GH-38868: [Python] Add dlpack producer to FixedShapeTensorArray/Scalar#51159

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GH-38868: [Python] Add dlpack producer to FixedShapeTensorArray/Scalar #51159

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bb34538
Add FixedShapeTensorArray.__dlpack__
AntoinePrv Sep 4, 2026
29bbc29
Factor numpy skips
AntoinePrv Sep 4, 2026
6790bce
Add Dlpack on FixedShapeTensorScalar
AntoinePrv Sep 4, 2026
6bf37d2
Clean up tests
AntoinePrv Sep 4, 2026
ce5c25a
Fix typo
AntoinePrv Sep 4, 2026
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16 changes: 15 additions & 1 deletion python/pyarrow/array.pxi
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -2269,7 +2269,7 @@ cdef class Array(_PandasConvertible):

return pyarrow_wrap_array(array)

def __dlpack__(self, stream=None, max_version=None, dl_device=None, copy=None):
def __dlpack__(self, *, stream=None, max_version=None, dl_device=None, copy=None):
"""
Export a primitive array as a DLPack capsule.

Expand DownExpand Up@@ -5045,6 +5045,20 @@ cdef class FixedShapeTensorArray(ExtensionArray):
FixedSizeListArray.from_arrays(values, shape[1:].prod())
)

def __dlpack__(self, *, stream=None, max_version=None, dl_device=None, copy=None):
"""
Export a tensor array as a DLPack capsule.

The element positions in the array become the first dimension of the
resulting tensor (equal to ``len(self)``).

See :meth:`Tensor.__dlpack__` for the parameter semantics.
"""
return self.to_tensor().__dlpack__(
stream=stream, max_version=max_version,
dl_device=dl_device, copy=copy,
)


cdef class OpaqueArray(ExtensionArray):
"""
Expand Down
29 changes: 29 additions & 0 deletions python/pyarrow/scalar.pxi
View file
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Original file line numberDiff line numberDiff line change
Expand Up@@ -1586,6 +1586,35 @@ cdef class FixedShapeTensorScalar(ExtensionScalar):
ctensor = GetResultValue(c_type.MakeTensor(scalar))
return pyarrow_wrap_tensor(ctensor)

def __dlpack__(self, *, stream=None, max_version=None, dl_device=None, copy=None):
"""
Export a tensor scalar as a DLPack capsule.

See :meth:`Tensor.__dlpack__` for the parameter semantics.
"""
return self.to_tensor().__dlpack__(
stream=stream, max_version=max_version,
dl_device=dl_device, copy=copy,
)

def __dlpack_device__(self):
"""
Return the DLPack device tuple this scalar resides on.

Returns
-------
tuple : Tuple[int, int]
Tuple with index specifying the type of the device (where
CPU = 1, see cpp/src/arrow/c/dlpack_abi.h) and index of the
device which is 0 by default for CPU.
"""
cdef:
CExtensionScalar* ext = <CExtensionScalar*> self.wrapped.get()
CBaseListScalar* storage = <CBaseListScalar*> ext.value.get()
# The base storage for this type is an Array, so we call into this function
device = GetResultValue(ExportDevice(storage.value))
return device.device_type, device.device_id


cdef class OpaqueScalar(ExtensionScalar):
"""
Expand Down
59 changes: 47 additions & 12 deletions python/pyarrow/tests/test_dlpack.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -29,6 +29,13 @@
np = pytest.importorskip("numpy")


def requires_numpy_version(min_version):
return pytest.mark.skipif(
Version(np.__version__) < Version(min_version),
reason=f"Test requires numpy {min_version} or later",
)


def PyCapsule_IsValid(capsule, name):
return ctypes.pythonapi.PyCapsule_IsValid(ctypes.py_object(capsule), name) == 1

Expand DownExpand Up@@ -150,12 +157,10 @@ def multidim_arrays():
]


@requires_numpy_version("2.1.0")
@check_bytes_allocated
@pytest.mark.parametrize(('arr', 'expected'), multidim_arrays())
def test_array_to_tensor_dlpack(arr, expected):
if Version(np.__version__) < Version("2.1.0"):
pytest.skip("Versioned DLPack capsules require numpy 2.1.0 or later")

tensor = arr.to_tensor()
# A Tensor sharing an Array buffer is immutable, so it can only be exported
# through the versioned DLPack protocol.
Expand All@@ -165,6 +170,42 @@ def test_array_to_tensor_dlpack(arr, expected):
assert tensor.__dlpack_device__() == (1, 0)


@requires_numpy_version("2.1.0")
@check_bytes_allocated
def test_fixed_shape_tensor_array_dlpack_permuted():
# A non-trivial permutation makes to_tensor() produce a non-row-major
# tensor: each row-major [3, 2] block is exposed as a logical [2, 3] cell.
storage = pa.FixedSizeListArray.from_arrays(
pa.array(range(24), type=pa.int32()), 6)
arr = pa.ExtensionArray.from_storage(
pa.fixed_shape_tensor(pa.int32(), [3, 2], permutation=[1, 0]), storage)

tensor = arr.to_tensor()
assert tensor.shape == (4, 2, 3)
assert not tensor.is_contiguous

# expected[i, j, k] == i * 6 + k * 2 + j (numpy is only the DLPack consumer)
expected = np.arange(24, dtype=np.int32).reshape(4, 3, 2).transpose(0, 2, 1)
result = np.from_dlpack(DLPackForwarder(arr, max_version=(1, 0)))
np.testing.assert_array_equal(result, expected, strict=True)
assert arr.__dlpack_device__() == (1, 0)


@requires_numpy_version("2.1.0")
@check_bytes_allocated
def test_fixed_shape_tensor_scalar_dlpack():
np_arr = np.arange(12, dtype=np.int32).reshape(3, 2, 2)
arr = pa.FixedShapeTensorArray.from_numpy_ndarray(np_arr)

scalar = arr[1]
assert isinstance(scalar, pa.FixedShapeTensorScalar)
# __dlpack_device__ reads the storage array's device, without building a Tensor.
assert scalar.__dlpack_device__() == (1, 0)

result = np.from_dlpack(DLPackForwarder(scalar, max_version=(1, 0)))
np.testing.assert_array_equal(result, np_arr[1], strict=True)


def multidim_arrays_with_nulls():
np_arr = np.arange(6, dtype=np.int32).reshape(3, 2)
# Masked entries keep defined values in the child array, so the tensor
Expand All@@ -183,12 +224,10 @@ def multidim_arrays_with_nulls():
]


@requires_numpy_version("2.1.0")
@check_bytes_allocated
@pytest.mark.parametrize(('arr', 'expected'), multidim_arrays_with_nulls())
def test_array_to_tensor_dlpack_nulls(arr, expected):
if Version(np.__version__) < Version("2.1.0"):
pytest.skip("Versioned DLPack capsules require numpy 2.1.0 or later")

with pytest.raises(pa.ArrowInvalid, match="Array contains nulls"):
arr.to_tensor()

Expand DownExpand Up@@ -264,25 +303,21 @@ def test_dlpack_versioned_capsule(obj, max_version, copy):
assert PyCapsule_IsValid(capsule, b"dltensor_versioned") is True


@requires_numpy_version("2.1.0")
@check_bytes_allocated
@pytest.mark.parametrize('obj', dlpack_objects())
def test_dlpack_versioned_roundtrip(obj):
if Version(np.__version__) < Version("2.1.0"):
pytest.skip("Versioned DLPack capsules require numpy 2.1.0 or later")

expected = np.from_dlpack(DLPackForwarder(obj, max_version=None))
for copy in [None, False, True]:
result = np.from_dlpack(
DLPackForwarder(obj, max_version=(1, 0), copy=copy))
np.testing.assert_array_equal(result, expected, strict=True)


@requires_numpy_version("2.2.5")
@check_bytes_allocated
def test_dlpack_copy_is_writeable():
# NumPy did not set the writeable flag on DLPack imports before 2.2.5.
if Version(np.__version__) < Version("2.2.5"):
pytest.skip("Writable DLPack imports require numpy 2.2.5 or later")

arr = pa.array([1, 2, 3], type=pa.int32())

