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Merged
merged 4 commits into from
Nov 16, 2024
Merged

improve coverage dpnp_iface_manipulation.py #2175

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8b38fd6
improve coverage dpnp_iface_manipulation.py
Nov 15, 2024
5a6824e
add a new test
Nov 15, 2024
3dd591b
update docstring tranpose
Nov 16, 2024
6a05a7f
Merge branch 'master' into improve-coverage-manipulation
vtavana Nov 16, 2024
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15 changes: 5 additions & 10 deletions dpnp/dpnp_iface_manipulation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3894,18 +3894,13 @@ def transpose(a, axes=None):

"""

if isinstance(a, dpnp_array):
array = a
elif isinstance(a, dpt.usm_ndarray):
array = dpnp_array._create_from_usm_ndarray(a)
else:
raise TypeError(
f"An array must be any of supported type, but got {type(a)}"
)
dpnp.check_supported_arrays_type(a)
if isinstance(a, dpt.usm_ndarray):
a = dpnp_array._create_from_usm_ndarray(a)

if axes is None:
return array.transpose()
return array.transpose(*axes)
return a.transpose()
return a.transpose(*axes)


permute_dims = transpose # permute_dims is an alias for transpose
Expand Down
348 changes: 174 additions & 174 deletions dpnp/tests/test_arraymanipulation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,6 +15,38 @@
from .third_party.cupy import testing


class TestAsfarray:
@testing.with_requires("numpy<2.0")
@pytest.mark.parametrize("dtype", get_all_dtypes())
@pytest.mark.parametrize(
"data", [[1, 2, 3], [1.0, 2.0, 3.0]], ids=["[1, 2, 3]", "[1., 2., 3.]"]
)
def test_asfarray1(self, dtype, data):
expected = numpy.asfarray(data, dtype)
result = dpnp.asfarray(data, dtype)
assert_array_equal(result, expected)

@testing.with_requires("numpy<2.0")
@pytest.mark.usefixtures("suppress_complex_warning")
@pytest.mark.parametrize("dtype", get_all_dtypes())
@pytest.mark.parametrize("data", [[1.0, 2.0, 3.0]], ids=["[1., 2., 3.]"])
@pytest.mark.parametrize("data_dtype", get_all_dtypes(no_none=True))
def test_asfarray2(self, dtype, data, data_dtype):
expected = numpy.asfarray(numpy.array(data, dtype=data_dtype), dtype)
result = dpnp.asfarray(dpnp.array(data, dtype=data_dtype), dtype)
assert_array_equal(result, expected)

# This is only for coverage with NumPy 2.0 and above
def test_asfarray_coverage(self):
expected = dpnp.array([1.0, 2.0, 3.0])
result = dpnp.asfarray([1, 2, 3])
assert_array_equal(result, expected)

expected = dpnp.array([1.0, 2.0, 3.0], dtype=dpnp.float32)
result = dpnp.asfarray([1, 2, 3], dtype=dpnp.float32)
assert_array_equal(result, expected)


class TestAtleast1d:
def test_0D_array(self):
a = dpnp.array(1)
Expand Down Expand Up @@ -132,6 +164,148 @@ def test_dpnp_dpt_array(self):
assert_array_equal(res, desired)


class TestBroadcastArray:
def assert_broadcast_correct(self, input_shapes):
np_arrays = [numpy.zeros(s, dtype="i1") for s in input_shapes]
out_np_arrays = numpy.broadcast_arrays(*np_arrays)
dpnp_arrays = [dpnp.asarray(Xnp) for Xnp in np_arrays]
out_dpnp_arrays = dpnp.broadcast_arrays(*dpnp_arrays)
for Xnp, X in zip(out_np_arrays, out_dpnp_arrays):
assert_array_equal(
Xnp, dpnp.asnumpy(X), err_msg=f"Failed for {input_shapes})"
)

def assert_broadcast_arrays_raise(self, input_shapes):
dpnp_arrays = [dpnp.asarray(numpy.zeros(s)) for s in input_shapes]
pytest.raises(ValueError, dpnp.broadcast_arrays, *dpnp_arrays)

def test_broadcast_arrays_same(self):
Xnp = numpy.arange(10)
Ynp = numpy.arange(10)
res_Xnp, res_Ynp = numpy.broadcast_arrays(Xnp, Ynp)
X = dpnp.asarray(Xnp)
Y = dpnp.asarray(Ynp)
res_X, res_Y = dpnp.broadcast_arrays(X, Y)
assert_array_equal(res_Xnp, dpnp.asnumpy(res_X))
assert_array_equal(res_Ynp, dpnp.asnumpy(res_Y))

def test_broadcast_arrays_one_off(self):
Xnp = numpy.array([[1, 2, 3]])
Ynp = numpy.array([[1], [2], [3]])
res_Xnp, res_Ynp = numpy.broadcast_arrays(Xnp, Ynp)
X = dpnp.asarray(Xnp)
Y = dpnp.asarray(Ynp)
res_X, res_Y = dpnp.broadcast_arrays(X, Y)
assert_array_equal(res_Xnp, dpnp.asnumpy(res_X))
assert_array_equal(res_Ynp, dpnp.asnumpy(res_Y))

