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Reuse dpctl.tensor.moveaxis for dpnp.moveaxis #1382

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merged 5 commits into from
Jun 1, 2023
Merged

Reuse dpctl.tensor.moveaxis for dpnp.moveaxis #1382

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3f540bb
reuse dpctl.tensor.moveaxis for dpnp.moveaxis
vlad-perevezentsev Apr 19, 2023
baf5101
Fix remark
vlad-perevezentsev Apr 27, 2023
2e11ad9
Merge master into reuse_dpctl_moveaxis
vlad-perevezentsev Apr 27, 2023
7c1f5cf
Merge branch 'master' into reuse_dpctl_moveaxis
antonwolfy May 31, 2023
6da3fd5
Merge branch 'master' into reuse_dpctl_moveaxis
antonwolfy Jun 1, 2023
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41 changes: 15 additions & 26 deletions dpnp/dpnp_iface_manipulation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -388,17 +388,25 @@ def hstack(tup):
return call_origin(numpy.hstack, tup_new)


def moveaxis(x1, source, destination):
def moveaxis(x, source, destination):
"""
Move axes of an array to new positions. Other axes remain in their original order.

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

Returns
-------
out : dpnp.ndarray
Array with moved axes.
The returned array must has the same data type as `x`,
is created on the same device as `x` and has the same
USM allocation type as `x`.
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Limitations
-----------
Input array ``x1`` is supported as :obj:`dpnp.ndarray`.
Parameters `x` is supported as either :class:`dpnp.ndarray`
or :class:`dpctl.tensor.usm_ndarray`.
Otherwise the function will be executed sequentially on CPU.
Sizes of normalized input arrays are supported to be equal.
Input array data types are limited by supported DPNP :ref:`Data types`.

See Also
Expand All @@ -417,30 +425,11 @@ def moveaxis(x1, source, destination):

"""

x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
if x1_desc:
source_norm = normalize_axis(source, x1_desc.ndim)
destination_norm = normalize_axis(destination, x1_desc.ndim)

if len(source_norm) != len(destination_norm):
pass
else:
# 'do nothing' pattern for transpose() with no elements in 'source'
input_permute = []
for i in range(x1_desc.ndim):
if i not in source_norm:
input_permute.append(i)

# insert moving axes into proper positions
for destination_id, source_id in sorted(zip(destination_norm, source_norm)):
# if destination_id in input_permute:
# pytest tests/third_party/cupy/manipulation_tests/test_transpose.py::TestTranspose::test_moveaxis_invalid5_3
# checker_throw_value_error("swapaxes", "source_id exists", source_id, input_permute)
input_permute.insert(destination_id, source_id)

return transpose(x1_desc.get_pyobj(), axes=input_permute)
if isinstance(x, dpnp_array) or isinstance(x, dpt.usm_ndarray):
dpt_array = x.get_array() if isinstance(x, dpnp_array) else x
return dpnp_array._create_from_usm_ndarray(dpt.moveaxis(dpt_array, source, destination))

return call_origin(numpy.moveaxis, x1, source, destination)
return call_origin(numpy.moveaxis, x, source, destination)


def ravel(x1, order='C'):
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2 changes: 0 additions & 2 deletions tests/skipped_tests.tbl
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Expand Up @@ -747,8 +747,6 @@ tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTile_param_2_{reps
tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTile_param_3_{reps=(0, 1)}::test_array_tile
tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTile_param_4_{reps=(2, 3)}::test_array_tile
tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTile_param_5_{reps=(2, 3, 4, 5)}::test_array_tile
tests/third_party/cupy/manipulation_tests/test_transpose.py::TestTranspose::test_moveaxis_invalid5_2
tests/third_party/cupy/manipulation_tests/test_transpose.py::TestTranspose::test_moveaxis_invalid5_3
tests/third_party/cupy/math_tests/test_arithmetic.py::TestArithmeticBinary2_param_455_{arg1=array([[1, 2, 3], [4, 5, 6]], dtype=int32), arg2=array([[0, 1, 2], [3, 4, 5]], dtype=int32), dtype=float64, name='floor_divide', use_dtype=False}::test_binary
tests/third_party/cupy/math_tests/test_arithmetic.py::TestArithmeticBinary2_param_457_{arg1=array([[1, 2, 3], [4, 5, 6]], dtype=int32), arg2=array([[0, 1, 2], [3, 4, 5]], dtype=int32), dtype=float64, name='fmod', use_dtype=False}::test_binary
tests/third_party/cupy/math_tests/test_arithmetic.py::TestArithmeticBinary2_param_459_{arg1=array([[1, 2, 3], [4, 5, 6]], dtype=int32), arg2=array([[0, 1, 2], [3, 4, 5]], dtype=int32), dtype=float64, name='remainder', use_dtype=False}::test_binary
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2 changes: 0 additions & 2 deletions tests/skipped_tests_gpu.tbl
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Original file line number Diff line number Diff line change
Expand Up @@ -908,8 +908,6 @@ tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTile_param_2_{reps
tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTile_param_3_{reps=(0, 1)}::test_array_tile
tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTile_param_4_{reps=(2, 3)}::test_array_tile
tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTile_param_5_{reps=(2, 3, 4, 5)}::test_array_tile
tests/third_party/cupy/manipulation_tests/test_transpose.py::TestTranspose::test_moveaxis_invalid5_2
tests/third_party/cupy/manipulation_tests/test_transpose.py::TestTranspose::test_moveaxis_invalid5_3

