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Merge branch 'master' into harlowjo/debug/wheels-tests
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‎.github/workflows/array-api-skips.txt

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@@ -17,18 +17,6 @@ array_api_tests/test_signatures.py::test_func_signature[unique_counts]
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array_api_tests/test_signatures.py::test_func_signature[unique_inverse]
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array_api_tests/test_signatures.py::test_func_signature[unique_values]
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# no '__array_namespace_info__' function
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array_api_tests/test_has_names.py::test_has_names[info-__array_namespace_info__]
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array_api_tests/test_inspection_functions.py::test_array_namespace_info
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array_api_tests/test_inspection_functions.py::test_array_namespace_info_dtypes
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array_api_tests/test_searching_functions.py::test_searchsorted
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array_api_tests/test_signatures.py::test_func_signature[__array_namespace_info__]
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array_api_tests/test_signatures.py::test_info_func_signature[capabilities]
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array_api_tests/test_signatures.py::test_info_func_signature[default_device]
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array_api_tests/test_signatures.py::test_info_func_signature[default_dtypes]
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array_api_tests/test_signatures.py::test_info_func_signature[devices]
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array_api_tests/test_signatures.py::test_info_func_signature[dtypes]
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# do not return a namedtuple
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array_api_tests/test_linalg.py::test_eigh
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array_api_tests/test_linalg.py::test_slogdet

‎doc/reference/array_api.rst

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.. _array-api-standard-compatibility:
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.. https://numpy.org/doc/stable/reference/array_api.html
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********************************
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Array API standard compatibility
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********************************
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DPNP's main namespace as well as the :mod:`dpnp.fft` and :mod:`dpnp.linalg`
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namespaces are compatible with the
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`2023.12 version <https://data-apis.org/array-api/2023.12/index.html>`__
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of the Python array API standard.
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Inspection
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==========
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DPNP implements the `array API inspection utilities
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<https://data-apis.org/array-api/latest/API_specification/inspection.html>`__.
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These functions can be accessed via the ``__array_namespace_info__()``
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function, which returns a namespace containing the inspection utilities.
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.. autosummary::
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:toctree: generated/
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:nosignatures:
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dpnp.__array_namespace_info__

‎doc/reference/fft.rst

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.. _routines.fft:
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.. py:module:: dpnp.fft
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15
Discrete Fourier Transform
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==========================
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‎doc/reference/index.rst

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@@ -33,3 +33,4 @@ API reference of the Data Parallel Extension for NumPy*
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dtypes_table
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comparison
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misc
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array_api

‎doc/reference/linalg.rst

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.. _routines.linalg:
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.. py:module:: dpnp.linalg
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15
Linear algebra
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==============
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‎dpnp/__init__.py

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)
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# Borrowed from DPCTL
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from dpctl.tensor import DLDeviceType
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from dpctl.tensor import __array_api_version__, DLDeviceType
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from dpnp.dpnp_array import dpnp_array as ndarray
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from dpnp.dpnp_flatiter import flatiter as flatiter
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from dpnp.dpnp_iface_types import *
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from dpnp.dpnp_iface import *
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from dpnp.dpnp_iface import __all__ as _iface__all__
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from dpnp.dpnp_iface_utils import *
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from dpnp.dpnp_iface_utils import __all__ as _ifaceutils__all__
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from dpnp._version import get_versions
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from .dpnp_array import dpnp_array as ndarray
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from .dpnp_array_api_info import __array_namespace_info__
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from .dpnp_flatiter import flatiter as flatiter
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from .dpnp_iface_types import *
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from .dpnp_iface import *
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from .dpnp_iface import __all__ as _iface__all__
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from .dpnp_iface_utils import *
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from .dpnp_iface_utils import __all__ as _ifaceutils__all__
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from ._version import get_versions
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__all__ = _iface__all__
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__all__ += _ifaceutils__all__

‎dpnp/dpnp_array_api_info.py

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# -*- coding: utf-8 -*-
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# *****************************************************************************
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# Copyright (c) 2025, Intel Corporation
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# All rights reserved.
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#
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# Redistribution and use in source and binary forms, with or without
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# modification, are permitted provided that the following conditions are met:
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# - Redistributions of source code must retain the above copyright notice,
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# this list of conditions and the following disclaimer.
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# - Redistributions in binary form must reproduce the above copyright notice,
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# this list of conditions and the following disclaimer in the documentation
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# and/or other materials provided with the distribution.
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#
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
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# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
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# THE POSSIBILITY OF SUCH DAMAGE.
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# *****************************************************************************
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"""
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Array API Inspection namespace
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This is the namespace for inspection functions as defined by the array API
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standard. See
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https://data-apis.org/array-api/latest/API_specification/inspection.html for
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more details.
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"""
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import dpctl.tensor as dpt
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__all__ = ["__array_namespace_info__"]
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def __array_namespace_info__():
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"""
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Returns a namespace with Array API namespace inspection utilities.
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The array API inspection namespace defines the following functions:
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- capabilities()
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- default_device()
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- default_dtypes()
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- dtypes()
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- devices()
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Returns
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-------
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info : ModuleType
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The array API inspection namespace for DPNP.
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Examples
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--------
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>>> import dpnp as np
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>>> info = np.__array_namespace_info__()
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>>> info.default_dtypes() # may vary and depends on default device
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{'real floating': dtype('float64'),
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'complex floating': dtype('complex128'),
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'integral': dtype('int64'),
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'indexing': dtype('int64')}
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"""
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return dpt.__array_namespace_info__()

