pitrou commented on code in PR #38472:
URL: https://github.com/apache/arrow/pull/38472#discussion_r1414141534
##########
python/pyarrow/array.pxi:
##########
@@ -1778,6 +1778,40 @@ cdef class Array(_PandasConvertible):
return pyarrow_wrap_array(array)
+ def __dlpack__(self, stream=None):
+ """Export a primitive array as a DLPack capsule.
+
+ Parameters
+ ----------
+ stream : int, optional
+ A Python integer representing a pointer to a stream. Currently not
supported.
+ Stream is provided by the consumer to the producer to instruct the
producer
+ to ensure that operations can safely be performed on the array.
+
+ Returns
+ -------
+ capsule : PyCapsule
+ A DLPack capsule for the array, containing a DLPackManagedTensor.
+ """
+ if stream is None:
+ return to_dlpack(self)
+ else:
+ raise NotImplementedError(
+ "Only stream=None is supported."
+ )
+
+ def __dlpack_device__(self):
+ """
+ Performs the operation __dlpack_device__.
Review Comment:
Where is this specified? I see nothing in
https://dmlc.github.io/dlpack/latest/python_spec.html
##########
cpp/src/arrow/c/dlpack.h:
##########
@@ -0,0 +1,58 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements. See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership. The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License. You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied. See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+#pragma once
+
+#include "arrow/array/array_base.h"
+#include "arrow/c/dlpack_abi.h"
+
+namespace arrow {
+
+namespace dlpack {
Review Comment:
Nit: can use C++17 nested namespace declarations
```suggestion
namespace arrow::dlpack {
```
(you'll have to change the closing braces as well)
##########
cpp/src/arrow/c/dlpack.cc:
##########
@@ -0,0 +1,151 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements. See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership. The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License. You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied. See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+#include "arrow/c/dlpack.h"
+
+#include "arrow/array/array_base.h"
+#include "arrow/c/dlpack_abi.h"
+#include "arrow/device.h"
+#include "arrow/type.h"
+
+namespace arrow {
+
+namespace dlpack {
+
+Status getDLDataType(const std::shared_ptr<DataType>& type, DLDataType* out) {
Review Comment:
1. naming style, 2. Result instead of out-ptr, 3. no need for shared_ptr
here :-)
```suggestion
Result<DLDataType> GetDLDataType(const DataType& type) {
```
##########
cpp/src/arrow/c/dlpack.h:
##########
@@ -0,0 +1,58 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements. See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership. The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License. You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied. See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+#pragma once
+
+#include "arrow/array/array_base.h"
+#include "arrow/c/dlpack_abi.h"
+
+namespace arrow {
+
+namespace dlpack {
+
+/// \brief DLPack protocol for producing DLManagedTensor
+///
+/// DLMangedTensor is produced from an array as defined by
+/// the DLPack protocol, see https://dmlc.github.io/dlpack/latest/.
+///
+/// Data types for which the protocol is supported are
+/// primitive data types without NullType, BooleanType and
+/// Decimal types.
+///
+/// DLPack protocol only supports arrays with one contiguous
+/// memory region which means Arrow Arrays with validity buffers
+/// are not supported.
+///
+/// \param[in] arr Arrow array
+/// \param[out] out DLManagedTensor struct
+/// \return Status
+ARROW_EXPORT
+Status ExportArray(const std::shared_ptr<Array>& arr, DLManagedTensor** out);
+
+/// \brief Get DLDevice with enumerator specifying the
+/// type of the device data is stored on and index of the
+/// device which is 0 by default for CPU.
+///
+/// \param[in] arr Arrow array
+/// \param[out] out DLDevice struct
+/// \return DLDevice
+ARROW_EXPORT
+Status ExportDevice(const std::shared_ptr<Array>& arr, DLDevice* out);
Review Comment:
```suggestion
Result<DLDevice> ExportDevice(const std::shared_ptr<Array>& arr);
```
##########
cpp/src/arrow/c/dlpack_test.cc:
##########
@@ -0,0 +1,122 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements. See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership. The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License. You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied. See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+#include <gtest/gtest.h>
+
+#include "arrow/array/array_base.h"
+#include "arrow/c/dlpack.h"
+#include "arrow/c/dlpack_abi.h"
+#include "arrow/testing/gtest_util.h"
+#include "arrow/testing/random.h"
+
+namespace arrow {
+
+namespace dlpack {
Review Comment:
Nit
```suggestion
namespace arrow::dlpack {
```
##########
cpp/src/arrow/c/dlpack.cc:
##########
@@ -0,0 +1,151 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements. See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership. The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License. You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied. See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+#include "arrow/c/dlpack.h"
+
+#include "arrow/array/array_base.h"
+#include "arrow/c/dlpack_abi.h"
+#include "arrow/device.h"
+#include "arrow/type.h"
+
+namespace arrow {
+
+namespace dlpack {
+
+Status getDLDataType(const std::shared_ptr<DataType>& type, DLDataType* out) {
+ DLDataType dtype;
+ dtype.lanes = 1;
+ dtype.bits = type->bit_width();
+ switch (type->id()) {
+ case Type::INT8:
+ case Type::INT16:
+ case Type::INT32:
+ case Type::INT64:
+ dtype.code = DLDataTypeCode::kDLInt;
+ *out = dtype;
+ return Status::OK();
+ case Type::UINT8:
+ case Type::UINT16:
+ case Type::UINT32:
+ case Type::UINT64:
+ dtype.code = DLDataTypeCode::kDLUInt;
+ *out = dtype;
+ return Status::OK();
+ case Type::HALF_FLOAT:
+ case Type::FLOAT:
+ case Type::DOUBLE:
+ dtype.code = DLDataTypeCode::kDLFloat;
+ *out = dtype;
+ return Status::OK();
+ case Type::BOOL:
+ // DLPack supports byte-packed boolean values
+ return Status::TypeError("Bit-packed boolean data type not supported by
DLPack.");
+ default:
+ return Status::TypeError(
+ "Can only use __dlpack__ on primitive arrays without NullType and
Decimal "
+ "types.");
+ }
+}
Review Comment:
Do we plan to later support `fixed_shape_tensor` extension arrays?