# Arrow arrays are immutable, so a shared export is read-only
Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all \u003cpre\u003e\u003ccode\u003e blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks"); } } catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); } })(); (function(){ try { var __m = "github.com"; var __re = new RegExp('^' + "github\\.com" + '
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GH-38868: [Python] Add dlpack producer to FixedShapeTensorArray/Scalar#51159

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GH-38868: [Python] Add dlpack producer to FixedShapeTensorArray/Scalar #51159

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bb34538
Add FixedShapeTensorArray.__dlpack__
AntoinePrv Sep 4, 2026
29bbc29
Factor numpy skips
AntoinePrv Sep 4, 2026
6790bce
Add Dlpack on FixedShapeTensorScalar
AntoinePrv Sep 4, 2026
6bf37d2
Clean up tests
AntoinePrv Sep 4, 2026
ce5c25a
Fix typo
AntoinePrv Sep 4, 2026
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16 changes: 15 additions & 1 deletion python/pyarrow/array.pxi
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -2269,7 +2269,7 @@ cdef class Array(_PandasConvertible):

return pyarrow_wrap_array(array)

def __dlpack__(self, stream=None, max_version=None, dl_device=None, copy=None):
def __dlpack__(self, *, stream=None, max_version=None, dl_device=None, copy=None):
"""
Export a primitive array as a DLPack capsule.

Expand DownExpand Up@@ -5045,6 +5045,20 @@ cdef class FixedShapeTensorArray(ExtensionArray):
FixedSizeListArray.from_arrays(values, shape[1:].prod())
)

def __dlpack__(self, *, stream=None, max_version=None, dl_device=None, copy=None):
"""
Export a tensor array as a DLPack capsule.

The element positions in the array become the first dimension of the
resulting tensor (equal to ``len(self)``).

See :meth:`Tensor.__dlpack__` for the parameter semantics.
"""
return self.to_tensor().__dlpack__(
stream=stream, max_version=max_version,
dl_device=dl_device, copy=copy,
)


cdef class OpaqueArray(ExtensionArray):
"""
Expand Down
29 changes: 29 additions & 0 deletions python/pyarrow/scalar.pxi
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -1586,6 +1586,35 @@ cdef class FixedShapeTensorScalar(ExtensionScalar):
ctensor = GetResultValue(c_type.MakeTensor(scalar))
return pyarrow_wrap_tensor(ctensor)

def __dlpack__(self, *, stream=None, max_version=None, dl_device=None, copy=None):
"""
Export a tensor scalar as a DLPack capsule.

See :meth:`Tensor.__dlpack__` for the parameter semantics.
"""
return self.to_tensor().__dlpack__(
stream=stream, max_version=max_version,
dl_device=dl_device, copy=copy,
)

def __dlpack_device__(self):
"""
Return the DLPack device tuple this scalar resides on.

Returns
-------
tuple : Tuple[int, int]
Tuple with index specifying the type of the device (where
CPU = 1, see cpp/src/arrow/c/dlpack_abi.h) and index of the
device which is 0 by default for CPU.
"""
cdef:
CExtensionScalar* ext = <CExtensionScalar*> self.wrapped.get()
CBaseListScalar* storage = <CBaseListScalar*> ext.value.get()
# The base storage for this type is an Array, so we call into this function
device = GetResultValue(ExportDevice(storage.value))
return device.device_type, device.device_id


cdef class OpaqueScalar(ExtensionScalar):
"""
Expand Down
59 changes: 47 additions & 12 deletions python/pyarrow/tests/test_dlpack.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -29,6 +29,13 @@
np = pytest.importorskip("numpy")


def requires_numpy_version(min_version):
return pytest.mark.skipif(
Version(np.__version__) < Version(min_version),
reason=f"Test requires numpy {min_version} or later",
)


def PyCapsule_IsValid(capsule, name):
return ctypes.pythonapi.PyCapsule_IsValid(ctypes.py_object(capsule), name) == 1

Expand DownExpand Up@@ -150,12 +157,10 @@ def multidim_arrays():
]


@requires_numpy_version("2.1.0")
@check_bytes_allocated
@pytest.mark.parametrize(('arr', 'expected'), multidim_arrays())
def test_array_to_tensor_dlpack(arr, expected):
if Version(np.__version__) < Version("2.1.0"):
pytest.skip("Versioned DLPack capsules require numpy 2.1.0 or later")

tensor = arr.to_tensor()
# A Tensor sharing an Array buffer is immutable, so it can only be exported
# through the versioned DLPack protocol.
Expand All@@ -165,6 +170,42 @@ def test_array_to_tensor_dlpack(arr, expected):
assert tensor.__dlpack_device__() == (1, 0)


@requires_numpy_version("2.1.0")
@check_bytes_allocated
def test_fixed_shape_tensor_array_dlpack_permuted():
# A non-trivial permutation makes to_tensor() produce a non-row-major
# tensor: each row-major [3, 2] block is exposed as a logical [2, 3] cell.
storage = pa.FixedSizeListArray.from_arrays(
pa.array(range(24), type=pa.int32()), 6)
arr = pa.ExtensionArray.from_storage(
pa.fixed_shape_tensor(pa.int32(), [3, 2], permutation=[1, 0]), storage)

tensor = arr.to_tensor()
assert tensor.shape == (4, 2, 3)
assert not tensor.is_contiguous

# expected[i, j, k] == i * 6 + k * 2 + j (numpy is only the DLPack consumer)
expected = np.arange(24, dtype=np.int32).reshape(4, 3, 2).transpose(0, 2, 1)
result = np.from_dlpack(DLPackForwarder(arr, max_version=(1, 0)))
np.testing.assert_array_equal(result, expected, strict=True)
assert arr.__dlpack_device__() == (1, 0)


@requires_numpy_version("2.1.0")
@check_bytes_allocated
def test_fixed_shape_tensor_scalar_dlpack():
np_arr = np.arange(12, dtype=np.int32).reshape(3, 2, 2)
arr = pa.FixedShapeTensorArray.from_numpy_ndarray(np_arr)

scalar = arr[1]
assert isinstance(scalar, pa.FixedShapeTensorScalar)
# __dlpack_device__ reads the storage array's device, without building a Tensor.
assert scalar.__dlpack_device__() == (1, 0)

result = np.from_dlpack(DLPackForwarder(scalar, max_version=(1, 0)))
np.testing.assert_array_equal(result, np_arr[1], strict=True)


def multidim_arrays_with_nulls():
np_arr = np.arange(6, dtype=np.int32).reshape(3, 2)
# Masked entries keep defined values in the child array, so the tensor
Expand All@@ -183,12 +224,10 @@ def multidim_arrays_with_nulls():
]


@requires_numpy_version("2.1.0")
@check_bytes_allocated
@pytest.mark.parametrize(('arr', 'expected'), multidim_arrays_with_nulls())
def test_array_to_tensor_dlpack_nulls(arr, expected):
if Version(np.__version__) < Version("2.1.0"):
pytest.skip("Versioned DLPack capsules require numpy 2.1.0 or later")

with pytest.raises(pa.ArrowInvalid, match="Array contains nulls"):
arr.to_tensor()

Expand DownExpand Up@@ -264,25 +303,21 @@ def test_dlpack_versioned_capsule(obj, max_version, copy):
assert PyCapsule_IsValid(capsule, b"dltensor_versioned") is True


@requires_numpy_version("2.1.0")
@check_bytes_allocated
@pytest.mark.parametrize('obj', dlpack_objects())
def test_dlpack_versioned_roundtrip(obj):
if Version(np.__version__) < Version("2.1.0"):
pytest.skip("Versioned DLPack capsules require numpy 2.1.0 or later")

expected = np.from_dlpack(DLPackForwarder(obj, max_version=None))
for copy in [None, False, True]:
result = np.from_dlpack(
DLPackForwarder(obj, max_version=(1, 0), copy=copy))
np.testing.assert_array_equal(result, expected, strict=True)


@requires_numpy_version("2.2.5")
@check_bytes_allocated
def test_dlpack_copy_is_writeable():
# NumPy did not set the writeable flag on DLPack imports before 2.2.5.
if Version(np.__version__) < Version("2.2.5"):
pytest.skip("Writable DLPack imports require numpy 2.2.5 or later")

arr = pa.array([1, 2, 3], type=pa.int32())

