Add implementation of dpnp.ndarray.data and dpnp.ndarray.data.ptr attributes

CHANGELOG.md

@@ -11,6 +11,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 * Added `--target-cuda[=ARCH]` option to replace the deprecated `--target=cuda`, allowing users to build for CUDA devices with optional architecture selection using [CodePlay oneAPI plug-in](https://developer.codeplay.com/products/oneapi/nvidia/home/) [#2478](https://github.com/IntelPython/dpnp/pull/2478)
 * Added several new `pre-commit` rules, including protection against direct commits to master/maintenance branches [#2500](https://github.com/IntelPython/dpnp/pull/2500)
 * Added implementation of `dpnp.ndarray.view` method [#2520](https://github.com/IntelPython/dpnp/pull/2520)
+* Added implementation of `dpnp.ndarray.data` and `dpnp.ndarray.data.ptr` attributes [#2521](https://github.com/IntelPython/dpnp/pull/2521)
 
 ### Changed
 

dpnp/dpnp_array.py

@@ -29,6 +29,7 @@
 from dpctl.tensor._numpy_helper import AxisError
 
 import dpnp
+import dpnp.memory as dpm
 
 
 def _get_unwrapped_index_key(key):
@@ -76,9 +77,12 @@ def __init__(
             order = "C"
 
         if buffer is not None:
-            buffer = dpnp.get_usm_ndarray(buffer)
+            # expecting to have buffer as dpnp.ndarray and usm_ndarray,
+            # or as USM memory allocation
+            if isinstance(buffer, dpnp_array):
+                buffer = buffer.get_array()
 
-            if dtype is None:
+            if dtype is None and hasattr(buffer, "dtype"):
                 dtype = buffer.dtype
         else:
             buffer = usm_type
@@ -1015,7 +1019,15 @@ def cumsum(self, axis=None, dtype=None, out=None):
 
         return dpnp.cumsum(self, axis=axis, dtype=dtype, out=out)
 
-    # 'data',
+    @property
+    def data(self):
+        """
+        Python object pointing to the start of USM memory allocation with the
+        array's data.
+
+        """
+
+        return dpm.create_data(self._array_obj)
 
     def diagonal(self, offset=0, axis1=0, axis2=1):
         """

dpnp/dpnp_iface.py

@@ -53,6 +53,7 @@
 from dpnp.dpnp_array import dpnp_array
 from dpnp.fft import *
 from dpnp.linalg import *
+from dpnp.memory import *
 from dpnp.random import *
 
 __all__ = [

dpnp/memory/__init__.py

@@ -0,0 +1,39 @@
+# -*- coding: utf-8 -*-
+# *****************************************************************************
+# Copyright (c) 2025, Intel Corporation
+# All rights reserved.
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+# - Redistributions of source code must retain the above copyright notice,
+#   this list of conditions and the following disclaimer.
+# - Redistributions in binary form must reproduce the above copyright notice,
+#   this list of conditions and the following disclaimer in the documentation
+#   and/or other materials provided with the distribution.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
+# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
+# THE POSSIBILITY OF SUCH DAMAGE.
+# *****************************************************************************
+
+from ._memory import (
+    MemoryUSMDevice,
+    MemoryUSMHost,
+    MemoryUSMShared,
+    create_data,
+)
+
+__all__ = [
+    "MemoryUSMDevice",
+    "MemoryUSMHost",
+    "MemoryUSMShared",
+    "create_data",
+]