##########
cpp/src/arrow/c/dlpack.h:
##########
@@ -0,0 +1,58 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements. See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership. The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License. You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied. See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+#pragma once
+
+#include "arrow/array/array_base.h"
+#include "arrow/c/dlpack_abi.h"
+
+namespace arrow {
+
+namespace dlpack {
+
+/// \brief DLPack protocol for producing DLManagedTensor
+///
+/// DLMangedTensor is produced from an array as defined by
+/// the DLPack protocol, see https://dmlc.github.io/dlpack/latest/.
+///
+/// Data types for which the protocol is supported are
+/// primitive data types without NullType, BooleanType and
+/// Decimal types.
+///
+/// DLPack protocol only supports arrays with one contiguous
+/// memory region which means Arrow Arrays with validity buffers
+/// are not supported.
+///
+/// \param[in] arr Arrow array
+/// \param[out] out DLManagedTensor struct
+/// \return Status
+ARROW_EXPORT
+Status ExportArray(const std::shared_ptr<Array>& arr, DLManagedTensor** out);
Review Comment:
Instead of returning a Status and writing into a separate out pointer, we
should simply return a Result:
```suggestion
Result<DLManagedTensor*> ExportArray(const std::shared_ptr<Array>& arr);
```
##########
cpp/src/arrow/c/dlpack.cc:
##########
@@ -0,0 +1,151 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements. See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership. The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License. You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied. See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+#include "arrow/c/dlpack.h"
+
+#include "arrow/array/array_base.h"
+#include "arrow/c/dlpack_abi.h"
+#include "arrow/device.h"
+#include "arrow/type.h"
+
+namespace arrow {
+
+namespace dlpack {
+
+Status getDLDataType(const std::shared_ptr<DataType>& type, DLDataType* out) {
+ DLDataType dtype;
+ dtype.lanes = 1;
+ dtype.bits = type->bit_width();
+ switch (type->id()) {
+ case Type::INT8:
+ case Type::INT16:
+ case Type::INT32:
+ case Type::INT64:
+ dtype.code = DLDataTypeCode::kDLInt;
+ *out = dtype;
+ return Status::OK();
+ case Type::UINT8:
+ case Type::UINT16:
+ case Type::UINT32:
+ case Type::UINT64:
+ dtype.code = DLDataTypeCode::kDLUInt;
+ *out = dtype;
+ return Status::OK();
+ case Type::HALF_FLOAT:
+ case Type::FLOAT:
+ case Type::DOUBLE:
+ dtype.code = DLDataTypeCode::kDLFloat;
+ *out = dtype;
+ return Status::OK();
+ case Type::BOOL:
+ // DLPack supports byte-packed boolean values
+ return Status::TypeError("Bit-packed boolean data type not supported by
DLPack.");
+ default:
+ return Status::TypeError(
+ "Can only use __dlpack__ on primitive arrays without NullType and
Decimal "
+ "types.");
+ }
+}
+
+struct DLMTensorCtx {
+ std::shared_ptr<ArrayData> ref;
+ std::vector<int64_t> shape;
+ DLManagedTensor tensor;
+};
+
+static void deleter(DLManagedTensor* arg) {
+ delete static_cast<DLMTensorCtx*>(arg->manager_ctx);
+}
+
+Status ExportArray(const std::shared_ptr<Array>& arr, DLManagedTensor** out) {
+ if (arr->null_count() > 0) {
+ return Status::TypeError("Can only use __dlpack__ on arrays with no
nulls.");
+ }
+
+ // Define the DLDataType struct
+ // Supported data types: int, uint, float
+ DLDataType arr_type;
+ RETURN_NOT_OK(getDLDataType(arr->type(), &arr_type));
+
+ // Create DLMTensorCtx struct with the reference to
+ // the data of the array
+ std::shared_ptr<ArrayData> array_ref = arr->data();