# Arrow arrays are immutable, so a shared export is read-only
Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix"); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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GH-38868: [Python] Add dlpack producer to FixedShapeTensorArray/Scalar#51159

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AntoinePrv wants to merge 5 commits into
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GH-38868: [Python] Add dlpack producer to FixedShapeTensorArray/Scalar #51159

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bb34538
Add FixedShapeTensorArray.__dlpack__
AntoinePrv Sep 4, 2026
29bbc29
Factor numpy skips
AntoinePrv Sep 4, 2026
6790bce
Add Dlpack on FixedShapeTensorScalar
AntoinePrv Sep 4, 2026
6bf37d2
Clean up tests
AntoinePrv Sep 4, 2026
ce5c25a
Fix typo
AntoinePrv Sep 4, 2026
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16 changes: 15 additions & 1 deletion python/pyarrow/array.pxi
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -2269,7 +2269,7 @@ cdef class Array(_PandasConvertible):

return pyarrow_wrap_array(array)

def __dlpack__(self, stream=None, max_version=None, dl_device=None, copy=None):
def __dlpack__(self, *, stream=None, max_version=None, dl_device=None, copy=None):
"""
Export a primitive array as a DLPack capsule.

Expand DownExpand Up@@ -5045,6 +5045,20 @@ cdef class FixedShapeTensorArray(ExtensionArray):
FixedSizeListArray.from_arrays(values, shape[1:].prod())
)

def __dlpack__(self, *, stream=None, max_version=None, dl_device=None, copy=None):
"""
Export a tensor array as a DLPack capsule.

The element positions in the array become the first dimension of the
resulting tensor (equal to ``len(self)``).

See :meth:`Tensor.__dlpack__` for the parameter semantics.
"""
return self.to_tensor().__dlpack__(
stream=stream, max_version=max_version,
dl_device=dl_device, copy=copy,
)


cdef class OpaqueArray(ExtensionArray):
"""
Expand Down
29 changes: 29 additions & 0 deletions python/pyarrow/scalar.pxi
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -1586,6 +1586,35 @@ cdef class FixedShapeTensorScalar(ExtensionScalar):
ctensor = GetResultValue(c_type.MakeTensor(scalar))
return pyarrow_wrap_tensor(ctensor)

def __dlpack__(self, *, stream=None, max_version=None, dl_device=None, copy=None):
"""
Export a tensor scalar as a DLPack capsule.

See :meth:`Tensor.__dlpack__` for the parameter semantics.
"""
return self.to_tensor().__dlpack__(
stream=stream, max_version=max_version,
dl_device=dl_device, copy=copy,
)

def __dlpack_device__(self):
"""
Return the DLPack device tuple this scalar resides on.

Returns
-------
tuple : Tuple[int, int]
Tuple with index specifying the type of the device (where
CPU = 1, see cpp/src/arrow/c/dlpack_abi.h) and index of the
device which is 0 by default for CPU.
"""
cdef:
CExtensionScalar* ext = <CExtensionScalar*> self.wrapped.get()
CBaseListScalar* storage = <CBaseListScalar*> ext.value.get()
# The base storage for this type is an Array, so we call into this function
device = GetResultValue(ExportDevice(storage.value))
return device.device_type, device.device_id


cdef class OpaqueScalar(ExtensionScalar):
"""
Expand Down
59 changes: 47 additions & 12 deletions python/pyarrow/tests/test_dlpack.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -29,6 +29,13 @@
np = pytest.importorskip("numpy")


def requires_numpy_version(min_version):
return pytest.mark.skipif(
Version(np.__version__) < Version(min_version),
reason=f"Test requires numpy {min_version} or later",
)


def PyCapsule_IsValid(capsule, name):
return ctypes.pythonapi.PyCapsule_IsValid(ctypes.py_object(capsule), name) == 1

Expand DownExpand Up@@ -150,12 +157,10 @@ def multidim_arrays():
]


@requires_numpy_version("2.1.0")
@check_bytes_allocated
@pytest.mark.parametrize(('arr', 'expected'), multidim_arrays())
def test_array_to_tensor_dlpack(arr, expected):
if Version(np.__version__) < Version("2.1.0"):
pytest.skip("Versioned DLPack capsules require numpy 2.1.0 or later")

tensor = arr.to_tensor()
# A Tensor sharing an Array buffer is immutable, so it can only be exported
# through the versioned DLPack protocol.
Expand All@@ -165,6 +170,42 @@ def test_array_to_tensor_dlpack(arr, expected):
assert tensor.__dlpack_device__() == (1, 0)


@requires_numpy_version("2.1.0")
@check_bytes_allocated
def test_fixed_shape_tensor_array_dlpack_permuted():
# A non-trivial permutation makes to_tensor() produce a non-row-major
# tensor: each row-major [3, 2] block is exposed as a logical [2, 3] cell.
storage = pa.FixedSizeListArray.from_arrays(
pa.array(range(24), type=pa.int32()), 6)
arr = pa.ExtensionArray.from_storage(
pa.fixed_shape_tensor(pa.int32(), [3, 2], permutation=[1, 0]), storage)

tensor = arr.to_tensor()
assert tensor.shape == (4, 2, 3)
assert not tensor.is_contiguous

# expected[i, j, k] == i * 6 + k * 2 + j (numpy is only the DLPack consumer)
expected = np.arange(24, dtype=np.int32).reshape(4, 3, 2).transpose(0, 2, 1)
result = np.from_dlpack(DLPackForwarder(arr, max_version=(1, 0)))
np.testing.assert_array_equal(result, expected, strict=True)
assert arr.__dlpack_device__() == (1, 0)


@requires_numpy_version("2.1.0")
@check_bytes_allocated
def test_fixed_shape_tensor_scalar_dlpack():
np_arr = np.arange(12, dtype=np.int32).reshape(3, 2, 2)
arr = pa.FixedShapeTensorArray.from_numpy_ndarray(np_arr)

scalar = arr[1]
assert isinstance(scalar, pa.FixedShapeTensorScalar)
# __dlpack_device__ reads the storage array's device, without building a Tensor.
assert scalar.__dlpack_device__() == (1, 0)

result = np.from_dlpack(DLPackForwarder(scalar, max_version=(1, 0)))
np.testing.assert_array_equal(result, np_arr[1], strict=True)


def multidim_arrays_with_nulls():
np_arr = np.arange(6, dtype=np.int32).reshape(3, 2)
# Masked entries keep defined values in the child array, so the tensor
Expand All@@ -183,12 +224,10 @@ def multidim_arrays_with_nulls():
]


@requires_numpy_version("2.1.0")
@check_bytes_allocated
@pytest.mark.parametrize(('arr', 'expected'), multidim_arrays_with_nulls())
def test_array_to_tensor_dlpack_nulls(arr, expected):
if Version(np.__version__) < Version("2.1.0"):
pytest.skip("Versioned DLPack capsules require numpy 2.1.0 or later")

with pytest.raises(pa.ArrowInvalid, match="Array contains nulls"):
arr.to_tensor()

Expand DownExpand Up@@ -264,25 +303,21 @@ def test_dlpack_versioned_capsule(obj, max_version, copy):
assert PyCapsule_IsValid(capsule, b"dltensor_versioned") is True


@requires_numpy_version("2.1.0")
@check_bytes_allocated
@pytest.mark.parametrize('obj', dlpack_objects())
def test_dlpack_versioned_roundtrip(obj):
if Version(np.__version__) < Version("2.1.0"):
pytest.skip("Versioned DLPack capsules require numpy 2.1.0 or later")

expected = np.from_dlpack(DLPackForwarder(obj, max_version=None))
for copy in [None, False, True]:
result = np.from_dlpack(
DLPackForwarder(obj, max_version=(1, 0), copy=copy))
np.testing.assert_array_equal(result, expected, strict=True)


@requires_numpy_version("2.2.5")
@check_bytes_allocated
def test_dlpack_copy_is_writeable():
# NumPy did not set the writeable flag on DLPack imports before 2.2.5.
if Version(np.__version__) < Version("2.2.5"):
pytest.skip("Writable DLPack imports require numpy 2.2.5 or later")

arr = pa.array([1, 2, 3], type=pa.int32())

# Arrow arrays are immutable, so a shared export is read-only
Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length \u003e 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms"); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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GH-38868: [Python] Add dlpack producer to FixedShapeTensorArray/Scalar#51159

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GH-38868: [Python] Add dlpack producer to FixedShapeTensorArray/Scalar #51159

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bb34538
Add FixedShapeTensorArray.__dlpack__
AntoinePrv Sep 4, 2026
29bbc29
Factor numpy skips
AntoinePrv Sep 4, 2026
6790bce
Add Dlpack on FixedShapeTensorScalar
AntoinePrv Sep 4, 2026
6bf37d2
Clean up tests
AntoinePrv Sep 4, 2026
ce5c25a
Fix typo
AntoinePrv Sep 4, 2026
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16 changes: 15 additions & 1 deletion python/pyarrow/array.pxi
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -2269,7 +2269,7 @@ cdef class Array(_PandasConvertible):

return pyarrow_wrap_array(array)

def __dlpack__(self, stream=None, max_version=None, dl_device=None, copy=None):
def __dlpack__(self, *, stream=None, max_version=None, dl_device=None, copy=None):
"""
Export a primitive array as a DLPack capsule.

