diff --git a/.github/workflows/build-sphinx.yml b/.github/workflows/build-sphinx.yml index 46d6667b99b..c1a10a4715e 100644 --- a/.github/workflows/build-sphinx.yml +++ b/.github/workflows/build-sphinx.yml @@ -104,7 +104,6 @@ jobs: - name: Setup miniconda uses: conda-incubator/setup-miniconda@a4260408e20b96e80095f42ff7f1a15b27dd94ca # v3.0.4 with: - miniforge-variant: Mambaforge miniforge-version: latest use-mamba: true channels: conda-forge diff --git a/.github/workflows/conda-package.yml b/.github/workflows/conda-package.yml index 4481223e052..6c34fa976d7 100644 --- a/.github/workflows/conda-package.yml +++ b/.github/workflows/conda-package.yml @@ -103,7 +103,6 @@ jobs: - name: Setup miniconda uses: conda-incubator/setup-miniconda@a4260408e20b96e80095f42ff7f1a15b27dd94ca # v3.0.4 with: - miniforge-variant: Mambaforge miniforge-version: latest use-mamba: true channels: conda-forge @@ -197,7 +196,6 @@ jobs: - name: Setup miniconda uses: conda-incubator/setup-miniconda@a4260408e20b96e80095f42ff7f1a15b27dd94ca # v3.0.4 with: - miniforge-variant: Mambaforge miniforge-version: latest use-mamba: true channels: conda-forge @@ -327,7 +325,6 @@ jobs: - name: Setup miniconda uses: conda-incubator/setup-miniconda@a4260408e20b96e80095f42ff7f1a15b27dd94ca # v3.0.4 with: - miniforge-variant: Mambaforge miniforge-version: latest use-mamba: true channels: conda-forge @@ -469,7 +466,6 @@ jobs: - name: Setup miniconda uses: conda-incubator/setup-miniconda@a4260408e20b96e80095f42ff7f1a15b27dd94ca # v3.0.4 with: - miniforge-variant: Mambaforge miniforge-version: latest use-mamba: true channels: conda-forge @@ -505,7 +501,6 @@ jobs: steps: - uses: conda-incubator/setup-miniconda@a4260408e20b96e80095f42ff7f1a15b27dd94ca # v3.0.4 with: - miniforge-variant: Mambaforge miniforge-version: latest use-mamba: true channels: conda-forge diff --git a/.github/workflows/generate_coverage.yaml b/.github/workflows/generate_coverage.yaml index 3db8f2e311a..36a7aecf28d 100644 --- a/.github/workflows/generate_coverage.yaml +++ b/.github/workflows/generate_coverage.yaml @@ -62,7 +62,6 @@ jobs: - name: Setup miniconda uses: conda-incubator/setup-miniconda@a4260408e20b96e80095f42ff7f1a15b27dd94ca # v3.0.4 with: - miniforge-variant: Mambaforge miniforge-version: latest use-mamba: true channels: conda-forge diff --git a/CHANGELOG.md b/CHANGELOG.md index 864fb2fb79a..f428b033c7d 100644 --- a/CHANGELOG.md +++ b/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 + +* Changed to use `Miniforge` installer in GutHub actions [#2057](https://github.com/IntelPython/dpnp/pull/2057) +* Updated `README.md` to reflect current installation requirements and available options [#2166](https://github.com/IntelPython/dpnp/pull/2166) + +### Fixed + +* Resolved a compilation error when building with DPC++ 2025.1 compiler [#2211](https://github.com/IntelPython/dpnp/pull/2211) + + ## [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. diff --git a/README.md b/README.md index aa31495d88f..6dd31be3e23 100644 --- a/README.md +++ b/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) +oneAPI logo + # 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=/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 -# 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 . -# 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 +``` diff --git a/dpnp/backend/kernels/dpnp_krnl_common.cpp b/dpnp/backend/kernels/dpnp_krnl_common.cpp index b1d864327e6..453c9a88747 100644 --- a/dpnp/backend/kernels/dpnp_krnl_common.cpp +++ b/dpnp/backend/kernels/dpnp_krnl_common.cpp @@ -33,11 +33,23 @@ #include "queue_sycl.hpp" #include +/** + * Version of SYCL DPC++ 2025.1 compiler where support of + * sycl::ext::oneapi::experimental::properties was added. + */ +#ifndef __SYCL_COMPILER_REDUCTION_PROPERTIES_SUPPORT +#define __SYCL_COMPILER_REDUCTION_PROPERTIES_SUPPORT 20241129 +#endif + namespace mkl_blas = oneapi::mkl::blas; namespace mkl_blas_cm = oneapi::mkl::blas::column_major; namespace mkl_blas_rm = oneapi::mkl::blas::row_major; namespace mkl_lapack = oneapi::mkl::lapack; +#if __SYCL_COMPILER_VERSION >= __SYCL_COMPILER_REDUCTION_PROPERTIES_SUPPORT +namespace syclex = sycl::ext::oneapi::experimental; +#endif + template @@ -76,8 +88,13 @@ sycl::event dot(sycl::queue &queue, cgh.parallel_for( sycl::range<1>{size}, sycl::reduction( - result_out, std::plus<_DataType_output>(), - sycl::property::reduction::initialize_to_identity{}), + result_out, sycl::plus<_DataType_output>(), +#if __SYCL_COMPILER_VERSION >= __SYCL_COMPILER_REDUCTION_PROPERTIES_SUPPORT + syclex::properties(syclex::initialize_to_identity) +#else + sycl::property::reduction::initialize_to_identity {} +#endif + ), [=](sycl::id<1> idx, auto &sum) { sum += static_cast<_DataType_output>( input1_in[idx * input1_strides]) * diff --git a/tests/third_party/cupy/creation_tests/test_ranges.py b/tests/third_party/cupy/creation_tests/test_ranges.py index 92c81061b7a..bd3a21539ae 100644 --- a/tests/third_party/cupy/creation_tests/test_ranges.py +++ b/tests/third_party/cupy/creation_tests/test_ranges.py @@ -172,7 +172,7 @@ def test_linspace_float_overflow(self, xp): dtype = cupy.default_float_type() return xp.linspace(0.0, xp.finfo(dtype).max / 5, 10, dtype=dtype) - @testing.numpy_cupy_allclose() + @testing.numpy_cupy_allclose(rtol={numpy.float32: 1e-6, "default": 1e-7}) def test_linspace_float_underflow(self, xp): # find minimum subnormal number dtype = cupy.default_float_type()