dpnp/memory/_memory.py

@@ -0,0 +1,105 @@
+# -*- coding: utf-8 -*-
+# *****************************************************************************
+# Copyright (c) 2025, Intel Corporation
+# All rights reserved.
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+# - Redistributions of source code must retain the above copyright notice,
+#   this list of conditions and the following disclaimer.
+# - Redistributions in binary form must reproduce the above copyright notice,
+#   this list of conditions and the following disclaimer in the documentation
+#   and/or other materials provided with the distribution.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
+# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
+# THE POSSIBILITY OF SUCH DAMAGE.
+# *****************************************************************************
+
+import dpctl.tensor as dpt
+from dpctl.memory import MemoryUSMDevice as DPCTLMemoryUSMDevice
+from dpctl.memory import MemoryUSMHost as DPCTLMemoryUSMHost
+from dpctl.memory import MemoryUSMShared as DPCTLMemoryUSMShared
+
+
+def _add_ptr_property(cls):
+    _storage_attr = "_ptr"
+
+    @property
+    def ptr(self):
+        """
+        Returns USM pointer to the start of array (element with zero
+        multi-index) encoded as integer.
+
+        """
+
+        return getattr(self, _storage_attr, None)
+
+    @ptr.setter
+    def ptr(self, value):
+        setattr(self, _storage_attr, value)
+
+    cls.ptr = ptr
+    return cls
+
+
+@_add_ptr_property
+class MemoryUSMDevice(DPCTLMemoryUSMDevice):
+    pass
+
+
+@_add_ptr_property
+class MemoryUSMHost(DPCTLMemoryUSMHost):
+    pass
+
+
+@_add_ptr_property
+class MemoryUSMShared(DPCTLMemoryUSMShared):
+    pass
+
+
+def create_data(x):
+    """
+    Create an instance of :class:`.MemoryUSMDevice`, :class:`.MemoryUSMHost`,
+    or :class:`.MemoryUSMShared` class depending on the type of USM allocation.
+
+    Parameters
+    ----------
+    x : usm_ndarray
+        Input array of :class:`dpctl.tensor.usm_ndarray` type.
+
+    Returns
+    -------
+    out : {MemoryUSMDevice, MemoryUSMHost, MemoryUSMShared}
+        A data object with a reference on USM memory.
+
+    """
+
+    dispatch = {
+        DPCTLMemoryUSMDevice: MemoryUSMDevice,
+        DPCTLMemoryUSMHost: MemoryUSMHost,
+        DPCTLMemoryUSMShared: MemoryUSMShared,
+    }
+
+    if not isinstance(x, dpt.usm_ndarray):
+        raise TypeError(
+            f"An array must be any of supported type, but got {type(x)}"
+        )
+    usm_data = x.usm_data
+
+    cls = dispatch.get(type(usm_data), None)
+    if cls:
+        data = cls(usm_data)
+        # `ptr`` is expecting to point at the start of the array's data,
+        # while `usm_data._pointer` is a pointer at the start of memory buffer
+        data.ptr = x._pointer
+        return data
+    raise TypeError(f"Expected USM memory, but got {type(usm_data)}")

dpnp/tests/test_dlpack.py

@@ -78,7 +78,7 @@ def test_device(self):
         x = dpnp.arange(5)
         y = dpnp.from_dlpack(x, device=x.__dlpack_device__())
         assert x.device == y.device
-        assert x.get_array()._pointer == y.get_array()._pointer
+        assert x.data.ptr == y.data.ptr
 
     def test_numpy_input(self):
         x = numpy.arange(10)

dpnp/tests/third_party/cupy/core_tests/test_dlpack.py

@@ -41,14 +41,15 @@ def __dlpack_device__(self):
 @pytest.mark.skip("toDlpack() and fromDlpack() are not supported")
 class TestDLPackConversion:
 
-    @pytest.mark.filterwarnings("ignore::DeprecationWarning")
     @testing.for_all_dtypes(no_bool=False)
-    def test_conversion(self, dtype):
+    def test_conversion(self, dtype, recwarn):
         orig_array = _gen_array(dtype)
         tensor = orig_array.toDlpack()
         out_array = cupy.fromDlpack(tensor)
         testing.assert_array_equal(orig_array, out_array)
-        assert orig_array.get_array()._pointer == out_array.get_array()._pointer
+        testing.assert_array_equal(orig_array.data.ptr, out_array.data.ptr)
+        for w in recwarn:
+            assert issubclass(w.category, cupy.VisibleDeprecationWarning)
 
 
 class TestNewDLPackConversion:
@@ -82,7 +83,7 @@ def test_conversion(self, dtype):
         orig_array = _gen_array(dtype)
         out_array = cupy.from_dlpack(orig_array)
         testing.assert_array_equal(orig_array, out_array)
-        assert orig_array.get_array()._pointer == out_array.get_array()._pointer
+        testing.assert_array_equal(orig_array.data.ptr, out_array.data.ptr)
 
