arange((3, 4), xp, dtype1)
return xp.vstack((a, b), dtype=dtype2)

@pytest.mark.skip("dpnp.vstack() is not implemented yet")
@pytest.mark.usefixtures("allow_fall_back_on_numpy")
@testing.with_requires("numpy>=1.24.0")
@pytest.mark.parametrize(
"casting",
[
"no",
"equiv",
"safe",
"same_kind",
"unsafe",
],
)
@testing.for_castings()
@testing.for_all_dtypes_combination(names=["dtype1", "dtype2"])
@testing.numpy_cupy_array_equal(
accept_error=(TypeError, numpy.ComplexWarning)
Expand Down