Backport gh-2185

.github/CODEOWNERS

@@ -1 +1 @@
-* @antonwolfy @npolina4 @vlad-perevezentsev @vtavana
+* @antonwolfy @AlexanderKalistratov @vlad-perevezentsev @vtavana

CHANGELOG.md

@@ -1,9 +1,23 @@
 # Changelog
 All notable changes to this project will be documented in this file.
 
-The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
+The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [0.16.1] - 12/XX/2024
+
+This is a bug-fix release.
+
+### Changed
+
+* Updated `README.md` to reflect current installation requirements and available options [#2166](https://github.com/IntelPython/dpnp/pull/2166)
+* Corrected a list of owners and code maintainers [#2185](https://github.com/IntelPython/dpnp/pull/2185)
+
+### Fixed
+
+* Resolved an issue with Compute Follows Data inconsistency in `dpnp.extract` function [#2172](https://github.com/IntelPython/dpnp/pull/2172)
+
+
 ## [0.16.0] - 10/14/2024
 
 This release reaches an important milestone by making offloading fully asynchronous. Calls to `dpnp` submit tasks for execution to DPC++ runtime and return without waiting for execution of these tasks to finish. The sequential semantics a user comes to expect from execution of Python script is preserved though.

README.md

@@ -6,117 +6,76 @@
 [![Build Sphinx](https://github.com/IntelPython/dpnp/workflows/Build%20Sphinx/badge.svg)](https://intelpython.github.io/dpnp)
 [![OpenSSF Scorecard](https://api.securityscorecards.dev/projects/github.com/IntelPython/dpnp/badge)](https://securityscorecards.dev/viewer/?uri=github.com/IntelPython/dpnp)
 
+<img align="left" src="https://spec.oneapi.io/oneapi-logo-white-scaled.jpg" alt="oneAPI logo" width="75"/>
+
 # DPNP - Data Parallel Extension for NumPy*
+
+Data Parallel Extension for NumPy* or `dpnp` is a Python library that
+implements a subset of NumPy* that can be executed on any data parallel device.
+The subset is a drop-in replacement of core NumPy* functions and numerical data types.
+
 [API coverage summary](https://intelpython.github.io/dpnp/reference/comparison.html#summary)
 
 [Full documentation](https://intelpython.github.io/dpnp/)
 
-[DPNP C++ backend documentation](https://intelpython.github.io/dpnp/backend_doc/)
+`Dpnp` is the core part of a larger family of [data-parallel Python libraries and tools](https://www.intel.com/content/www/us/en/developer/tools/oneapi/distribution-for-python.html)
+to program on XPUs.
 
-## Build from source:
-Ensure you have the following prerequisite packages installed:
 
-- `cython`
-- `cmake >=3.21`
-- `dpcpp_linux-64` or `dpcpp_win-64` (depending on your OS)
-- `dpctl`
-- `mkl-devel-dpcpp`
-- `onedpl-devel`
-- `ninja`
-- `numpy >=1.19,<1.25a0`
-- `python`
-- `scikit-build`
-- `setuptools`
-- `sysroot_linux-64 >=2.28` (only on Linux OS)
-- `tbb-devel`
+# Installing
 
-After these steps, `dpnp` can be built in debug mode as follows:
+You can install the library using `conda`, `mamba` or [pip](https://pypi.org/project/dpnp/)
+package managers. It is also available as part of the [Intel(R) Distribution for Python](https://www.intel.com/content/www/us/en/developer/tools/oneapi/distribution-for-python.html)
+(IDP).
 
-```bash
-git clone https://github.com/IntelPython/dpnp
-cd dpnp
-python scripts/build_locally.py
-```
+## Intel(R) Distribution for Python
 
-## Install Wheel Package via pip
-Install DPNP
-```cmd
-python -m pip install --index-url https://software.repos.intel.com/python/pypi dpnp
-```
+You can find the most recent release of `dpnp` every quarter as part of the IDP
+releases.
 
-Set path to Performance Libraries in case of using venv or system Python:
-```cmd
-export LD_LIBRARY_PATH=<path_to_your_env>/lib
-```
+To get the library from the latest release, follow the instructions from
+[Get Started With Intel® Distribution for Python](https://www.intel.com/content/www/us/en/developer/articles/technical/get-started-with-intel-distribution-for-python.html).
 