‎dpnp/tests/test_array_api_info.py

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import numpy
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import pytest
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from dpctl import SyclDeviceCreationError, get_devices, select_default_device
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from dpctl.tensor._tensor_impl import default_device_complex_type
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import dpnp
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from dpnp.tests.helper import (
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has_support_aspect64,
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is_win_platform,
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numpy_version,
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)
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info = dpnp.__array_namespace_info__()
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default_device = select_default_device()
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def test_capabilities():
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caps = info.capabilities()
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assert caps["boolean indexing"] is True
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assert caps["data-dependent shapes"] is True
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assert caps["max dimensions"] == 64
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def test_default_device():
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assert info.default_device() == default_device
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def test_default_dtypes():
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dtypes = info.default_dtypes()
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assert (
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dtypes["real floating"]
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== dpnp.default_float_type()
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== dpnp.asarray(0.0).dtype
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)
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# TODO: add dpnp.default_complex_type() function
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assert (
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dtypes["complex floating"]
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== default_device_complex_type(default_device)
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== dpnp.asarray(0.0j).dtype
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)
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if not is_win_platform() or numpy_version() >= "2.0.0":
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# numpy changed default integer on Windows since 2.0
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assert dtypes["integral"] == dpnp.intp == dpnp.asarray(0).dtype
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assert (
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dtypes["indexing"] == dpnp.intp == dpnp.argmax(dpnp.zeros(10)).dtype
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)
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with pytest.raises(
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TypeError, match="Unsupported type for device argument:"
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):
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info.default_dtypes(device=1)
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def test_dtypes_all():
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dtypes = info.dtypes()
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assert dtypes == (
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{
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"bool": dpnp.bool_,
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"int8": numpy.int8, # TODO: replace with dpnp.int8
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"int16": numpy.int16, # TODO: replace with dpnp.int16
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"int32": dpnp.int32,
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"int64": dpnp.int64,
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"uint8": numpy.uint8, # TODO: replace with dpnp.uint8
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"uint16": numpy.uint16, # TODO: replace with dpnp.uint16
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"uint32": numpy.uint32, # TODO: replace with dpnp.uint32
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"uint64": numpy.uint64, # TODO: replace with dpnp.uint64
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"float32": dpnp.float32,
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}
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| ({"float64": dpnp.float64} if has_support_aspect64() else {})
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| {"complex64": dpnp.complex64}
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| ({"complex128": dpnp.complex128} if has_support_aspect64() else {})
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)
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dtype_categories = {
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"bool": {"bool": dpnp.bool_},
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"signed integer": {
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"int8": numpy.int8, # TODO: replace with dpnp.int8
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"int16": numpy.int16, # TODO: replace with dpnp.int16
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"int32": dpnp.int32,
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"int64": dpnp.int64,
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},
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"unsigned integer": { # TODO: replace with dpnp dtypes once available
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"uint8": numpy.uint8,
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"uint16": numpy.uint16,
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"uint32": numpy.uint32,
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"uint64": numpy.uint64,
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},
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"integral": ("signed integer", "unsigned integer"),
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"real floating": {"float32": dpnp.float32}
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| ({"float64": dpnp.float64} if has_support_aspect64() else {}),
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"complex floating": {"complex64": dpnp.complex64}
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| ({"complex128": dpnp.complex128} if has_support_aspect64() else {}),
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"numeric": ("integral", "real floating", "complex floating"),
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}
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@pytest.mark.parametrize("kind", dtype_categories)
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def test_dtypes_kind(kind):
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expected = dtype_categories[kind]
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if isinstance(expected, tuple):
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assert info.dtypes(kind=kind) == info.dtypes(kind=expected)
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else:
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assert info.dtypes(kind=kind) == expected
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def test_dtypes_tuple():
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dtypes = info.dtypes(kind=("bool", "integral"))
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assert dtypes == {
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"bool": dpnp.bool_,
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"int8": numpy.int8, # TODO: replace with dpnp.int8
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"int16": numpy.int16, # TODO: replace with dpnp.int16
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"int32": dpnp.int32,
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"int64": dpnp.int64,
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"uint8": numpy.uint8, # TODO: replace with dpnp.uint8
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"uint16": numpy.uint16, # TODO: replace with dpnp.uint16
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"uint32": numpy.uint32, # TODO: replace with dpnp.uint32
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"uint64": numpy.uint64, # TODO: replace with dpnp.uint64
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}
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def test_dtypes_invalid_kind():
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with pytest.raises(ValueError, match="Unrecognized data type kind"):
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info.dtypes(kind="invalid")
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def test_dtypes_invalid_device():
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with pytest.raises(SyclDeviceCreationError, match="Could not create"):
129+
info.dtypes(device="str")
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def test_devices():
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assert info.devices() == get_devices()

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