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‎.github/dependabot.yml

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directory: "/"
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schedule:
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interval: "weekly"
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day: "saturday"
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rebase-strategy: "disabled"

‎.github/workflows/build-sphinx.yml

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sudo apt-get install -y nvidia-cuda-toolkit clinfo
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- name: Checkout repo
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uses: actions/checkout@b4ffde65f46336ab88eb53be808477a3936bae11 # v4.1.1
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uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633 # v4.1.2
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with:
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fetch-depth: 0
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# https://github.com/marketplace/actions/setup-miniconda
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- name: Setup miniconda
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uses: conda-incubator/setup-miniconda@392cf345b1784333caa1a1185081c71e6ffd61bc # v3.0.2
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uses: conda-incubator/setup-miniconda@030178870c779d9e5e1b4e563269f3aa69b04081 # v3.0.3
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with:
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auto-update-conda: true
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python-version: ${{ env.python-ver }}
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runs-on: ubuntu-20.04
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steps:
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- uses: actions/checkout@b4ffde65f46336ab88eb53be808477a3936bae11 # v4.1.1
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- uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633 # v4.1.2
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with:
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fetch-depth: 0
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‎.github/workflows/conda-package.yml

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CHANNELS: '-c dppy/label/dev -c intel -c conda-forge --override-channels'
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CONDA_BUILD_VERSION: '24.1.2'
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CONDA_INDEX_VERSION: '0.4.0'
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TEST_ENV_NAME: 'test'
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# TODO: to add test_arraymanipulation.py back to the scope once crash on Windows is gone
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TEST_SCOPE: >-
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test_arraycreation.py
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access_token: ${{ github.token }}
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- name: Checkout DPNP repo
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uses: actions/checkout@b4ffde65f46336ab88eb53be808477a3936bae11 # v4.1.1
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uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633 # v4.1.2
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with:
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fetch-depth: 0
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- name: Setup miniconda
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uses: conda-incubator/setup-miniconda@392cf345b1784333caa1a1185081c71e6ffd61bc # v3.0.2
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uses: conda-incubator/setup-miniconda@030178870c779d9e5e1b4e563269f3aa69b04081 # v3.0.3
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with:
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auto-update-conda: true
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python-version: ${{ matrix.python }}
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run: conda install conda-build=${{ env.CONDA_BUILD_VERSION}}
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- name: Cache conda packages
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uses: actions/cache@13aacd865c20de90d75de3b17ebe84f7a17d57d2 # v4.0.0
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uses: actions/cache@0c45773b623bea8c8e75f6c82b208c3cf94ea4f9 # v4.0.2
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env:
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CACHE_NUMBER: 1 # Increase to reset cache
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with:
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steps:
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- name: Download artifact
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uses: actions/download-artifact@eaceaf801fd36c7dee90939fad912460b18a1ffe # v4.1.2
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uses: actions/download-artifact@c850b930e6ba138125429b7e5c93fc707a7f8427 # v4.1.4
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with:
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name: ${{ env.PACKAGE_NAME }} ${{ runner.os }} Python ${{ matrix.python }}
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path: ${{ env.pkg-path-in-channel }}
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tar -xvf ${{ env.pkg-path-in-channel }}/${{ env.PACKAGE_NAME }}-*.tar.bz2 -C ${{ env.extracted-pkg-path }}
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- name: Setup miniconda
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uses: conda-incubator/setup-miniconda@392cf345b1784333caa1a1185081c71e6ffd61bc # v3.0.2
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uses: conda-incubator/setup-miniconda@030178870c779d9e5e1b4e563269f3aa69b04081 # v3.0.3
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with:
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auto-update-conda: true
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python-version: ${{ matrix.python }}
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miniconda-version: 'latest'
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activate-environment: 'test'
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activate-environment: ${{ env.TEST_ENV_NAME }}
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- name: Install conda-index
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run: conda install conda-index=${{ env.CONDA_INDEX_VERSION}}
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run: conda install conda-index=${{ env.CONDA_INDEX_VERSION }}
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- name: Create conda channel
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run: |
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TEST_CHANNELS: '-c ${{ env.channel-path }} ${{ env.CHANNELS }}'
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- name: Cache conda packages
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uses: actions/cache@13aacd865c20de90d75de3b17ebe84f7a17d57d2 # v4.0.0
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uses: actions/cache@0c45773b623bea8c8e75f6c82b208c3cf94ea4f9 # v4.0.2
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env:
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CACHE_NUMBER: 1 # Increase to reset cache
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with:
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python -c "import dpnp; print(dpnp.__version__)"
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# TODO: run the whole scope once the issues on CPU are resolved
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# - name: Run tests
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# run: |
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# python -m pytest -q -ra --disable-warnings -vv ${{ env.TEST_SCOPE }}
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# working-directory: ${{ env.tests-path }}
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# TODO: remove once 2024.2 release is published
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- name: Run tests
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run: |
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python -m pytest -q -ra --disable-warnings -vv ${{ env.TEST_SCOPE }}
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working-directory: ${{ env.tests-path }}