-It is also required to set following environment variables:
-```cmd
-export OCL_ICD_FILENAMES_RESET=1
-export OCL_ICD_FILENAMES=libintelocl.so
-```
+## Conda
 
-## Run test
-```bash
-pytest
-# or
-pytest tests/test_matmul.py -s -v
-# or
-python -m unittest tests/test_mixins.py
-```
+To install `dpnp` from the Intel(R) conda channel, use the following command:
 
-## Run numpy external test
 ```bash
-. ./0.env.sh
-python -m tests.third_party.numpy_ext
-# or
-python -m tests.third_party.numpy_ext core/tests/test_umath.py
-# or
-python -m tests.third_party.numpy_ext core/tests/test_umath.py::TestHypot::test_simple
+conda install dpnp -c https://software.repos.intel.com/python/conda/ -c conda-forge
 ```
 
-### Building documentation:
+## Pip
+
+The `dpnp` can be installed using `pip` obtaining wheel packages either from
+PyPi or from Intel(R) channel. To install `dpnp` wheel package from Intel(R)
+channel, run the following command:
+
 ```bash
-Prerequisites:
-$ conda install sphinx sphinx_rtd_theme
-Building:
-1. Install dpnp into your python environment
-2. $ cd doc && make html
-3. The documentation will be in doc/_build/html
+python -m pip install --index-url https://software.repos.intel.com/python/pypi dpnp
 ```
 
-## Packaging:
+## Installing the bleeding edge
+
+To try out the latest features, install `dpnp` using our development channel on
+Anaconda cloud:
+
 ```bash
-. ./0.env.sh
-conda-build conda-recipe/
+conda install dpnp -c dppy/label/dev -c https://software.repos.intel.com/python/conda/ -c conda-forge
 ```
 
-## Run benchmark:
-```bash
-cd benchmarks/
 
-asv run --python=python --bench <filename without .py>
-# example:
-asv run --python=python --bench bench_elementwise
+# Building
 
-# or
+Refer to our [Documentation](https://intelpython.github.io/dpnp/quick_start_guide.html)
+for more information on setting up a development environment and building `dpnp`
+from the source.
 
-asv run --python=python --bench <class>.<bench>
-# example:
-asv run --python=python --bench Elementwise.time_square
 
-# add --quick option to run every case once but looks like first execution has additional overheads and takes a lot of time (need to be investigated)
-```
+# Running Tests
 
+Tests are located in folder [dpnp/tests](dpnp/tests).
 
-## Tests matrix:
-| # |Name                                |OS   |distributive|interpreter|python used from|SYCL queue manager|build commands set                                                                                                                              |forced environment                                                                                                       |
-|---|------------------------------------|-----|------------|-----------|:--------------:|:----------------:|------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------|
-|1  |Ubuntu 20.04 Python37               |Linux|Ubuntu 20.04|Python 3.7 |  IntelOneAPI   |      local       |export DPNP_DEBUG=1 python setup.py clean python setup.py build_clib python setup.py build_ext --inplace pytest                                 |cmake-3.19.2, valgrind, pytest-valgrind, conda-build, pytest, hypothesis                                                 |
-|2  |Ubuntu 20.04 Python38               |Linux|Ubuntu 20.04|Python 3.8 |  IntelOneAPI   |      local       |export DPNP_DEBUG=1 python setup.py clean python setup.py build_clib python setup.py build_ext --inplace pytest                                 |cmake-3.19.2, valgrind, pytest-valgrind, conda-build, pytest, hypothesis                                                 |
-|3  |Ubuntu 20.04 Python39               |Linux|Ubuntu 20.04|Python 3.9 |  IntelOneAPI   |      local       |export DPNP_DEBUG=1 python setup.py clean python setup.py build_clib python setup.py build_ext --inplace pytest                                 |cmake-3.19.2, valgrind, pytest-valgrind, conda-build, pytest, hypothesis                                                 |
-|4  |Ubuntu 20.04 External Tests Python37|Linux|Ubuntu 20.04|Python 3.7 |  IntelOneAPI   |      local       |export DPNP_DEBUG=1 python setup.py clean python setup.py build_clib python setup.py build_ext --inplace python -m tests_external.numpy.runtests|cmake-3.19.2, valgrind, pytest-valgrind, conda-build, pytest, hypothesis                                                 |
-|5  |Ubuntu 20.04 External Tests Python38|Linux|Ubuntu 20.04|Python 3.8 |  IntelOneAPI   |      local       |export DPNP_DEBUG=1 python setup.py clean python setup.py build_clib python setup.py build_ext --inplace python -m tests_external.numpy.runtests|cmake-3.19.2, valgrind, pytest-valgrind, conda-build, pytest, hypothesis                                                 |
-|6  |Ubuntu 20.04 External Tests Python39|Linux|Ubuntu 20.04|Python 3.9 |  IntelOneAPI   |      local       |export DPNP_DEBUG=1 python setup.py clean python setup.py build_clib python setup.py build_ext --inplace python -m tests_external.numpy.runtests|cmake-3.19.2, valgrind, pytest-valgrind, conda-build, pytest, hypothesis                                                 |
-|7  |Code style                          |Linux|Ubuntu 20.04|Python 3.8 |  IntelOneAPI   |      local       |python ./setup.py style                                                                                                                         |cmake-3.19.2, valgrind, pytest-valgrind, conda-build, pytest, hypothesis, conda-verify, pycodestyle, autopep8, black     |
-|8  |Valgrind                            |Linux|Ubuntu 20.04|           |  IntelOneAPI   |      local       |export DPNP_DEBUG=1 python setup.py clean python setup.py build_clib python setup.py build_ext --inplace                                        |cmake-3.19.2, valgrind, pytest-valgrind, conda-build, pytest, hypothesis                                                 |
-|9  |Code coverage                       |Linux|Ubuntu 20.04|Python 3.8 |  IntelOneAPI   |      local       |export DPNP_DEBUG=1 python setup.py clean python setup.py build_clib python setup.py build_ext --inplace                                        |cmake-3.19.2, valgrind, pytest-valgrind, conda-build, pytest, hypothesis, conda-verify, pycodestyle, autopep8, pytest-cov|
+To run the tests, use:
+```bash
+python -m pytest --pyargs dpnp
+```

