From 3afbcfd9793647fcd8eb1c88203ee8b957bab148 Mon Sep 17 00:00:00 2001 From: Anton Volkov Date: Tue, 12 Nov 2024 13:25:59 +0100 Subject: [PATCH 1/2] Update README.md --- README.md | 131 +++++++++++++++++++----------------------------------- 1 file changed, 46 insertions(+), 85 deletions(-) diff --git a/README.md b/README.md index aa31495d88fc..220a2768e2f0 100644 --- a/README.md +++ b/README.md @@ -6,117 +6,78 @@ [![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` 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) oneAPI -## 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 Intel(R) oneAPI 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 oneAPI release, follow the +instructions from Intel(R) [oneAPI installation guide](https://www.intel.com/content/www/us/en/developer/articles/guide/installation-guide-for-oneapi-toolkits.html). -It is also required to set following environment variables: -```cmd -export OCL_ICD_FILENAMES_RESET=1 -export OCL_ICD_FILENAMES=libintelocl.so -``` +> **NOTE:** You need to install the Intel(R) oneAPI AI Analytics Toolkit to get +>IDP and `dpnp`. -## Run test -```bash -pytest -# or -pytest tests/test_matmul.py -s -v -# or -python -m unittest tests/test_mixins.py -``` +## Conda + +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 +``` From 9791ea4bd6abc975785acf619d7096a2a89df654 Mon Sep 17 00:00:00 2001 From: Anton Volkov Date: Tue, 12 Nov 2024 17:28:26 +0100 Subject: [PATCH 2/2] Replace with a link to IDP installation guide --- README.md | 14 ++++++-------- 1 file changed, 6 insertions(+), 8 deletions(-) diff --git a/README.md b/README.md index 220a2768e2f0..6dd31be3e231 100644 --- a/README.md +++ b/README.md @@ -24,19 +24,17 @@ to program on XPUs. # Installing -You can install the library using `conda` or [pip](https://pypi.org/project/dpnp/) +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). -## Intel(R) oneAPI +## Intel(R) Distribution for Python -You can find the most recent release of `dpnp` every quarter as part of the Intel(R) oneAPI releases. +You can find the most recent release of `dpnp` every quarter as part of the IDP +releases. -To get the library from the latest oneAPI release, follow the -instructions from Intel(R) [oneAPI installation guide](https://www.intel.com/content/www/us/en/developer/articles/guide/installation-guide-for-oneapi-toolkits.html). - -> **NOTE:** You need to install the Intel(R) oneAPI AI Analytics Toolkit to get ->IDP and `dpnp`. +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). ## Conda