Expand DownExpand Up@@ -5045,6 +5045,20 @@ cdef class FixedShapeTensorArray(ExtensionArray):
FixedSizeListArray.from_arrays(values, shape[1:].prod())
)

def __dlpack__(self, *, stream=None, max_version=None, dl_device=None, copy=None):
"""
Export a tensor array as a DLPack capsule.

The element positions in the array become the first dimension of the
resulting tensor (equal to ``len(self)``).

See :meth:`Tensor.__dlpack__` for the parameter semantics.
"""
return self.to_tensor().__dlpack__(
stream=stream, max_version=max_version,
dl_device=dl_device, copy=copy,
)


cdef class OpaqueArray(ExtensionArray):
"""
Expand Down
29 changes: 29 additions & 0 deletions python/pyarrow/scalar.pxi
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -1586,6 +1586,35 @@ cdef class FixedShapeTensorScalar(ExtensionScalar):
ctensor = GetResultValue(c_type.MakeTensor(scalar))
return pyarrow_wrap_tensor(ctensor)

def __dlpack__(self, *, stream=None, max_version=None, dl_device=None, copy=None):
"""
Export a tensor scalar as a DLPack capsule.

See :meth:`Tensor.__dlpack__` for the parameter semantics.
"""
return self.to_tensor().__dlpack__(
stream=stream, max_version=max_version,
dl_device=dl_device, copy=copy,
)

def __dlpack_device__(self):
"""
Return the DLPack device tuple this scalar resides on.

Returns
-------
tuple : Tuple[int, int]
Tuple with index specifying the type of the device (where
CPU = 1, see cpp/src/arrow/c/dlpack_abi.h) and index of the
device which is 0 by default for CPU.
"""
cdef:
CExtensionScalar* ext = <CExtensionScalar*> self.wrapped.get()
CBaseListScalar* storage = <CBaseListScalar*> ext.value.get()
# The base storage for this type is an Array, so we call into this function
device = GetResultValue(ExportDevice(storage.value))
return device.device_type, device.device_id


cdef class OpaqueScalar(ExtensionScalar):
"""
Expand Down
59 changes: 47 additions & 12 deletions python/pyarrow/tests/test_dlpack.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -29,6 +29,13 @@
np = pytest.importorskip("numpy")


def requires_numpy_version(min_version):
return pytest.mark.skipif(
Version(np.__version__) < Version(min_version),
reason=f"Test requires numpy {min_version} or later",
)


def PyCapsule_IsValid(capsule, name):
return ctypes.pythonapi.PyCapsule_IsValid(ctypes.py_object(capsule), name) == 1

Expand DownExpand Up@@ -150,12 +157,10 @@ def multidim_arrays():
]


@requires_numpy_version("2.1.0")
@check_bytes_allocated
@pytest.mark.parametrize(('arr', 'expected'), multidim_arrays())
def test_array_to_tensor_dlpack(arr, expected):
if Version(np.__version__) < Version("2.1.0"):
pytest.skip("Versioned DLPack capsules require numpy 2.1.0 or later")

tensor = arr.to_tensor()
# A Tensor sharing an Array buffer is immutable, so it can only be exported
# through the versioned DLPack protocol.
Expand All@@ -165,6 +170,42 @@ def test_array_to_tensor_dlpack(arr, expected):
assert tensor.__dlpack_device__() == (1, 0)


@requires_numpy_version("2.1.0")
@check_bytes_allocated
def test_fixed_shape_tensor_array_dlpack_permuted():
# A non-trivial permutation makes to_tensor() produce a non-row-major
# tensor: each row-major [3, 2] block is exposed as a logical [2, 3] cell.
storage = pa.FixedSizeListArray.from_arrays(
pa.array(range(24), type=pa.int32()), 6)
arr = pa.ExtensionArray.from_storage(
pa.fixed_shape_tensor(pa.int32(), [3, 2], permutation=[1, 0]), storage)

tensor = arr.to_tensor()
assert tensor.shape == (4, 2, 3)
assert not tensor.is_contiguous

# expected[i, j, k] == i * 6 + k * 2 + j (numpy is only the DLPack consumer)
expected = np.arange(24, dtype=np.int32).reshape(4, 3, 2).transpose(0, 2, 1)
result = np.from_dlpack(DLPackForwarder(arr, max_version=(1, 0)))
np.testing.assert_array_equal(result, expected, strict=True)
assert arr.__dlpack_device__() == (1, 0)


@requires_numpy_version("2.1.0")
@check_bytes_allocated
def test_fixed_shape_tensor_scalar_dlpack():
np_arr = np.arange(12, dtype=np.int32).reshape(3, 2, 2)
arr = pa.FixedShapeTensorArray.from_numpy_ndarray(np_arr)

scalar = arr[1]
assert isinstance(scalar, pa.FixedShapeTensorScalar)
# __dlpack_device__ reads the storage array's device, without building a Tensor.
assert scalar.__dlpack_device__() == (1, 0)

result = np.from_dlpack(DLPackForwarder(scalar, max_version=(1, 0)))
np.testing.assert_array_equal(result, np_arr[1], strict=True)


def multidim_arrays_with_nulls():
np_arr = np.arange(6, dtype=np.int32).reshape(3, 2)
# Masked entries keep defined values in the child array, so the tensor
Expand All@@ -183,12 +224,10 @@ def multidim_arrays_with_nulls():
]


@requires_numpy_version("2.1.0")
@check_bytes_allocated
@pytest.mark.parametrize(('arr', 'expected'), multidim_arrays_with_nulls())
def test_array_to_tensor_dlpack_nulls(arr, expected):
if Version(np.__version__) < Version("2.1.0"):
pytest.skip("Versioned DLPack capsules require numpy 2.1.0 or later")

with pytest.raises(pa.ArrowInvalid, match="Array contains nulls"):
arr.to_tensor()

Expand DownExpand Up@@ -264,25 +303,21 @@ def test_dlpack_versioned_capsule(obj, max_version, copy):
assert PyCapsule_IsValid(capsule, b"dltensor_versioned") is True


@requires_numpy_version("2.1.0")
@check_bytes_allocated
@pytest.mark.parametrize('obj', dlpack_objects())
def test_dlpack_versioned_roundtrip(obj):
if Version(np.__version__) < Version("2.1.0"):
pytest.skip("Versioned DLPack capsules require numpy 2.1.0 or later")

expected = np.from_dlpack(DLPackForwarder(obj, max_version=None))
for copy in [None, False, True]:
result = np.from_dlpack(
DLPackForwarder(obj, max_version=(1, 0), copy=copy))
np.testing.assert_array_equal(result, expected, strict=True)


@requires_numpy_version("2.2.5")
@check_bytes_allocated
def test_dlpack_copy_is_writeable():
# NumPy did not set the writeable flag on DLPack imports before 2.2.5.
if Version(np.__version__) < Version("2.2.5"):
pytest.skip("Writable DLPack imports require numpy 2.2.5 or later")

arr = pa.array([1, 2, 3], type=pa.int32())

# Arrow arrays are immutable, so a shared export is read-only
Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links"); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + '
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GH-38868: [Python] Add dlpack producer to FixedShapeTensorArray/Scalar#51159

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AntoinePrv wants to merge 5 commits into
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GH-38868: [Python] Add dlpack producer to FixedShapeTensorArray/Scalar #51159

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bb34538
Add FixedShapeTensorArray.__dlpack__
AntoinePrv Sep 4, 2026
29bbc29
Factor numpy skips
AntoinePrv Sep 4, 2026
6790bce
Add Dlpack on FixedShapeTensorScalar
AntoinePrv Sep 4, 2026
6bf37d2
Clean up tests
AntoinePrv Sep 4, 2026
ce5c25a
Fix typo
AntoinePrv Sep 4, 2026
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16 changes: 15 additions & 1 deletion python/pyarrow/array.pxi
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -2269,7 +2269,7 @@ cdef class Array(_PandasConvertible):

return pyarrow_wrap_array(array)

def __dlpack__(self, stream=None, max_version=None, dl_device=None, copy=None):
def __dlpack__(self, *, stream=None, max_version=None, dl_device=None, copy=None):
"""
Export a primitive array as a DLPack capsule.