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id: run_tests_linux
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uses: nick-fields/retry@7152eba30c6575329ac0576536151aca5a72780e # v3.0.0
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with:
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shell: bash
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timeout_minutes: 10
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max_attempts: 5
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retry_on: any
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command: |
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. $CONDA/etc/profile.d/conda.sh
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conda activate ${{ env.TEST_ENV_NAME }}
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cd ${{ env.tests-path }}
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python -m pytest -q -ra --disable-warnings -vv ${{ env.TEST_SCOPE }}
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test_windows:
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name: Test ['windows-latest', python='${{ matrix.python }}']
@@ -252,11 +268,10 @@ jobs:
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extracted-pkg-path: '${{ github.workspace }}\pkg'
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tests-path: '${{ github.workspace }}\pkg\info\test\tests\'
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ver-json-path: '${{ github.workspace }}\version.json'
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active-env-name: 'test'
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steps:
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- name: Download artifact
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uses: actions/download-artifact@eaceaf801fd36c7dee90939fad912460b18a1ffe # v4.1.2
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uses: actions/download-artifact@c850b930e6ba138125429b7e5c93fc707a7f8427 # v4.1.4
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with:
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name: ${{ env.PACKAGE_NAME }} ${{ runner.os }} Python ${{ matrix.python }}
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path: ${{ env.pkg-path-in-channel }}
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dir ${{ env.extracted-pkg-path }}
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- name: Setup miniconda
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uses: conda-incubator/setup-miniconda@392cf345b1784333caa1a1185081c71e6ffd61bc # v3.0.2
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uses: conda-incubator/setup-miniconda@030178870c779d9e5e1b4e563269f3aa69b04081 # v3.0.3
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with:
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python-version: ${{ matrix.python }}
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miniconda-version: 'latest'
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activate-environment: ${{ env.active-env-name }}
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activate-environment: ${{ env.TEST_ENV_NAME }}
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- name: Store conda paths as envs
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run: |
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run: more lockfile
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- name: Cache conda packages
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uses: actions/cache@13aacd865c20de90d75de3b17ebe84f7a17d57d2 # v4.0.0
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uses: actions/cache@0c45773b623bea8c8e75f6c82b208c3cf94ea4f9 # v4.0.2
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env:
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CACHE_NUMBER: 1 # Increase to reset cache
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with:
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${{ runner.os }}-conda-${{ env.CACHE_NUMBER }}-python-${{ matrix.python }}-
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${{ runner.os }}-conda-${{ env.CACHE_NUMBER }}-
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- name: Install opencl_rt
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run: conda install opencl_rt -c intel --override-channels
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- name: Install dpnp
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run: |
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@echo on
@@ -362,10 +374,24 @@ jobs:
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python -c "import dpnp; print(dpnp.__version__)"
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# TODO: run the whole scope once the issues on CPU are resolved
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# - name: Run tests
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# run: |
379+
# python -m pytest -q -ra --disable-warnings -vv ${{ env.TEST_SCOPE }}
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# working-directory: ${{ env.tests-path }}
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# TODO: remove once 2024.2 release is published
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- name: Run tests
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run: |
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python -m pytest -q -ra --disable-warnings -vv ${{ env.TEST_SCOPE }}
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working-directory: ${{ env.tests-path }}
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id: run_tests_win
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uses: nick-fields/retry@7152eba30c6575329ac0576536151aca5a72780e # v3.0.0
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with:
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shell: cmd
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timeout_minutes: 15
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max_attempts: 5
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retry_on: any
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command: >-
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conda activate ${{ env.TEST_ENV_NAME }}
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& cd ${{ env.tests-path }}
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& python -m pytest -q -ra --disable-warnings -vv ${{ env.TEST_SCOPE }}
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upload:
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name: Upload ['${{ matrix.os }}', python='${{ matrix.python }}']
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- name: Download artifact
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uses: actions/download-artifact@eaceaf801fd36c7dee90939fad912460b18a1ffe # v4.1.2
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uses: actions/download-artifact@c850b930e6ba138125429b7e5c93fc707a7f8427 # v4.1.4
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with:
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name: ${{ env.PACKAGE_NAME }} ${{ runner.os }} Python ${{ matrix.python }}
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- name: Setup miniconda
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uses: conda-incubator/setup-miniconda@392cf345b1784333caa1a1185081c71e6ffd61bc # v3.0.2
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uses: conda-incubator/setup-miniconda@030178870c779d9e5e1b4e563269f3aa69b04081 # v3.0.3
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shell: bash -el {0}
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- uses: conda-incubator/setup-miniconda@392cf345b1784333caa1a1185081c71e6ffd61bc # v3.0.2
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- uses: conda-incubator/setup-miniconda@030178870c779d9e5e1b4e563269f3aa69b04081 # v3.0.3
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run-post: false
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channel-priority: "disabled"
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run: conda install anaconda-client
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- name: Checkout repo
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uses: actions/checkout@b4ffde65f46336ab88eb53be808477a3936bae11 # v4.1.1
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uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633 # v4.1.2
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repository: IntelPython/devops-tools
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fetch-depth: 0

