Merge branch 'master' into fix-vecmat-win-failure

Author: vtavana

CHANGELOG.md

@@ -13,6 +13,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 * Added implementation of `dpnp.ndarray.view` method [#2520](https://github.com/IntelPython/dpnp/pull/2520)
 * Added a new backend routine `syrk` from oneMKL to perform symmetric rank-k update which is used for a specialized matrix multiplication where the result is a symmetric matrix [2509](https://github.com/IntelPython/dpnp/pull/2509)
 * Added `timeout-minutes` property to GitHub jobs [#2526](https://github.com/IntelPython/dpnp/pull/2526)
+* Added implementation of `dpnp.ndarray.data` and `dpnp.ndarray.data.ptr` attributes [#2521](https://github.com/IntelPython/dpnp/pull/2521)
 
 ### Changed
 
@@ -26,6 +27,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 * Bumped oneMKL version up to `v0.8` [#2514](https://github.com/IntelPython/dpnp/pull/2514)
 * Removed the use of class template argument deduction for alias template to conform to the C++17 standard [#2517](https://github.com/IntelPython/dpnp/pull/2517)
 * Changed th order of individual FFTs over `axes` for `dpnp.fft.irfftn` to be in forward order [#2524](https://github.com/IntelPython/dpnp/pull/2524)
+* Replaced the use of `numpy.testing.suppress_warnings` with appropriate calls from the warnings module [#2529](https://github.com/IntelPython/dpnp/pull/2529)
 
 ### Deprecated
 

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/conftest.py

@@ -183,9 +183,8 @@ def allow_fall_back_on_numpy(monkeypatch):
 
 @pytest.fixture
 def suppress_complex_warning():
-    sup = numpy.testing.suppress_warnings("always")
-    sup.filter(ComplexWarning)
-    with sup:
+    with warnings.catch_warnings():
+        warnings.simplefilter("ignore", ComplexWarning)
         yield
 
 

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/test_linalg.py

@@ -1,3 +1,5 @@
+import warnings
+
 import dpctl
 import dpctl.tensor as dpt
 import numpy
@@ -10,7 +12,6 @@
     assert_equal,
     assert_raises,
     assert_raises_regex,
-    suppress_warnings,
 )
 
 import dpnp
@@ -847,8 +848,8 @@ def check_einsum_sums(self, dtype, do_opt=False):
             )
 
         # Suppress the complex warnings for the 'as f8' tests
-        with suppress_warnings() as sup:
-            sup.filter(numpy.exceptions.ComplexWarning)
+        with warnings.catch_warnings():
+            warnings.simplefilter("ignore", numpy.exceptions.ComplexWarning)
 
             # matvec(a,b) / a.dot(b) where a is matrix, b is vector
             for n in range(1, 17):

dpnp/tests/test_memory.py

@@ -0,0 +1,28 @@
+import dpctl.tensor as dpt
+import numpy
+import pytest
+
+import dpnp
+import dpnp.memory as dpm
+
+
+class IntUsmData(dpt.usm_ndarray):
+    """Class that overrides `usm_data` property in `dpt.usm_ndarray`."""
+
+    @property
+    def usm_data(self):
+        return 1
+
+
+class TestCreateData:
+    @pytest.mark.parametrize("x", [numpy.ones(4), dpnp.zeros(2)])
+    def test_wrong_input_type(self, x):
+        with pytest.raises(TypeError):
+            dpm.create_data(x)
+
+    def test_wrong_usm_data(self):
+        a = dpt.ones(10)
+        d = IntUsmData(a.shape, buffer=a)
+
+        with pytest.raises(TypeError):
+            dpm.create_data(d)

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)