     @pytest.mark.skip("no limitations in from_dlpack()")
     def test_from_dlpack_and_conv_errors(self):
@@ -121,7 +122,7 @@ def test_conversion_max_version(self, kwargs, versioned):
         )
 
         testing.assert_array_equal(orig_array, out_array)
-        assert orig_array.get_array()._pointer == out_array.get_array()._pointer
+        testing.assert_array_equal(orig_array.data.ptr, out_array.data.ptr)
 
     def test_conversion_device(self):
         orig_array = _gen_array("float32")
@@ -135,7 +136,7 @@ def test_conversion_device(self):
         )
 
         testing.assert_array_equal(orig_array, out_array)
-        assert orig_array.get_array()._pointer == out_array.get_array()._pointer
+        testing.assert_array_equal(orig_array.data.ptr, out_array.data.ptr)
 
     def test_conversion_bad_device(self):
         arr = _gen_array("float32")
@@ -212,9 +213,8 @@ def test_stream(self):
                 out_array = dlp.from_dlpack_capsule(dltensor)
                 out_array = cupy.from_dlpack(out_array, device=dst_s)
                 testing.assert_array_equal(orig_array, out_array)
-                assert (
-                    orig_array.get_array()._pointer
-                    == out_array.get_array()._pointer
+                testing.assert_array_equal(
+                    orig_array.data.ptr, out_array.data.ptr
                 )
 
 
@@ -267,12 +267,13 @@ def test_deleter2(self, pool, max_version):
         # assert pool.n_free_blocks() == 1
 
     @pytest.mark.skip("toDlpack() and fromDlpack() are not supported")
-    @pytest.mark.filterwarnings("ignore::DeprecationWarning")
-    def test_multiple_consumption_error(self):
+    def test_multiple_consumption_error(self, recwarn):
         # Prevent segfault, see #3611
         array = cupy.empty(10)
         tensor = array.toDlpack()
         array2 = cupy.fromDlpack(tensor)
         with pytest.raises(ValueError) as e:
             array3 = cupy.fromDlpack(tensor)
         assert "consumed multiple times" in str(e.value)
+        for w in recwarn:
+            assert issubclass(w.category, cupy.VisibleDeprecationWarning)

dpnp/tests/third_party/cupy/core_tests/test_ndarray.py

@@ -43,13 +43,13 @@ def test_shape_not_integer(self):
 
     def test_shape_int_with_strides(self):
         dummy = cupy.ndarray(3)
-        a = cupy.ndarray(3, strides=(0,), buffer=dummy)
+        a = cupy.ndarray(3, strides=(0,), buffer=dummy.data)
         assert a.shape == (3,)
         assert a.strides == (0,)
 
     def test_memptr(self):
         a = cupy.arange(6).astype(numpy.float32).reshape((2, 3))
-        memptr = a
+        memptr = a.data
 
         b = cupy.ndarray((2, 3), numpy.float32, memptr)
         testing.assert_array_equal(a, b)
@@ -62,7 +62,7 @@ def test_memptr(self):
     )
     def test_memptr_with_strides(self):
         buf = cupy.ndarray(20, numpy.uint8)
-        memptr = buf
+        memptr = buf.data
 
         # self-overlapping strides
         a = cupy.ndarray((2, 3), numpy.float32, memptr, strides=(2, 1))
@@ -82,7 +82,9 @@ def test_strides_without_memptr(self):
 
     def test_strides_is_given_and_order_is_ignored(self):
         buf = cupy.ndarray(20, numpy.uint8)
-        a = cupy.ndarray((2, 3), numpy.float32, buf, strides=(2, 1), order="C")
+        a = cupy.ndarray(
+            (2, 3), numpy.float32, buf.data, strides=(2, 1), order="C"
+        )
         assert a.strides == (2, 1)
 
     @testing.with_requires("numpy>=1.19")