Expand DownExpand Up@@ -5045,6 +5045,20 @@ cdef class FixedShapeTensorArray(ExtensionArray):
FixedSizeListArray.from_arrays(values, shape[1:].prod())
)

def __dlpack__(self, *, stream=None, max_version=None, dl_device=None, copy=None):
"""
Export a tensor array as a DLPack capsule.

The element positions in the array become the first dimension of the
resulting tensor (equal to ``len(self)``).

See :meth:`Tensor.__dlpack__` for the parameter semantics.
"""
return self.to_tensor().__dlpack__(
stream=stream, max_version=max_version,
dl_device=dl_device, copy=copy,
)


cdef class OpaqueArray(ExtensionArray):
"""
Expand Down
29 changes: 29 additions & 0 deletions python/pyarrow/scalar.pxi
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -1586,6 +1586,35 @@ cdef class FixedShapeTensorScalar(ExtensionScalar):
ctensor = GetResultValue(c_type.MakeTensor(scalar))
return pyarrow_wrap_tensor(ctensor)

def __dlpack__(self, *, stream=None, max_version=None, dl_device=None, copy=None):
"""
Export a tensor scalar as a DLPack capsule.

See :meth:`Tensor.__dlpack__` for the parameter semantics.
"""
return self.to_tensor().__dlpack__(
stream=stream, max_version=max_version,
dl_device=dl_device, copy=copy,
)

def __dlpack_device__(self):
"""
Return the DLPack device tuple this scalar resides on.

Returns
-------
tuple : Tuple[int, int]
Tuple with index specifying the type of the device (where
CPU = 1, see cpp/src/arrow/c/dlpack_abi.h) and index of the
device which is 0 by default for CPU.
"""
cdef:
CExtensionScalar* ext = <CExtensionScalar*> self.wrapped.get()
CBaseListScalar* storage = <CBaseListScalar*> ext.value.get()
# The base storage for this type is an Array, so we call into this function
device = GetResultValue(ExportDevice(storage.value))
return device.device_type, device.device_id


cdef class OpaqueScalar(ExtensionScalar):
"""
Expand Down
59 changes: 47 additions & 12 deletions python/pyarrow/tests/test_dlpack.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -29,6 +29,13 @@
np = pytest.importorskip("numpy")


def requires_numpy_version(min_version):
return pytest.mark.skipif(
Version(np.__version__) < Version(min_version),
reason=f"Test requires numpy {min_version} or later",
)


def PyCapsule_IsValid(capsule, name):
return ctypes.pythonapi.PyCapsule_IsValid(ctypes.py_object(capsule), name) == 1

Expand DownExpand Up@@ -150,12 +157,10 @@ def multidim_arrays():
]


@requires_numpy_version("2.1.0")
@check_bytes_allocated
@pytest.mark.parametrize(('arr', 'expected'), multidim_arrays())
def test_array_to_tensor_dlpack(arr, expected):
if Version(np.__version__) < Version("2.1.0"):
pytest.skip("Versioned DLPack capsules require numpy 2.1.0 or later")

tensor = arr.to_tensor()
# A Tensor sharing an Array buffer is immutable, so it can only be exported
# through the versioned DLPack protocol.
Expand All@@ -165,6 +170,42 @@ def test_array_to_tensor_dlpack(arr, expected):
assert tensor.__dlpack_device__() == (1, 0)


@requires_numpy_version("2.1.0")
@check_bytes_allocated
def test_fixed_shape_tensor_array_dlpack_permuted():
# A non-trivial permutation makes to_tensor() produce a non-row-major
# tensor: each row-major [3, 2] block is exposed as a logical [2, 3] cell.
storage = pa.FixedSizeListArray.from_arrays(
pa.array(range(24), type=pa.int32()), 6)
arr = pa.ExtensionArray.from_storage(
pa.fixed_shape_tensor(pa.int32(), [3, 2], permutation=[1, 0]), storage)

tensor = arr.to_tensor()
assert tensor.shape == (4, 2, 3)
assert not tensor.is_contiguous

# expected[i, j, k] == i * 6 + k * 2 + j (numpy is only the DLPack consumer)
expected = np.arange(24, dtype=np.int32).reshape(4, 3, 2).transpose(0, 2, 1)
result = np.from_dlpack(DLPackForwarder(arr, max_version=(1, 0)))
np.testing.assert_array_equal(result, expected, strict=True)
assert arr.__dlpack_device__() == (1, 0)


@requires_numpy_version("2.1.0")
@check_bytes_allocated
def test_fixed_shape_tensor_scalar_dlpack():
np_arr = np.arange(12, dtype=np.int32).reshape(3, 2, 2)
arr = pa.FixedShapeTensorArray.from_numpy_ndarray(np_arr)

scalar = arr[1]
assert isinstance(scalar, pa.FixedShapeTensorScalar)
# __dlpack_device__ reads the storage array's device, without building a Tensor.
assert scalar.__dlpack_device__() == (1, 0)

result = np.from_dlpack(DLPackForwarder(scalar, max_version=(1, 0)))
np.testing.assert_array_equal(result, np_arr[1], strict=True)


def multidim_arrays_with_nulls():
np_arr = np.arange(6, dtype=np.int32).reshape(3, 2)
# Masked entries keep defined values in the child array, so the tensor
Expand All@@ -183,12 +224,10 @@ def multidim_arrays_with_nulls():
]


@requires_numpy_version("2.1.0")
@check_bytes_allocated
@pytest.mark.parametrize(('arr', 'expected'), multidim_arrays_with_nulls())
def test_array_to_tensor_dlpack_nulls(arr, expected):
if Version(np.__version__) < Version("2.1.0"):
pytest.skip("Versioned DLPack capsules require numpy 2.1.0 or later")

with pytest.raises(pa.ArrowInvalid, match="Array contains nulls"):
arr.to_tensor()

Expand DownExpand Up@@ -264,25 +303,21 @@ def test_dlpack_versioned_capsule(obj, max_version, copy):
assert PyCapsule_IsValid(capsule, b"dltensor_versioned") is True


@requires_numpy_version("2.1.0")
@check_bytes_allocated
@pytest.mark.parametrize('obj', dlpack_objects())
def test_dlpack_versioned_roundtrip(obj):
if Version(np.__version__) < Version("2.1.0"):
pytest.skip("Versioned DLPack capsules require numpy 2.1.0 or later")

expected = np.from_dlpack(DLPackForwarder(obj, max_version=None))
for copy in [None, False, True]:
result = np.from_dlpack(
DLPackForwarder(obj, max_version=(1, 0), copy=copy))
np.testing.assert_array_equal(result, expected, strict=True)


@requires_numpy_version("2.2.5")
@check_bytes_allocated
def test_dlpack_copy_is_writeable():
# NumPy did not set the writeable flag on DLPack imports before 2.2.5.
if Version(np.__version__) < Version("2.2.5"):
pytest.skip("Writable DLPack imports require numpy 2.2.5 or later")

arr = pa.array([1, 2, 3], type=pa.int32())

# Arrow arrays are immutable, so a shared export is read-only
Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default"); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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GH-38868: [Python] Add dlpack producer to FixedShapeTensorArray/Scalar#51159

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GH-38868: [Python] Add dlpack producer to FixedShapeTensorArray/Scalar #51159

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bb34538
Add FixedShapeTensorArray.__dlpack__
AntoinePrv Sep 4, 2026
29bbc29
Factor numpy skips
AntoinePrv Sep 4, 2026
6790bce
Add Dlpack on FixedShapeTensorScalar
AntoinePrv Sep 4, 2026
6bf37d2
Clean up tests
AntoinePrv Sep 4, 2026
ce5c25a
Fix typo
AntoinePrv Sep 4, 2026
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16 changes: 15 additions & 1 deletion python/pyarrow/array.pxi
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -2269,7 +2269,7 @@ cdef class Array(_PandasConvertible):

return pyarrow_wrap_array(array)

def __dlpack__(self, stream=None, max_version=None, dl_device=None, copy=None):
def __dlpack__(self, *, stream=None, max_version=None, dl_device=None, copy=None):
"""
Export a primitive array as a DLPack capsule.