+ DLMTensorCtx* DLMTensor = new DLMTensorCtx;
+ DLMTensor->ref = array_ref;
+
+ // Define DLManagedTensor struct defined by
+ // DLPack (dlpack_structure.h)
+ DLManagedTensor* dlm_tensor = &DLMTensor->tensor;
+ dlm_tensor->manager_ctx = DLMTensor;
+ dlm_tensor->deleter = &deleter;
+
+ // Define the data pointer to the DLTensor
+ // If array is of length 0, data pointer should be NULL
+ if (arr->length() == 0) {
+ dlm_tensor->dl_tensor.data = NULL;
+ } else if (arr->offset() > 0) {
+ const auto byte_width = arr->type()->byte_width();
+ const auto start = arr->offset() * byte_width;
+ ARROW_ASSIGN_OR_RAISE(auto sliced_buffer,
+ SliceBufferSafe(array_ref->buffers[1], start));
+ dlm_tensor->dl_tensor.data =
+ const_cast<void*>(reinterpret_cast<const
void*>(sliced_buffer->address()));
+ } else {
+ dlm_tensor->dl_tensor.data = const_cast<void*>(
+ reinterpret_cast<const void*>(array_ref->buffers[1]->address()));
+ }
+
+ // Define DLDevice struct
+ DLDevice ctx;
+ if (array_ref->buffers[1]->device_type() == DeviceAllocationType::kCPU) {
+ ctx.device_id = 0;
+ ctx.device_type = DLDeviceType::kDLCPU;
+ } else {
+ return Status::NotImplemented(
+ "DLPack support is implemented only for buffers on CPU device.");
+ }
+ dlm_tensor->dl_tensor.device = ctx;
+
+ dlm_tensor->dl_tensor.ndim = 1;
+ dlm_tensor->dl_tensor.dtype = arr_type;
+ std::vector<int64_t>* shape_arr = &DLMTensor->shape;
+ shape_arr->resize(1);
+ (*shape_arr)[0] = arr->length();
+ dlm_tensor->dl_tensor.shape = shape_arr->data();
+ dlm_tensor->dl_tensor.strides = NULL;
+ dlm_tensor->dl_tensor.byte_offset = 0;
+
+ *out = dlm_tensor;
+ return Status::OK();
+}
+
+Status ExportDevice(const std::shared_ptr<Array>& arr, DLDevice* out) {
+ DLDevice device;
+ if (arr->data()->buffers[1]->device_type() == DeviceAllocationType::kCPU) {
Review Comment:
We shouldn't blindly access buffer #1.
Instead we should first check that the array type is supported by DLPack,
and raise a `TypeError` if not.
##########
python/pyarrow/_dlpack.pxi:
##########
@@ -0,0 +1,62 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+from libc.stdlib cimport malloc, free
+
+cimport cpython
+from cpython.pycapsule cimport PyCapsule_New
+from cython import sizeof
+
+
+cdef void pycapsule_deleter(object dltensor) noexcept:
+ cdef DLManagedTensor* dlm_tensor
+ cdef PyObject* err_type
+ cdef PyObject* err_value
+ cdef PyObject* err_traceback
+
+ # Do nothing if the capsule has been consumed
+ if cpython.PyCapsule_IsValid(dltensor, "used_dltensor"):
+ return
+
+ # An exception may be in-flight, we must save it in case
+ # we create another one
+ cpython.PyErr_Fetch(&err_type, &err_value, &err_traceback)
+
+ if cpython.PyCapsule_IsValid(dltensor, 'dltensor'):
+ dlm_tensor = <DLManagedTensor*>cpython.PyCapsule_GetPointer(
+ dltensor, 'dltensor')
+ dlm_tensor.deleter(dlm_tensor)
+ else:
+ cpython.PyErr_WriteUnraisable(dltensor)
+
+ # Set the error indicator from err_type, err_value, err_traceback
+ cpython.PyErr_Restore(err_type, err_value, err_traceback)
+
+
+cpdef object to_dlpack(Array arr) except *:
+
+ cdef DLManagedTensor* dlm_tensor
+ check_status(ExportToDLPack(pyarrow_unwrap_array(arr), &dlm_tensor))
+
+ return PyCapsule_New(dlm_tensor, 'dltensor', pycapsule_deleter)
+
+cpdef object dlpack_device(Array arr) except *:
+
+ cdef DLDevice device
+ check_status(ExportDevice(pyarrow_unwrap_array(arr), &device))
+
+ return (device.device_type, device.device_id)
Review Comment:
This code could go directly in the Array method implementations, I don't
think it's useful to have them here.