‎.github/workflows/generate_coverage.yaml

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- name: Checkout repo
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uses: actions/checkout@b4ffde65f46336ab88eb53be808477a3936bae11 # v4.1.1
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uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633 # v4.1.2
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fetch-depth: 0
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- name: Setup miniconda
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uses: conda-incubator/setup-miniconda@392cf345b1784333caa1a1185081c71e6ffd61bc # v3.0.2
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uses: conda-incubator/setup-miniconda@030178870c779d9e5e1b4e563269f3aa69b04081 # v3.0.3
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‎.github/workflows/openssf-scorecard.yml

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steps:
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- name: "Checkout code"
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uses: actions/checkout@b4ffde65f46336ab88eb53be808477a3936bae11 # v4.1.1
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uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633 # v4.1.2
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with:
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persist-credentials: false
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# Upload the results to GitHub's code scanning dashboard.
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- name: "Upload to code-scanning"
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uses: github/codeql-action/upload-sarif@47b3d888fe66b639e431abf22ebca059152f1eea # v3.24.5
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uses: github/codeql-action/upload-sarif@1b1aada464948af03b950897e5eb522f92603cc2 # v3.24.9
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‎.github/workflows/pre-commit.yml

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pylint
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- name: Checkout DPNP repo
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uses: actions/checkout@b4ffde65f46336ab88eb53be808477a3936bae11 # v4.1.1
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uses: actions/checkout@9bb56186c3b09b4f86b1c65136769dd318469633 # v4.1.2
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- name: Set up python
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uses: actions/setup-python@0a5c61591373683505ea898e09a3ea4f39ef2b9c # v5.0.0

‎conda-recipe/meta.yaml

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{% set required_compiler_and_mkl_version = "2024.0" %}
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{% set excluded_compiler_version1 = "2024.0.1" %}
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{% set excluded_compiler_version2 = "2024.0.2" %}
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{% set excluded_compiler_version3 = "2024.0.3" %}
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{% set required_dpctl_version = "0.16.0" %}
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package:
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- scikit-build
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2829
- {{ compiler('cxx') }}
29-
- {{ compiler('dpcpp') }} >={{ required_compiler_and_mkl_version }},!={{ excluded_compiler_version1 }},!={{ excluded_compiler_version2 }} # [not osx]
30+
- {{ compiler('dpcpp') }} >={{ required_compiler_and_mkl_version }},!={{ excluded_compiler_version1 }},!={{ excluded_compiler_version2 }},!={{ excluded_compiler_version3 }} # [win]
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- {{ compiler('dpcpp') }} >={{ required_compiler_and_mkl_version }},!={{ excluded_compiler_version1 }},!={{ excluded_compiler_version2 }} # [linux]
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- python