Expand DownExpand Up@@ -5045,6 +5045,20 @@ cdef class FixedShapeTensorArray(ExtensionArray):
FixedSizeListArray.from_arrays(values, shape[1:].prod())
)

def __dlpack__(self, *, stream=None, max_version=None, dl_device=None, copy=None):
"""
Export a tensor array as a DLPack capsule.

The element positions in the array become the first dimension of the
resulting tensor (equal to ``len(self)``).

See :meth:`Tensor.__dlpack__` for the parameter semantics.
"""
return self.to_tensor().__dlpack__(
stream=stream, max_version=max_version,
dl_device=dl_device, copy=copy,
)


cdef class OpaqueArray(ExtensionArray):
"""
Expand Down
29 changes: 29 additions & 0 deletions python/pyarrow/scalar.pxi
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -1586,6 +1586,35 @@ cdef class FixedShapeTensorScalar(ExtensionScalar):
ctensor = GetResultValue(c_type.MakeTensor(scalar))
return pyarrow_wrap_tensor(ctensor)

def __dlpack__(self, *, stream=None, max_version=None, dl_device=None, copy=None):
"""
Export a tensor scalar as a DLPack capsule.

See :meth:`Tensor.__dlpack__` for the parameter semantics.
"""
return self.to_tensor().__dlpack__(
stream=stream, max_version=max_version,
dl_device=dl_device, copy=copy,
)

def __dlpack_device__(self):
"""
Return the DLPack device tuple this scalar resides on.

Returns
-------
tuple : Tuple[int, int]
Tuple with index specifying the type of the device (where
CPU = 1, see cpp/src/arrow/c/dlpack_abi.h) and index of the
device which is 0 by default for CPU.
"""
cdef:
CExtensionScalar* ext = <CExtensionScalar*> self.wrapped.get()
CBaseListScalar* storage = <CBaseListScalar*> ext.value.get()
# The base storage for this type is an Array, so we call into this function
device = GetResultValue(ExportDevice(storage.value))
return device.device_type, device.device_id


cdef class OpaqueScalar(ExtensionScalar):
"""
Expand Down
59 changes: 47 additions & 12 deletions python/pyarrow/tests/test_dlpack.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -29,6 +29,13 @@
np = pytest.importorskip("numpy")


def requires_numpy_version(min_version):
return pytest.mark.skipif(
Version(np.__version__) < Version(min_version),
reason=f"Test requires numpy {min_version} or later",
)


def PyCapsule_IsValid(capsule, name):
return ctypes.pythonapi.PyCapsule_IsValid(ctypes.py_object(capsule), name) == 1

Expand DownExpand Up@@ -150,12 +157,10 @@ def multidim_arrays():
]


@requires_numpy_version("2.1.0")
@check_bytes_allocated
@pytest.mark.parametrize(('arr', 'expected'), multidim_arrays())
def test_array_to_tensor_dlpack(arr, expected):
if Version(np.__version__) < Version("2.1.0"):
pytest.skip("Versioned DLPack capsules require numpy 2.1.0 or later")

tensor = arr.to_tensor()
# A Tensor sharing an Array buffer is immutable, so it can only be exported
# through the versioned DLPack protocol.
Expand All@@ -165,6 +170,42 @@ def test_array_to_tensor_dlpack(arr, expected):
assert tensor.__dlpack_device__() == (1, 0)


@requires_numpy_version("2.1.0")
@check_bytes_allocated
def test_fixed_shape_tensor_array_dlpack_permuted():
# A non-trivial permutation makes to_tensor() produce a non-row-major
# tensor: each row-major [3, 2] block is exposed as a logical [2, 3] cell.
storage = pa.FixedSizeListArray.from_arrays(
pa.array(range(24), type=pa.int32()), 6)
arr = pa.ExtensionArray.from_storage(
pa.fixed_shape_tensor(pa.int32(), [3, 2], permutation=[1, 0]), storage)

tensor = arr.to_tensor()
assert tensor.shape == (4, 2, 3)
assert not tensor.is_contiguous

# expected[i, j, k] == i * 6 + k * 2 + j (numpy is only the DLPack consumer)
expected = np.arange(24, dtype=np.int32).reshape(4, 3, 2).transpose(0, 2, 1)
result = np.from_dlpack(DLPackForwarder(arr, max_version=(1, 0)))
np.testing.assert_array_equal(result, expected, strict=True)
assert arr.__dlpack_device__() == (1, 0)


@requires_numpy_version("2.1.0")
@check_bytes_allocated
def test_fixed_shape_tensor_scalar_dlpack():
np_arr = np.arange(12, dtype=np.int32).reshape(3, 2, 2)
arr = pa.FixedShapeTensorArray.from_numpy_ndarray(np_arr)

scalar = arr[1]
assert isinstance(scalar, pa.FixedShapeTensorScalar)
# __dlpack_device__ reads the storage array's device, without building a Tensor.
assert scalar.__dlpack_device__() == (1, 0)

result = np.from_dlpack(DLPackForwarder(scalar, max_version=(1, 0)))
np.testing.assert_array_equal(result, np_arr[1], strict=True)


def multidim_arrays_with_nulls():
np_arr = np.arange(6, dtype=np.int32).reshape(3, 2)
# Masked entries keep defined values in the child array, so the tensor
Expand All@@ -183,12 +224,10 @@ def multidim_arrays_with_nulls():
]


@requires_numpy_version("2.1.0")
@check_bytes_allocated
@pytest.mark.parametrize(('arr', 'expected'), multidim_arrays_with_nulls())
def test_array_to_tensor_dlpack_nulls(arr, expected):
if Version(np.__version__) < Version("2.1.0"):
pytest.skip("Versioned DLPack capsules require numpy 2.1.0 or later")

with pytest.raises(pa.ArrowInvalid, match="Array contains nulls"):
arr.to_tensor()

Expand DownExpand Up@@ -264,25 +303,21 @@ def test_dlpack_versioned_capsule(obj, max_version, copy):
assert PyCapsule_IsValid(capsule, b"dltensor_versioned") is True


@requires_numpy_version("2.1.0")
@check_bytes_allocated
@pytest.mark.parametrize('obj', dlpack_objects())
def test_dlpack_versioned_roundtrip(obj):
if Version(np.__version__) < Version("2.1.0"):
pytest.skip("Versioned DLPack capsules require numpy 2.1.0 or later")

expected = np.from_dlpack(DLPackForwarder(obj, max_version=None))
for copy in [None, False, True]:
result = np.from_dlpack(
DLPackForwarder(obj, max_version=(1, 0), copy=copy))
np.testing.assert_array_equal(result, expected, strict=True)


@requires_numpy_version("2.2.5")
@check_bytes_allocated
def test_dlpack_copy_is_writeable():
# NumPy did not set the writeable flag on DLPack imports before 2.2.5.
if Version(np.__version__) < Version("2.2.5"):
pytest.skip("Writable DLPack imports require numpy 2.2.5 or later")

arr = pa.array([1, 2, 3], type=pa.int32())

# Arrow arrays are immutable, so a shared export is read-only
Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers"); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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GH-38868: [Python] Add dlpack producer to FixedShapeTensorArray/Scalar#51159

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GH-38868: [Python] Add dlpack producer to FixedShapeTensorArray/Scalar #51159

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bb34538
Add FixedShapeTensorArray.__dlpack__
AntoinePrv Sep 4, 2026
29bbc29
Factor numpy skips
AntoinePrv Sep 4, 2026
6790bce
Add Dlpack on FixedShapeTensorScalar
AntoinePrv Sep 4, 2026
6bf37d2
Clean up tests
AntoinePrv Sep 4, 2026
ce5c25a
Fix typo
AntoinePrv Sep 4, 2026
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16 changes: 15 additions & 1 deletion python/pyarrow/array.pxi
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -2269,7 +2269,7 @@ cdef class Array(_PandasConvertible):

return pyarrow_wrap_array(array)

def __dlpack__(self, stream=None, max_version=None, dl_device=None, copy=None):
def __dlpack__(self, *, stream=None, max_version=None, dl_device=None, copy=None):
"""
Export a primitive array as a DLPack capsule.