##########
python/pyarrow/tests/test_array.py:
##########
@@ -3546,3 +3548,123 @@ def test_run_end_encoded_from_buffers():
with pytest.raises(ValueError):
pa.RunEndEncodedArray.from_buffers(ree_type, length, buffers,
1, offset, children)
+
+
+def PyCapsule_IsValid(capsule, name):
+ return ctypes.pythonapi.PyCapsule_IsValid(ctypes.py_object(capsule), name)
== 1
+
+
[email protected](
+ ('value_type', 'np_type'),
+ [
+ (pa.uint8(), np.uint8),
+ (pa.uint16(), np.uint16),
+ (pa.uint32(), np.uint32),
+ (pa.uint64(), np.uint64),
+ (pa.int8(), np.int8),
+ (pa.int16(), np.int16),
+ (pa.int32(), np.int32),
+ (pa.int64(), np.int64),
+ (pa.float16(), np.float16),
+ (pa.float32(), np.float32),
+ (pa.float64(), np.float64),
+ ]
+)
+def test_dlpack(value_type, np_type):
+ if Version(np.__version__) < Version("1.24.0"):
+ pytest.skip("No dlpack support in numpy versions older than 1.22.0, "
+ "strict keyward in assert_array_equal added in numpy
version "
Review Comment:
```suggestion
"strict keyword in assert_array_equal added in numpy
version "
```
##########
python/pyarrow/array.pxi:
##########
@@ -1778,6 +1778,40 @@ cdef class Array(_PandasConvertible):
return pyarrow_wrap_array(array)
+ def __dlpack__(self, stream=None):
+ """Export a primitive array as a DLPack capsule.
+
+ Parameters
+ ----------
+ stream : int, optional
+ A Python integer representing a pointer to a stream. Currently not
supported.
+ Stream is provided by the consumer to the producer to instruct the
producer
+ to ensure that operations can safely be performed on the array.
+
+ Returns
+ -------
+ capsule : PyCapsule
+ A DLPack capsule for the array, containing a DLPackManagedTensor.
Review Comment:
```suggestion
A DLPack capsule for the array, pointing to a DLManagedTensor.
```
##########
cpp/src/arrow/c/dlpack.cc:
##########
@@ -0,0 +1,151 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements. See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership. The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License. You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied. See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+#include "arrow/c/dlpack.h"
+
+#include "arrow/array/array_base.h"
+#include "arrow/c/dlpack_abi.h"
+#include "arrow/device.h"
+#include "arrow/type.h"
+
+namespace arrow {
+
+namespace dlpack {
+
+Status getDLDataType(const std::shared_ptr<DataType>& type, DLDataType* out) {
+ DLDataType dtype;
+ dtype.lanes = 1;
+ dtype.bits = type->bit_width();
+ switch (type->id()) {
+ case Type::INT8:
+ case Type::INT16:
+ case Type::INT32:
+ case Type::INT64:
+ dtype.code = DLDataTypeCode::kDLInt;
+ *out = dtype;
+ return Status::OK();
+ case Type::UINT8:
+ case Type::UINT16:
+ case Type::UINT32:
+ case Type::UINT64:
+ dtype.code = DLDataTypeCode::kDLUInt;
+ *out = dtype;
+ return Status::OK();
+ case Type::HALF_FLOAT:
+ case Type::FLOAT:
+ case Type::DOUBLE:
+ dtype.code = DLDataTypeCode::kDLFloat;
+ *out = dtype;
+ return Status::OK();
+ case Type::BOOL:
+ // DLPack supports byte-packed boolean values
+ return Status::TypeError("Bit-packed boolean data type not supported by
DLPack.");
+ default:
+ return Status::TypeError(
+ "Can only use __dlpack__ on primitive arrays without NullType and
Decimal "
+ "types.");
Review Comment:
DLPack also doesn't support temporals, strings, etc.
```suggestion
return Status::TypeError(
"DataType is not compatible with DLPack spec: ", type.ToString());
```
##########
cpp/src/arrow/c/dlpack.cc:
##########
@@ -0,0 +1,151 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements. See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership. The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License. You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied. See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+#include "arrow/c/dlpack.h"
+
+#include "arrow/array/array_base.h"
+#include "arrow/c/dlpack_abi.h"
+#include "arrow/device.h"
+#include "arrow/type.h"
+
+namespace arrow {
+
+namespace dlpack {
+
+Status getDLDataType(const std::shared_ptr<DataType>& type, DLDataType* out) {
+ DLDataType dtype;
+ dtype.lanes = 1;
+ dtype.bits = type->bit_width();
+ switch (type->id()) {
+ case Type::INT8:
+ case Type::INT16:
+ case Type::INT32:
+ case Type::INT64:
+ dtype.code = DLDataTypeCode::kDLInt;
+ *out = dtype;
+ return Status::OK();
+ case Type::UINT8:
+ case Type::UINT16:
+ case Type::UINT32:
+ case Type::UINT64:
+ dtype.code = DLDataTypeCode::kDLUInt;
+ *out = dtype;
+ return Status::OK();
+ case Type::HALF_FLOAT:
+ case Type::FLOAT:
+ case Type::DOUBLE:
+ dtype.code = DLDataTypeCode::kDLFloat;
+ *out = dtype;
+ return Status::OK();
+ case Type::BOOL:
+ // DLPack supports byte-packed boolean values