conda-recipe/meta.yaml

@@ -78,6 +78,6 @@ extra:
     recipe-maintainers:
         - oleksandr-pavlyk
         - antonwolfy
-        - npolina4
+        - AlexanderKalistratov
         - vtavana
         - vlad-perevezentsev

dpnp/dpnp_iface_indexing.py

@@ -51,10 +51,7 @@
     dpnp_putmask,
 )
 from .dpnp_array import dpnp_array
-from .dpnp_utils import (
-    call_origin,
-    get_usm_allocations,
-)
+from .dpnp_utils import call_origin, get_usm_allocations
 
 __all__ = [
     "choose",
@@ -585,11 +582,12 @@ def extract(condition, a):
     """
 
     usm_a = dpnp.get_usm_ndarray(a)
+    usm_type, exec_q = get_usm_allocations([usm_a, condition])
     usm_cond = dpnp.as_usm_ndarray(
         condition,
         dtype=dpnp.bool,
-        usm_type=usm_a.usm_type,
-        sycl_queue=usm_a.sycl_queue,
+        usm_type=usm_type,
+        sycl_queue=exec_q,
     )
 
     if usm_cond.size != usm_a.size:

tests/test_sycl_queue.py

@@ -406,6 +406,20 @@ def test_copy_operation(device):
     assert_sycl_queue_equal(y.sycl_queue, x.sycl_queue)
 
 
+@pytest.mark.parametrize(
+    "device",
+    valid_devices,
+    ids=[device.filter_string for device in valid_devices],
+)
+def test_extract(device):
+    x = dpnp.arange(3, device=device)
+    y = dpnp.array([True, False, True], device=device)
+    result = dpnp.extract(x, y)
+
+    assert_sycl_queue_equal(result.sycl_queue, x.sycl_queue)
+    assert_sycl_queue_equal(result.sycl_queue, y.sycl_queue)
+
+
 @pytest.mark.parametrize(
     "device",
     valid_devices,

tests/test_usm_type.py

@@ -769,6 +769,18 @@ def test_concat_stack(func, data1, data2, usm_type_x, usm_type_y):
     assert z.usm_type == du.get_coerced_usm_type([usm_type_x, usm_type_y])
 
 
+@pytest.mark.parametrize("usm_type_x", list_of_usm_types, ids=list_of_usm_types)
+@pytest.mark.parametrize("usm_type_y", list_of_usm_types, ids=list_of_usm_types)
+def test_extract(usm_type_x, usm_type_y):
+    x = dp.arange(3, usm_type=usm_type_x)
+    y = dp.array([True, False, True], usm_type=usm_type_y)
+    z = dp.extract(y, x)
+
+    assert x.usm_type == usm_type_x
+    assert y.usm_type == usm_type_y
+    assert z.usm_type == du.get_coerced_usm_type([usm_type_x, usm_type_y])
+
+
 @pytest.mark.parametrize(
     "func,data1",
     [