Expand DownExpand Up@@ -5045,6 +5045,20 @@ cdef class FixedShapeTensorArray(ExtensionArray):
FixedSizeListArray.from_arrays(values, shape[1:].prod())
)

def __dlpack__(self, *, stream=None, max_version=None, dl_device=None, copy=None):
"""
Export a tensor array as a DLPack capsule.

The element positions in the array become the first dimension of the
resulting tensor (equal to ``len(self)``).

See :meth:`Tensor.__dlpack__` for the parameter semantics.
"""
return self.to_tensor().__dlpack__(
stream=stream, max_version=max_version,
dl_device=dl_device, copy=copy,
)


cdef class OpaqueArray(ExtensionArray):
"""
Expand Down
29 changes: 29 additions & 0 deletions python/pyarrow/scalar.pxi
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -1586,6 +1586,35 @@ cdef class FixedShapeTensorScalar(ExtensionScalar):
ctensor = GetResultValue(c_type.MakeTensor(scalar))
return pyarrow_wrap_tensor(ctensor)

def __dlpack__(self, *, stream=None, max_version=None, dl_device=None, copy=None):
"""
Export a tensor scalar as a DLPack capsule.

See :meth:`Tensor.__dlpack__` for the parameter semantics.
"""
return self.to_tensor().__dlpack__(
stream=stream, max_version=max_version,
dl_device=dl_device, copy=copy,
)

def __dlpack_device__(self):
"""
Return the DLPack device tuple this scalar resides on.

Returns
-------
tuple : Tuple[int, int]
Tuple with index specifying the type of the device (where
CPU = 1, see cpp/src/arrow/c/dlpack_abi.h) and index of the
device which is 0 by default for CPU.
"""
cdef:
CExtensionScalar* ext = <CExtensionScalar*> self.wrapped.get()
CBaseListScalar* storage = <CBaseListScalar*> ext.value.get()
# The base storage for this type is an Array, so we call into this function
device = GetResultValue(ExportDevice(storage.value))
return device.device_type, device.device_id


cdef class OpaqueScalar(ExtensionScalar):
"""
Expand Down
59 changes: 47 additions & 12 deletions python/pyarrow/tests/test_dlpack.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -29,6 +29,13 @@
np = pytest.importorskip("numpy")


def requires_numpy_version(min_version):
return pytest.mark.skipif(
Version(np.__version__) < Version(min_version),
reason=f"Test requires numpy {min_version} or later",
)


def PyCapsule_IsValid(capsule, name):
return ctypes.pythonapi.PyCapsule_IsValid(ctypes.py_object(capsule), name) == 1

Expand DownExpand Up@@ -150,12 +157,10 @@ def multidim_arrays():
]


@requires_numpy_version("2.1.0")
@check_bytes_allocated
@pytest.mark.parametrize(('arr', 'expected'), multidim_arrays())
def test_array_to_tensor_dlpack(arr, expected):
if Version(np.__version__) < Version("2.1.0"):
pytest.skip("Versioned DLPack capsules require numpy 2.1.0 or later")

tensor = arr.to_tensor()
# A Tensor sharing an Array buffer is immutable, so it can only be exported
# through the versioned DLPack protocol.
Expand All@@ -165,6 +170,42 @@ def test_array_to_tensor_dlpack(arr, expected):
assert tensor.__dlpack_device__() == (1, 0)


@requires_numpy_version("2.1.0")
@check_bytes_allocated
def test_fixed_shape_tensor_array_dlpack_permuted():
# A non-trivial permutation makes to_tensor() produce a non-row-major
# tensor: each row-major [3, 2] block is exposed as a logical [2, 3] cell.
storage = pa.FixedSizeListArray.from_arrays(
pa.array(range(24), type=pa.int32()), 6)
arr = pa.ExtensionArray.from_storage(
pa.fixed_shape_tensor(pa.int32(), [3, 2], permutation=[1, 0]), storage)

tensor = arr.to_tensor()
assert tensor.shape == (4, 2, 3)
assert not tensor.is_contiguous

# expected[i, j, k] == i * 6 + k * 2 + j (numpy is only the DLPack consumer)
expected = np.arange(24, dtype=np.int32).reshape(4, 3, 2).transpose(0, 2, 1)
result = np.from_dlpack(DLPackForwarder(arr, max_version=(1, 0)))
np.testing.assert_array_equal(result, expected, strict=True)
assert arr.__dlpack_device__() == (1, 0)


@requires_numpy_version("2.1.0")
@check_bytes_allocated
def test_fixed_shape_tensor_scalar_dlpack():
np_arr = np.arange(12, dtype=np.int32).reshape(3, 2, 2)
arr = pa.FixedShapeTensorArray.from_numpy_ndarray(np_arr)

scalar = arr[1]
assert isinstance(scalar, pa.FixedShapeTensorScalar)
# __dlpack_device__ reads the storage array's device, without building a Tensor.
assert scalar.__dlpack_device__() == (1, 0)

result = np.from_dlpack(DLPackForwarder(scalar, max_version=(1, 0)))
np.testing.assert_array_equal(result, np_arr[1], strict=True)


def multidim_arrays_with_nulls():
np_arr = np.arange(6, dtype=np.int32).reshape(3, 2)
# Masked entries keep defined values in the child array, so the tensor
Expand All@@ -183,12 +224,10 @@ def multidim_arrays_with_nulls():
]


@requires_numpy_version("2.1.0")
@check_bytes_allocated
@pytest.mark.parametrize(('arr', 'expected'), multidim_arrays_with_nulls())
def test_array_to_tensor_dlpack_nulls(arr, expected):
if Version(np.__version__) < Version("2.1.0"):
pytest.skip("Versioned DLPack capsules require numpy 2.1.0 or later")

with pytest.raises(pa.ArrowInvalid, match="Array contains nulls"):
arr.to_tensor()

Expand DownExpand Up@@ -264,25 +303,21 @@ def test_dlpack_versioned_capsule(obj, max_version, copy):
assert PyCapsule_IsValid(capsule, b"dltensor_versioned") is True


@requires_numpy_version("2.1.0")
@check_bytes_allocated
@pytest.mark.parametrize('obj', dlpack_objects())
def test_dlpack_versioned_roundtrip(obj):
if Version(np.__version__) < Version("2.1.0"):
pytest.skip("Versioned DLPack capsules require numpy 2.1.0 or later")

expected = np.from_dlpack(DLPackForwarder(obj, max_version=None))
for copy in [None, False, True]:
result = np.from_dlpack(
DLPackForwarder(obj, max_version=(1, 0), copy=copy))
np.testing.assert_array_equal(result, expected, strict=True)


@requires_numpy_version("2.2.5")
@check_bytes_allocated
def test_dlpack_copy_is_writeable():
# NumPy did not set the writeable flag on DLPack imports before 2.2.5.
if Version(np.__version__) < Version("2.2.5"):
pytest.skip("Writable DLPack imports require numpy 2.2.5 or later")

arr = pa.array([1, 2, 3], type=pa.int32())

# Arrow arrays are immutable, so a shared export is read-only
Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode"); } } catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); } })(); })();
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GH-38868: [Python] Add dlpack producer to FixedShapeTensorArray/Scalar#51159

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AntoinePrv wants to merge 5 commits into
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GH-38868: [Python] Add dlpack producer to FixedShapeTensorArray/Scalar #51159

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bb34538
Add FixedShapeTensorArray.__dlpack__
AntoinePrv Sep 4, 2026
29bbc29
Factor numpy skips
AntoinePrv Sep 4, 2026
6790bce
Add Dlpack on FixedShapeTensorScalar
AntoinePrv Sep 4, 2026
6bf37d2
Clean up tests
AntoinePrv Sep 4, 2026
ce5c25a
Fix typo
AntoinePrv Sep 4, 2026
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16 changes: 15 additions & 1 deletion python/pyarrow/array.pxi
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -2269,7 +2269,7 @@ cdef class Array(_PandasConvertible):

return pyarrow_wrap_array(array)

def __dlpack__(self, stream=None, max_version=None, dl_device=None, copy=None):
def __dlpack__(self, *, stream=None, max_version=None, dl_device=None, copy=None):
"""
Export a primitive array as a DLPack capsule.