+ return Status::TypeError("Bit-packed boolean data type not supported by
DLPack.");
+ default:
+ return Status::TypeError(
+ "Can only use __dlpack__ on primitive arrays without NullType and
Decimal "
+ "types.");
+ }
+}
+
+struct DLMTensorCtx {
+ std::shared_ptr<ArrayData> ref;
+ std::vector<int64_t> shape;
+ DLManagedTensor tensor;
+};
+
+static void deleter(DLManagedTensor* arg) {
+ delete static_cast<DLMTensorCtx*>(arg->manager_ctx);
+}
+
+Status ExportArray(const std::shared_ptr<Array>& arr, DLManagedTensor** out) {
+ if (arr->null_count() > 0) {
+ return Status::TypeError("Can only use __dlpack__ on arrays with no
nulls.");
+ }
+
+ // Define the DLDataType struct
+ // Supported data types: int, uint, float
+ DLDataType arr_type;
+ RETURN_NOT_OK(getDLDataType(arr->type(), &arr_type));
+
+ // Create DLMTensorCtx struct with the reference to
+ // the data of the array
+ std::shared_ptr<ArrayData> array_ref = arr->data();
+ DLMTensorCtx* DLMTensor = new DLMTensorCtx;
+ DLMTensor->ref = array_ref;
+
+ // Define DLManagedTensor struct defined by
+ // DLPack (dlpack_structure.h)
+ DLManagedTensor* dlm_tensor = &DLMTensor->tensor;
+ dlm_tensor->manager_ctx = DLMTensor;
+ dlm_tensor->deleter = &deleter;
+
+ // Define the data pointer to the DLTensor
+ // If array is of length 0, data pointer should be NULL
+ if (arr->length() == 0) {
+ dlm_tensor->dl_tensor.data = NULL;
+ } else if (arr->offset() > 0) {
+ const auto byte_width = arr->type()->byte_width();
+ const auto start = arr->offset() * byte_width;
+ ARROW_ASSIGN_OR_RAISE(auto sliced_buffer,
+ SliceBufferSafe(array_ref->buffers[1], start));
+ dlm_tensor->dl_tensor.data =
+ const_cast<void*>(reinterpret_cast<const
void*>(sliced_buffer->address()));
+ } else {
+ dlm_tensor->dl_tensor.data = const_cast<void*>(
+ reinterpret_cast<const void*>(array_ref->buffers[1]->address()));
+ }
+
+ // Define DLDevice struct
+ DLDevice ctx;
+ if (array_ref->buffers[1]->device_type() == DeviceAllocationType::kCPU) {
+ ctx.device_id = 0;
+ ctx.device_type = DLDeviceType::kDLCPU;
+ } else {
+ return Status::NotImplemented(
+ "DLPack support is implemented only for buffers on CPU device.");
+ }
+ dlm_tensor->dl_tensor.device = ctx;
+
+ dlm_tensor->dl_tensor.ndim = 1;
+ dlm_tensor->dl_tensor.dtype = arr_type;
+ std::vector<int64_t>* shape_arr = &DLMTensor->shape;
+ shape_arr->resize(1);
+ (*shape_arr)[0] = arr->length();
+ dlm_tensor->dl_tensor.shape = shape_arr->data();
Review Comment:
This is not necessary, we could simply point to the existing length and
remove `DLMTensorCtx::shape`:
```suggestion
dlm_tensor->dl_tensor.shape = const_cast<int64_t*>(&array_ref->length);
```
##########
cpp/src/arrow/c/dlpack.cc:
##########
@@ -0,0 +1,151 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements. See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership. The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License. You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied. See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+#include "arrow/c/dlpack.h"
+
+#include "arrow/array/array_base.h"
+#include "arrow/c/dlpack_abi.h"
+#include "arrow/device.h"
+#include "arrow/type.h"
+
+namespace arrow {
+
+namespace dlpack {
+
+Status getDLDataType(const std::shared_ptr<DataType>& type, DLDataType* out) {
+ DLDataType dtype;
+ dtype.lanes = 1;
+ dtype.bits = type->bit_width();
+ switch (type->id()) {
+ case Type::INT8:
+ case Type::INT16:
+ case Type::INT32:
+ case Type::INT64:
+ dtype.code = DLDataTypeCode::kDLInt;
+ *out = dtype;
+ return Status::OK();
+ case Type::UINT8:
+ case Type::UINT16:
+ case Type::UINT32:
+ case Type::UINT64:
+ dtype.code = DLDataTypeCode::kDLUInt;
+ *out = dtype;
+ return Status::OK();
+ case Type::HALF_FLOAT:
+ case Type::FLOAT:
+ case Type::DOUBLE:
+ dtype.code = DLDataTypeCode::kDLFloat;
+ *out = dtype;
+ return Status::OK();
+ case Type::BOOL:
+ // DLPack supports byte-packed boolean values
+ return Status::TypeError("Bit-packed boolean data type not supported by
DLPack.");
+ default:
+ return Status::TypeError(
+ "Can only use __dlpack__ on primitive arrays without NullType and
Decimal "
+ "types.");
+ }
+}
+
+struct DLMTensorCtx {
+ std::shared_ptr<ArrayData> ref;
+ std::vector<int64_t> shape;
+ DLManagedTensor tensor;
+};
+
+static void deleter(DLManagedTensor* arg) {
+ delete static_cast<DLMTensorCtx*>(arg->manager_ctx);
+}
+
+Status ExportArray(const std::shared_ptr<Array>& arr, DLManagedTensor** out) {
+ if (arr->null_count() > 0) {
+ return Status::TypeError("Can only use __dlpack__ on arrays with no
nulls.");
Review Comment:
Let's not use the Python spelling as this could be used directly from
third-party C++ code:
```suggestion