tests/third_party/cupy/math_tests/test_arithmetic.py::TestArithmeticBinary2_param_279_{arg1=array([[1., 2., 3.], [4., 5., 6.]], dtype=float32), arg2=array([[0., 1., 2.], [3., 4., 5.]], dtype=float32), dtype=float64, name='floor_divide', use_dtype=False}::test_binary
tests/third_party/cupy/math_tests/test_arithmetic.py::TestArithmeticBinary2_param_287_{arg1=array([[1., 2., 3.], [4., 5., 6.]], dtype=float32), arg2=array([[0., 1., 2.], [3., 4., 5.]]), dtype=float64, name='floor_divide', use_dtype=False}::test_binary
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7 changes: 0 additions & 7 deletions tests/third_party/cupy/manipulation_tests/test_transpose.py
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Original file line number Diff line number Diff line change
Expand Up @@ -41,53 +41,46 @@ def test_moveaxis6(self, xp):
return xp.moveaxis(a, [0, 2, 1], [3, 4, 0])

# dim is too large
@pytest.mark.usefixtures("allow_fall_back_on_numpy")
def test_moveaxis_invalid1_1(self):
for xp in (numpy, cupy):
a = testing.shaped_arange((2, 3, 4), xp)
with pytest.raises(numpy.AxisError):
xp.moveaxis(a, [0, 1], [1, 3])

@pytest.mark.usefixtures("allow_fall_back_on_numpy")
def test_moveaxis_invalid1_2(self):
for xp in (numpy, cupy):
a = testing.shaped_arange((2, 3, 4), xp)
with pytest.raises(numpy.AxisError):
xp.moveaxis(a, [0, 1], [1, 3])

# dim is too small
@pytest.mark.usefixtures("allow_fall_back_on_numpy")
def test_moveaxis_invalid2_1(self):
for xp in (numpy, cupy):
a = testing.shaped_arange((2, 3, 4), xp)
with pytest.raises(numpy.AxisError):
xp.moveaxis(a, [0, -4], [1, 2])

@pytest.mark.usefixtures("allow_fall_back_on_numpy")
def test_moveaxis_invalid2_2(self):
for xp in (numpy, cupy):
a = testing.shaped_arange((2, 3, 4), xp)
with pytest.raises(numpy.AxisError):
xp.moveaxis(a, [0, -4], [1, 2])

# len(source) != len(destination)
@pytest.mark.usefixtures("allow_fall_back_on_numpy")
def test_moveaxis_invalid3(self):
for xp in (numpy, cupy):
a = testing.shaped_arange((2, 3, 4), xp)
with pytest.raises(ValueError):
xp.moveaxis(a, [0, 1, 2], [1, 2])

# len(source) != len(destination)
@pytest.mark.usefixtures("allow_fall_back_on_numpy")
def test_moveaxis_invalid4(self):
for xp in (numpy, cupy):
a = testing.shaped_arange((2, 3, 4), xp)
with pytest.raises(ValueError):
xp.moveaxis(a, [0, 1], [1, 2, 0])

# Use the same axis twice
@pytest.mark.usefixtures("allow_fall_back_on_numpy")
def test_moveaxis_invalid5_1(self):
for xp in (numpy, cupy):
a = testing.shaped_arange((2, 3, 4), xp)
Expand Down