Expand DownExpand Up@@ -5045,6 +5045,20 @@ cdef class FixedShapeTensorArray(ExtensionArray):
FixedSizeListArray.from_arrays(values, shape[1:].prod())
)

def __dlpack__(self, *, stream=None, max_version=None, dl_device=None, copy=None):
"""
Export a tensor array as a DLPack capsule.

The element positions in the array become the first dimension of the
resulting tensor (equal to ``len(self)``).

See :meth:`Tensor.__dlpack__` for the parameter semantics.
"""
return self.to_tensor().__dlpack__(
stream=stream, max_version=max_version,
dl_device=dl_device, copy=copy,
)


cdef class OpaqueArray(ExtensionArray):
"""
Expand Down
29 changes: 29 additions & 0 deletions python/pyarrow/scalar.pxi
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -1586,6 +1586,35 @@ cdef class FixedShapeTensorScalar(ExtensionScalar):
ctensor = GetResultValue(c_type.MakeTensor(scalar))
return pyarrow_wrap_tensor(ctensor)

def __dlpack__(self, *, stream=None, max_version=None, dl_device=None, copy=None):
"""
Export a tensor scalar as a DLPack capsule.

See :meth:`Tensor.__dlpack__` for the parameter semantics.
"""
return self.to_tensor().__dlpack__(
stream=stream, max_version=max_version,
dl_device=dl_device, copy=copy,
)

def __dlpack_device__(self):
"""
Return the DLPack device tuple this scalar resides on.

Returns
-------
tuple : Tuple[int, int]
Tuple with index specifying the type of the device (where
CPU = 1, see cpp/src/arrow/c/dlpack_abi.h) and index of the
device which is 0 by default for CPU.
"""
cdef:
CExtensionScalar* ext = <CExtensionScalar*> self.wrapped.get()
CBaseListScalar* storage = <CBaseListScalar*> ext.value.get()
# The base storage for this type is an Array, so we call into this function
device = GetResultValue(ExportDevice(storage.value))
return device.device_type, device.device_id


cdef class OpaqueScalar(ExtensionScalar):
"""
Expand Down
59 changes: 47 additions & 12 deletions python/pyarrow/tests/test_dlpack.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -29,6 +29,13 @@
np = pytest.importorskip("numpy")


def requires_numpy_version(min_version):
return pytest.mark.skipif(
Version(np.__version__) < Version(min_version),
reason=f"Test requires numpy {min_version} or later",
)


def PyCapsule_IsValid(capsule, name):
return ctypes.pythonapi.PyCapsule_IsValid(ctypes.py_object(capsule), name) == 1

Expand DownExpand Up@@ -150,12 +157,10 @@ def multidim_arrays():
]


@requires_numpy_version("2.1.0")
@check_bytes_allocated
@pytest.mark.parametrize(('arr', 'expected'), multidim_arrays())
def test_array_to_tensor_dlpack(arr, expected):
if Version(np.__version__) < Version("2.1.0"):
pytest.skip("Versioned DLPack capsules require numpy 2.1.0 or later")

tensor = arr.to_tensor()
# A Tensor sharing an Array buffer is immutable, so it can only be exported
# through the versioned DLPack protocol.
Expand All@@ -165,6 +170,42 @@ def test_array_to_tensor_dlpack(arr, expected):
assert tensor.__dlpack_device__() == (1, 0)


@requires_numpy_version("2.1.0")
@check_bytes_allocated
def test_fixed_shape_tensor_array_dlpack_permuted():
# A non-trivial permutation makes to_tensor() produce a non-row-major
# tensor: each row-major [3, 2] block is exposed as a logical [2, 3] cell.
storage = pa.FixedSizeListArray.from_arrays(
pa.array(range(24), type=pa.int32()), 6)
arr = pa.ExtensionArray.from_storage(
pa.fixed_shape_tensor(pa.int32(), [3, 2], permutation=[1, 0]), storage)

tensor = arr.to_tensor()
assert tensor.shape == (4, 2, 3)
assert not tensor.is_contiguous

# expected[i, j, k] == i * 6 + k * 2 + j (numpy is only the DLPack consumer)
expected = np.arange(24, dtype=np.int32).reshape(4, 3, 2).transpose(0, 2, 1)
result = np.from_dlpack(DLPackForwarder(arr, max_version=(1, 0)))
np.testing.assert_array_equal(result, expected, strict=True)
assert arr.__dlpack_device__() == (1, 0)


@requires_numpy_version("2.1.0")
@check_bytes_allocated
def test_fixed_shape_tensor_scalar_dlpack():
np_arr = np.arange(12, dtype=np.int32).reshape(3, 2, 2)
arr = pa.FixedShapeTensorArray.from_numpy_ndarray(np_arr)

scalar = arr[1]
assert isinstance(scalar, pa.FixedShapeTensorScalar)
# __dlpack_device__ reads the storage array's device, without building a Tensor.
assert scalar.__dlpack_device__() == (1, 0)

result = np.from_dlpack(DLPackForwarder(scalar, max_version=(1, 0)))
np.testing.assert_array_equal(result, np_arr[1], strict=True)


def multidim_arrays_with_nulls():
np_arr = np.arange(6, dtype=np.int32).reshape(3, 2)
# Masked entries keep defined values in the child array, so the tensor
Expand All@@ -183,12 +224,10 @@ def multidim_arrays_with_nulls():
]


@requires_numpy_version("2.1.0")
@check_bytes_allocated
@pytest.mark.parametrize(('arr', 'expected'), multidim_arrays_with_nulls())
def test_array_to_tensor_dlpack_nulls(arr, expected):
if Version(np.__version__) < Version("2.1.0"):
pytest.skip("Versioned DLPack capsules require numpy 2.1.0 or later")

with pytest.raises(pa.ArrowInvalid, match="Array contains nulls"):
arr.to_tensor()

Expand DownExpand Up@@ -264,25 +303,21 @@ def test_dlpack_versioned_capsule(obj, max_version, copy):
assert PyCapsule_IsValid(capsule, b"dltensor_versioned") is True


@requires_numpy_version("2.1.0")
@check_bytes_allocated
@pytest.mark.parametrize('obj', dlpack_objects())
def test_dlpack_versioned_roundtrip(obj):
if Version(np.__version__) < Version("2.1.0"):
pytest.skip("Versioned DLPack capsules require numpy 2.1.0 or later")

expected = np.from_dlpack(DLPackForwarder(obj, max_version=None))
for copy in [None, False, True]:
result = np.from_dlpack(
DLPackForwarder(obj, max_version=(1, 0), copy=copy))
np.testing.assert_array_equal(result, expected, strict=True)


@requires_numpy_version("2.2.5")
@check_bytes_allocated
def test_dlpack_copy_is_writeable():
# NumPy did not set the writeable flag on DLPack imports before 2.2.5.
if Version(np.__version__) < Version("2.2.5"):
pytest.skip("Writable DLPack imports require numpy 2.2.5 or later")

arr = pa.array([1, 2, 3], type=pa.int32())

# Arrow arrays are immutable, so a shared export is read-only
Expand Down