@pytest.mark.parametrize(
"shapes",
[
(),
(1,),
(3,),
(0, 1),
(0, 3),
(1, 0),
(3, 0),
(1, 3),
(3, 1),
(3, 3),
],
)
def test_broadcast_arrays_same_shapes(self, shapes):
for shape in shapes:
single_input_shapes = [shape]
self.assert_broadcast_correct(single_input_shapes)
double_input_shapes = [shape, shape]
self.assert_broadcast_correct(double_input_shapes)
triple_input_shapes = [shape, shape, shape]
self.assert_broadcast_correct(triple_input_shapes)

@pytest.mark.parametrize(
"shapes",
[
[[(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_arrays_same_len_shapes(self, shapes):
# Check that two different input shapes of the same length, but some have
# ones, broadcast to the correct shape.
for input_shapes in shapes:
self.assert_broadcast_correct(input_shapes)
self.assert_broadcast_correct(input_shapes[::-1])

@pytest.mark.parametrize(
"shapes",
[
[[(), (3,)]],
[[(3,), (3, 3)]],
[[(3,), (3, 1)]],
[[(1,), (3, 3)]],
[[(), (3, 3)]],
[[(1, 1), (3,)]],
[[(1,), (3, 1)]],
[[(1,), (1, 3)]],
[[(), (1, 3)]],
[[(), (3, 1)]],
[[(), (0,)]],
[[(0,), (0, 0)]],
[[(0,), (0, 1)]],
[[(1,), (0, 0)]],
[[(), (0, 0)]],
[[(1, 1), (0,)]],
[[(1,), (0, 1)]],
[[(1,), (1, 0)]],
[[(), (1, 0)]],
[[(), (0, 1)]],
],
)
def test_broadcast_arrays_different_len_shapes(self, shapes):
# Check that two different input shapes (of different lengths) broadcast
# to the correct shape.
for input_shapes in shapes:
self.assert_broadcast_correct(input_shapes)
self.assert_broadcast_correct(input_shapes[::-1])

@pytest.mark.parametrize(
"shapes",
[
[[(3,), (4,)]],
[[(2, 3), (2,)]],
[[(3,), (3,), (4,)]],
[[(1, 3, 4), (2, 3, 3)]],
],
)
def test_incompatible_shapes_raise_valueerror(self, shapes):
for input_shapes in shapes:
self.assert_broadcast_arrays_raise(input_shapes)
self.assert_broadcast_arrays_raise(input_shapes[::-1])

def test_broadcast_arrays_empty_input(self):
assert dpnp.broadcast_arrays() == []

def test_subok_error(self):
x = dpnp.ones((4))
with pytest.raises(NotImplementedError):
dpnp.broadcast_arrays(x, subok=True)

with pytest.raises(NotImplementedError):
dpnp.broadcast_to(x, (4, 4), subok=True)


class TestColumnStack:
def test_non_iterable(self):
with pytest.raises(TypeError):
Expand Down Expand Up @@ -987,180 +1161,6 @@ def test_generator(self):
dpnp.vstack(map(lambda x: x, dpnp.ones((3, 2))))


@testing.with_requires("numpy<2.0")
@pytest.mark.parametrize("dtype", get_all_dtypes())
@pytest.mark.parametrize(
"data", [[1, 2, 3], [1.0, 2.0, 3.0]], ids=["[1, 2, 3]", "[1., 2., 3.]"]
)
def test_asfarray(dtype, data):
expected = numpy.asfarray(data, dtype)
result = dpnp.asfarray(data, dtype)

assert_array_equal(result, expected)


@testing.with_requires("numpy<2.0")
@pytest.mark.usefixtures("suppress_complex_warning")
@pytest.mark.parametrize("dtype", get_all_dtypes())
@pytest.mark.parametrize("data", [[1.0, 2.0, 3.0]], ids=["[1., 2., 3.]"])
@pytest.mark.parametrize("data_dtype", get_all_dtypes(no_none=True))
def test_asfarray2(dtype, data, data_dtype):
expected = numpy.asfarray(numpy.array(data, dtype=data_dtype), dtype)
result = dpnp.asfarray(dpnp.array(data, dtype=data_dtype), dtype)

assert_array_equal(result, expected)