return Status::TypeError("Can only use DLPack on arrays with no nulls.");
```
##########
python/pyarrow/_dlpack.pxi:
##########
@@ -0,0 +1,62 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+from libc.stdlib cimport malloc, free
+
+cimport cpython
+from cpython.pycapsule cimport PyCapsule_New
+from cython import sizeof
+
+
+cdef void pycapsule_deleter(object dltensor) noexcept:
+ cdef DLManagedTensor* dlm_tensor
+ cdef PyObject* err_type
+ cdef PyObject* err_value
+ cdef PyObject* err_traceback
+
+ # Do nothing if the capsule has been consumed
+ if cpython.PyCapsule_IsValid(dltensor, "used_dltensor"):
+ return
+
+ # An exception may be in-flight, we must save it in case
+ # we create another one
+ cpython.PyErr_Fetch(&err_type, &err_value, &err_traceback)
+
+ if cpython.PyCapsule_IsValid(dltensor, 'dltensor'):
+ dlm_tensor = <DLManagedTensor*>cpython.PyCapsule_GetPointer(
+ dltensor, 'dltensor')
+ dlm_tensor.deleter(dlm_tensor)
+ else:
+ cpython.PyErr_WriteUnraisable(dltensor)
Review Comment:
This writes the raised exception but nothing is raised by
`PyCapsule_IsValid`. Instead, you can probably call `PyCapsule_GetPointer`
directly and check the result...
##########
cpp/src/arrow/c/dlpack.cc:
##########
@@ -0,0 +1,151 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements. See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership. The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License. You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied. See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+#include "arrow/c/dlpack.h"
+
+#include "arrow/array/array_base.h"
+#include "arrow/c/dlpack_abi.h"
+#include "arrow/device.h"
+#include "arrow/type.h"
+
+namespace arrow {
+
+namespace dlpack {
+
+Status getDLDataType(const std::shared_ptr<DataType>& type, DLDataType* out) {
+ DLDataType dtype;
+ dtype.lanes = 1;
+ dtype.bits = type->bit_width();
+ switch (type->id()) {
+ case Type::INT8:
+ case Type::INT16:
+ case Type::INT32:
+ case Type::INT64:
+ dtype.code = DLDataTypeCode::kDLInt;
+ *out = dtype;
+ return Status::OK();
+ case Type::UINT8:
+ case Type::UINT16:
+ case Type::UINT32:
+ case Type::UINT64:
+ dtype.code = DLDataTypeCode::kDLUInt;
+ *out = dtype;
+ return Status::OK();
+ case Type::HALF_FLOAT:
+ case Type::FLOAT:
+ case Type::DOUBLE:
+ dtype.code = DLDataTypeCode::kDLFloat;
+ *out = dtype;
+ return Status::OK();
+ case Type::BOOL:
+ // DLPack supports byte-packed boolean values
+ return Status::TypeError("Bit-packed boolean data type not supported by
DLPack.");
+ default:
+ return Status::TypeError(
+ "Can only use __dlpack__ on primitive arrays without NullType and
Decimal "
+ "types.");
+ }
+}
+
+struct DLMTensorCtx {
+ std::shared_ptr<ArrayData> ref;
+ std::vector<int64_t> shape;
+ DLManagedTensor tensor;
+};
+
+static void deleter(DLManagedTensor* arg) {
+ delete static_cast<DLMTensorCtx*>(arg->manager_ctx);
+}
+
+Status ExportArray(const std::shared_ptr<Array>& arr, DLManagedTensor** out) {
+ if (arr->null_count() > 0) {
+ return Status::TypeError("Can only use __dlpack__ on arrays with no
nulls.");
+ }
+
+ // Define the DLDataType struct
+ // Supported data types: int, uint, float
+ DLDataType arr_type;
+ RETURN_NOT_OK(getDLDataType(arr->type(), &arr_type));
+
+ // Create DLMTensorCtx struct with the reference to
+ // the data of the array
+ std::shared_ptr<ArrayData> array_ref = arr->data();
+ DLMTensorCtx* DLMTensor = new DLMTensorCtx;
+ DLMTensor->ref = array_ref;
+
+ // Define DLManagedTensor struct defined by
+ // DLPack (dlpack_structure.h)
+ DLManagedTensor* dlm_tensor = &DLMTensor->tensor;
+ dlm_tensor->manager_ctx = DLMTensor;
+ dlm_tensor->deleter = &deleter;
+
+ // Define the data pointer to the DLTensor
+ // If array is of length 0, data pointer should be NULL
+ if (arr->length() == 0) {
+ dlm_tensor->dl_tensor.data = NULL;
+ } else if (arr->offset() > 0) {
+ const auto byte_width = arr->type()->byte_width();
+ const auto start = arr->offset() * byte_width;
+ ARROW_ASSIGN_OR_RAISE(auto sliced_buffer,
+ SliceBufferSafe(array_ref->buffers[1], start));
+ dlm_tensor->dl_tensor.data =
+ const_cast<void*>(reinterpret_cast<const
void*>(sliced_buffer->address()));
+ } else {
+ dlm_tensor->dl_tensor.data = const_cast<void*>(
+ reinterpret_cast<const void*>(array_ref->buffers[1]->address()));
+ }
+
+ // Define DLDevice struct
+ DLDevice ctx;
+ if (array_ref->buffers[1]->device_type() == DeviceAllocationType::kCPU) {
+ ctx.device_id = 0;
+ ctx.device_type = DLDeviceType::kDLCPU;
+ } else {
+ return Status::NotImplemented(
+ "DLPack support is implemented only for buffers on CPU device.");
+ }
Review Comment:
We should not duplicate this code since this is already implemented in
`ExportDevice` below...