‎doc/dpctl.rst

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An example below demonstrates how the Data Parallel Extension for NumPy* can be
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easily combined with the device management interface provided by dpctl package.
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13-
Literally, the SYCL* queue manager interface from the dpctl package allows
14-
to set an input queue as the currently usable queue inside the context
15-
manager's scope. This way an array creation function from the dpnp package
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which is defined inside the context will allocate the data using that queue.
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.. code-block:: python
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:linenos:
2015
21-
import dpctl
22-
import dpnp as np
16+
import dpctl
17+
import dpnp
18+
19+
d = dpctl.select_cpu_device()
20+
x = dpnp.array([1, 2, 3], device=d)
21+
s = dpnp.sum(x)
22+
23+
y = dpnp.linspace(0, dpnp.pi, num=10**6, device="gpu")
24+
f = 1 + y * dpnp.sin(y)
25+
26+
# locate argument where function attains global maximum
27+
max_arg = x[dpnp.argmax(f)]
28+
max_val = dpnp.max(f)
2329
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with dpctl.device_context("opencl:gpu"):
25-
x = np.array([1, 2, 3])
26-
s = np.sum(x)
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For more information please refer to `Data Parallel Control Library`_
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documentation.

‎doc/reference/dtype.rst

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dpnp.issubdtype
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dpnp.issubsctype
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dpnp.issubclass_
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dpnp.find_common_type
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Miscellaneous
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-------------

‎dpnp/backend/examples/example10.cpp

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5252

53-
dpnp_queue_initialize_c(QueueOptions::GPU_SELECTOR);
54-
5553
double *result = (double *)dpnp_memory_alloc_c(size * sizeof(double));
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5755
dpnp_rng_srand_c(seed); // TODO: will move

‎dpnp/backend/examples/example3.cpp

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{
4545
const size_t size = 256;
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47-
dpnp_queue_initialize_c();
4847
std::cout << "SYCL queue is CPU: " << dpnp_queue_is_cpu_c() << std::endl;
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int *array1 = (int *)dpnp_memory_alloc_c(size * sizeof(int));

‎dpnp/backend/examples/example5.cpp

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{
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55-
dpnp_queue_initialize_c(QueueOptions::CPU_SELECTOR);
56-
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double *result = (double *)dpnp_memory_alloc_c(size * sizeof(double));
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‎dpnp/backend/examples/example7.cpp

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const size_t size = 2;
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size_t len = size * size;
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48-
dpnp_queue_initialize_c(QueueOptions::CPU_SELECTOR);
49-
5048
float *array = (float *)dpnp_memory_alloc_c(len * sizeof(float));
5149
float *result1 = (float *)dpnp_memory_alloc_c(size * sizeof(float));
5250
float *result2 = (float *)dpnp_memory_alloc_c(len * sizeof(float));

‎dpnp/backend/examples/example8.cpp

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{
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const size_t size = 16;
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45-
dpnp_queue_initialize_c(QueueOptions::GPU_SELECTOR);
46-
4745
double *array = (double *)dpnp_memory_alloc_c(size * sizeof(double));
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long *result = (long *)dpnp_memory_alloc_c(size * sizeof(long));
4947

‎dpnp/backend/examples/example9.cpp

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long result = 0;
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long result_verification = 0;
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49-
dpnp_queue_initialize_c(QueueOptions::CPU_SELECTOR);
50-
5149
long *array =
5250
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‎dpnp/backend/examples/example_bs.cpp

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const double RISK_FREE = 0.1;
230230
const double VOLATILITY = 0.2;
231231

232-
dpnp_queue_initialize_c(QueueOptions::GPU_SELECTOR);
233232
std::cout << "SYCL queue is CPU: " << dpnp_queue_is_cpu_c() << std::endl;
234233

235234
double *price = (double *)dpnp_memory_alloc_c(SIZE * sizeof(double));

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