def assert_broadcast_correct(input_shapes):
np_arrays = [numpy.zeros(s, dtype="i1") for s in input_shapes]
out_np_arrays = numpy.broadcast_arrays(*np_arrays)
dpnp_arrays = [dpnp.asarray(Xnp) for Xnp in np_arrays]
out_dpnp_arrays = dpnp.broadcast_arrays(*dpnp_arrays)
for Xnp, X in zip(out_np_arrays, out_dpnp_arrays):
assert_array_equal(
Xnp, dpnp.asnumpy(X), err_msg=f"Failed for {input_shapes})"
)


def assert_broadcast_arrays_raise(input_shapes):
dpnp_arrays = [dpnp.asarray(numpy.zeros(s)) for s in input_shapes]
pytest.raises(ValueError, dpnp.broadcast_arrays, *dpnp_arrays)


def test_broadcast_arrays_same():
Xnp = numpy.arange(10)
Ynp = numpy.arange(10)
res_Xnp, res_Ynp = numpy.broadcast_arrays(Xnp, Ynp)
X = dpnp.asarray(Xnp)
Y = dpnp.asarray(Ynp)
res_X, res_Y = dpnp.broadcast_arrays(X, Y)
assert_array_equal(res_Xnp, dpnp.asnumpy(res_X))
assert_array_equal(res_Ynp, dpnp.asnumpy(res_Y))


def test_broadcast_arrays_one_off():
Xnp = numpy.array([[1, 2, 3]])
Ynp = numpy.array([[1], [2], [3]])
res_Xnp, res_Ynp = numpy.broadcast_arrays(Xnp, Ynp)
X = dpnp.asarray(Xnp)
Y = dpnp.asarray(Ynp)
res_X, res_Y = dpnp.broadcast_arrays(X, Y)
assert_array_equal(res_Xnp, dpnp.asnumpy(res_X))
assert_array_equal(res_Ynp, dpnp.asnumpy(res_Y))


@pytest.mark.parametrize(
"shapes",
[
(),
(1,),
(3,),
(0, 1),
(0, 3),
(1, 0),
(3, 0),
(1, 3),
(3, 1),
(3, 3),
],
)
def test_broadcast_arrays_same_shapes(shapes):
for shape in shapes:
single_input_shapes = [shape]
assert_broadcast_correct(single_input_shapes)
double_input_shapes = [shape, shape]
assert_broadcast_correct(double_input_shapes)
triple_input_shapes = [shape, shape, shape]
assert_broadcast_correct(triple_input_shapes)


@pytest.mark.parametrize(
"shapes",
[
[[(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_arrays_same_len_shapes(shapes):
# Check that two different input shapes of the same length, but some have
# ones, broadcast to the correct shape.

for input_shapes in shapes:
assert_broadcast_correct(input_shapes)
assert_broadcast_correct(input_shapes[::-1])


@pytest.mark.parametrize(
"shapes",
[
[[(), (3,)]],
[[(3,), (3, 3)]],
[[(3,), (3, 1)]],
[[(1,), (3, 3)]],
[[(), (3, 3)]],
[[(1, 1), (3,)]],
[[(1,), (3, 1)]],
[[(1,), (1, 3)]],
[[(), (1, 3)]],
[[(), (3, 1)]],
[[(), (0,)]],
[[(0,), (0, 0)]],
[[(0,), (0, 1)]],
[[(1,), (0, 0)]],
[[(), (0, 0)]],
[[(1, 1), (0,)]],
[[(1,), (0, 1)]],
[[(1,), (1, 0)]],
[[(), (1, 0)]],
[[(), (0, 1)]],
],
)
def test_broadcast_arrays_different_len_shapes(shapes):
# Check that two different input shapes (of different lengths) broadcast
# to the correct shape.

for input_shapes in shapes:
assert_broadcast_correct(input_shapes)
assert_broadcast_correct(input_shapes[::-1])


@pytest.mark.parametrize(
"shapes",
[
[[(3,), (4,)]],
[[(2, 3), (2,)]],
[[(3,), (3,), (4,)]],
[[(1, 3, 4), (2, 3, 3)]],
],
)
def test_incompatible_shapes_raise_valueerror(shapes):
for input_shapes in shapes:
assert_broadcast_arrays_raise(input_shapes)
assert_broadcast_arrays_raise(input_shapes[::-1])


def test_broadcast_arrays_empty_input():
assert dpnp.broadcast_arrays() == []


def test_subok_error():
x = dpnp.ones((4))
with pytest.raises(NotImplementedError):
dpnp.broadcast_arrays(x, subok=True)
dpnp.broadcast_to(x, (4, 4), subok=True)


def test_can_cast():
X = dpnp.ones((2, 2), dtype=dpnp.int64)
pytest.raises(TypeError, dpnp.can_cast, X, 1)
Expand Down
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