##########
cpp/src/arrow/c/dlpack.cc:
##########
@@ -0,0 +1,151 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements. See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership. The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License. You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied. See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+#include "arrow/c/dlpack.h"
+
+#include "arrow/array/array_base.h"
+#include "arrow/c/dlpack_abi.h"
+#include "arrow/device.h"
+#include "arrow/type.h"
+
+namespace arrow {
+
+namespace dlpack {
+
+Status getDLDataType(const std::shared_ptr<DataType>& type, DLDataType* out) {
+ DLDataType dtype;
+ dtype.lanes = 1;
+ dtype.bits = type->bit_width();
+ switch (type->id()) {
+ case Type::INT8:
+ case Type::INT16:
+ case Type::INT32:
+ case Type::INT64:
+ dtype.code = DLDataTypeCode::kDLInt;
+ *out = dtype;
+ return Status::OK();
+ case Type::UINT8:
+ case Type::UINT16:
+ case Type::UINT32:
+ case Type::UINT64:
+ dtype.code = DLDataTypeCode::kDLUInt;
+ *out = dtype;
+ return Status::OK();
+ case Type::HALF_FLOAT:
+ case Type::FLOAT:
+ case Type::DOUBLE:
+ dtype.code = DLDataTypeCode::kDLFloat;
+ *out = dtype;
+ return Status::OK();
+ case Type::BOOL:
+ // DLPack supports byte-packed boolean values
+ return Status::TypeError("Bit-packed boolean data type not supported by
DLPack.");
+ default:
+ return Status::TypeError(
+ "Can only use __dlpack__ on primitive arrays without NullType and
Decimal "
+ "types.");
+ }
+}
+
+struct DLMTensorCtx {
+ std::shared_ptr<ArrayData> ref;
+ std::vector<int64_t> shape;
+ DLManagedTensor tensor;
+};
+
+static void deleter(DLManagedTensor* arg) {
+ delete static_cast<DLMTensorCtx*>(arg->manager_ctx);
+}
+
+Status ExportArray(const std::shared_ptr<Array>& arr, DLManagedTensor** out) {
+ if (arr->null_count() > 0) {
+ return Status::TypeError("Can only use __dlpack__ on arrays with no
nulls.");
+ }
+
+ // Define the DLDataType struct
+ // Supported data types: int, uint, float
+ DLDataType arr_type;
+ RETURN_NOT_OK(getDLDataType(arr->type(), &arr_type));
+
+ // Create DLMTensorCtx struct with the reference to
+ // the data of the array
+ std::shared_ptr<ArrayData> array_ref = arr->data();
+ DLMTensorCtx* DLMTensor = new DLMTensorCtx;
+ DLMTensor->ref = array_ref;
+
+ // Define DLManagedTensor struct defined by
+ // DLPack (dlpack_structure.h)
+ DLManagedTensor* dlm_tensor = &DLMTensor->tensor;
+ dlm_tensor->manager_ctx = DLMTensor;
+ dlm_tensor->deleter = &deleter;
+
+ // Define the data pointer to the DLTensor
+ // If array is of length 0, data pointer should be NULL
Review Comment:
Is this specified somewhere?
##########
python/pyarrow/tests/test_array.py:
##########
@@ -3546,3 +3548,123 @@ def test_run_end_encoded_from_buffers():
with pytest.raises(ValueError):
pa.RunEndEncodedArray.from_buffers(ree_type, length, buffers,
1, offset, children)
+
+
+def PyCapsule_IsValid(capsule, name):
+ return ctypes.pythonapi.PyCapsule_IsValid(ctypes.py_object(capsule), name)
== 1
+
+
[email protected](
+ ('value_type', 'np_type'),
+ [
+ (pa.uint8(), np.uint8),
+ (pa.uint16(), np.uint16),
+ (pa.uint32(), np.uint32),
+ (pa.uint64(), np.uint64),
+ (pa.int8(), np.int8),
+ (pa.int16(), np.int16),
+ (pa.int32(), np.int32),
+ (pa.int64(), np.int64),
+ (pa.float16(), np.float16),
+ (pa.float32(), np.float32),
+ (pa.float64(), np.float64),
+ ]
+)
+def test_dlpack(value_type, np_type):
+ if Version(np.__version__) < Version("1.24.0"):
+ pytest.skip("No dlpack support in numpy versions older than 1.22.0, "
+ "strict keyward in assert_array_equal added in numpy
version "
+ "1.24.0")
+
+ expected = np.array([1, 2, 3], dtype=np_type)
+ arr = pa.array(expected, type=value_type)
+ DLTensor = arr.__dlpack__()
+ assert PyCapsule_IsValid(DLTensor, b"dltensor") is True
+ result = np.from_dlpack(arr)
+ np.testing.assert_array_equal(result, expected, strict=True)
+
+ assert arr.__dlpack_device__() == (1, 0)
+
+ arr_sliced = arr.slice(1, 1)
+ DLTensor = arr_sliced.__dlpack__()
+ assert PyCapsule_IsValid(DLTensor, b"dltensor") is True
+ expected = np.array([2], dtype=np_type)
+ result = np.from_dlpack(arr_sliced)
+ np.testing.assert_array_equal(result, expected, strict=True)
Review Comment:
Can we avoid such copy-pasting in tests? There could be some test helper(s)
such that you would write, e.g.:
```suggestion
check_dlpack_export(arr_sliced, expected=np.array([2], dtype=np_type))
```
##########
python/pyarrow/tests/test_array.py:
##########
@@ -3546,3 +3548,123 @@ def test_run_end_encoded_from_buffers():
with pytest.raises(ValueError):
pa.RunEndEncodedArray.from_buffers(ree_type, length, buffers,
1, offset, children)
+
Review Comment:
Hmm, can we move all these tests into a separate `test_dlpack.py`?
##########
cpp/src/arrow/c/dlpack.cc:
##########
@@ -0,0 +1,151 @@
+// Licensed to the Apache Software Foundation (ASF) under one
+// or more contributor license agreements. See the NOTICE file
+// distributed with this work for additional information
+// regarding copyright ownership. The ASF licenses this file
+// to you under the Apache License, Version 2.0 (the
+// "License"); you may not use this file except in compliance
+// with the License. You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing,
+// software distributed under the License is distributed on an
+// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+// KIND, either express or implied. See the License for the
+// specific language governing permissions and limitations
+// under the License.
+
+#include "arrow/c/dlpack.h"
+
+#include "arrow/array/array_base.h"
+#include "arrow/c/dlpack_abi.h"
+#include "arrow/device.h"
+#include "arrow/type.h"
+
+namespace arrow {
+
+namespace dlpack {
+
+Status getDLDataType(const std::shared_ptr<DataType>& type, DLDataType* out) {
+ DLDataType dtype;
+ dtype.lanes = 1;
+ dtype.bits = type->bit_width();
+ switch (type->id()) {
+ case Type::INT8:
+ case Type::INT16:
+ case Type::INT32:
+ case Type::INT64:
+ dtype.code = DLDataTypeCode::kDLInt;
+ *out = dtype;
+ return Status::OK();
+ case Type::UINT8:
+ case Type::UINT16:
+ case Type::UINT32:
+ case Type::UINT64:
+ dtype.code = DLDataTypeCode::kDLUInt;
+ *out = dtype;
+ return Status::OK();
+ case Type::HALF_FLOAT:
+ case Type::FLOAT:
+ case Type::DOUBLE:
+ dtype.code = DLDataTypeCode::kDLFloat;
+ *out = dtype;
+ return Status::OK();
+ case Type::BOOL:
+ // DLPack supports byte-packed boolean values
+ return Status::TypeError("Bit-packed boolean data type not supported by
DLPack.");
+ default:
+ return Status::TypeError(
+ "Can only use __dlpack__ on primitive arrays without NullType and
Decimal "
+ "types.");
+ }
+}
+
+struct DLMTensorCtx {
+ std::shared_ptr<ArrayData> ref;
+ std::vector<int64_t> shape;
+ DLManagedTensor tensor;
+};
+
+static void deleter(DLManagedTensor* arg) {
+ delete static_cast<DLMTensorCtx*>(arg->manager_ctx);
+}
+
+Status ExportArray(const std::shared_ptr<Array>& arr, DLManagedTensor** out) {
+ if (arr->null_count() > 0) {
+ return Status::TypeError("Can only use __dlpack__ on arrays with no
nulls.");
+ }
+
+ // Define the DLDataType struct
+ // Supported data types: int, uint, float
+ DLDataType arr_type;
+ RETURN_NOT_OK(getDLDataType(arr->type(), &arr_type));
+
+ // Create DLMTensorCtx struct with the reference to
+ // the data of the array
+ std::shared_ptr<ArrayData> array_ref = arr->data();
+ DLMTensorCtx* DLMTensor = new DLMTensorCtx;
Review Comment:
Indeed, something like this:
```c++
struct ManagerCtx {
std::shared_ptr<ArrayData> ref;
DLManagedTensor tensor;
};
std::unique_ptr<ManagerCtx> ctx(new ManagerCtx);
ctx->ref = array_ref;
// fill struct fields
...
// end of function
ctx->tensor->manager_ctx = ctx.release();
ctx->tensor->deleter = [](struct DLManagedTensor *self) {
delete reinterpret_cast<ManagerCtx*>(self->manager_ctx);
};
return &ctx->tensor;
```
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