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.github/workflows/build-sphinx.yml

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pull_request:
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types: [opened, synchronize, reopened, closed]
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permissions:
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pull-requests: write
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env:
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PUBLISH_DIR: doc/_build/html/
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github_token: ${{ secrets.GITHUB_TOKEN }}
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publish_dir: ${{ env.PUBLISH_DIR }}
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- name: Deploy docs [PR]
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- name: Publish pull-request docs
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if: |
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!github.event.pull_request.head.repo.fork && github.event.pull_request && github.event.action != 'closed'
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uses: peaceiris/[email protected]
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user_name: 'github-actions[bot]'
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user_email: 'github-actions[bot]@users.noreply.github.com'
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- name: Comment with URL to published pull-request docs
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if: |
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!github.event.pull_request.head.repo.fork && github.event.pull_request && github.event.action != 'closed'
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env:
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PR_NUM: ${{ github.event.number }}
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uses: mshick/[email protected]
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with:
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message: |
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View rendered docs @ https://intelpython.github.io/dpnp/pulls/${{ env.PR_NUM }}/index.html
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allow-repeats: false
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clean:
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if: |
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!github.event.pull_request.head.repo.fork && github.event.pull_request && github.event.action == 'closed'
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git config --global user.email 'github-actions[bot]@users.noreply.github.com'
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git commit -m "Removing docs for closed pull request ${PR_NUM}"
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git push tokened_docs gh-pages
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- name: Modify the comment with URL to published pull-request docs
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uses: mshick/[email protected]
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with:
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find: |
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View rendered docs @.+
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replace: |
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View rendered docs @ https://intelpython.github.io/dpnp/index.html

doc/dpnp_backend_api.rst

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C++ backend API Reference
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*************************
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`DPNP C++ backend <backend_doc/>`_
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`C++ backend of Data Parallel Extension for NumPy* <backend_doc/>`_

doc/overview.rst

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The Data Parallel Extension for NumPy* is being developed as part of
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`Intel AI Analytics Toolkit`_ and is distributed with the
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`Intel Distribution for Python*`_. The dpnp package is also available
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on Anaconda cloud. Please refer the :doc:`getting_started` page to learn more.
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on Anaconda cloud. Please refer the :doc:`quick_start_guide` page to learn more.
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Being drop-in replacement for `NumPy*`_ means that the usage is very similar:
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doc/quick_start_guide.rst

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It is recommended to use conda packages from the ``anaconda.org/intel``
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channel. You will need one of the commands below:
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* Conda: ``conda install dpnp``
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* Conda: ``conda install dpnp -c intel -c conda-forge``
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* Pip: ``pip install dpnp``
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* Pip: ``pip install -i https://pypi.anaconda.org/intel/simple dpnp``
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These commands install dpnp package along with its dependencies, including
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``dpctl`` package with `Data Parallel Control Library`_ and all required

doc/reference/difference.rst

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Difference between DPNP and NumPy
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=================================
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Difference with NumPy*
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======================
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.. _Data types:
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dpnp/backend/doc/Doxyfile

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# for a project that appears at the top of each page and should give viewer a
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# quick idea about the purpose of the project. Keep the description short.
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PROJECT_BRIEF = "NumPy-like API accelerated with SYCL"
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PROJECT_BRIEF = "Data Parallel Extension for NumPy*"
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# With the PROJECT_LOGO tag one can specify a logo or an icon that is included
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# in the documentation. The maximum height of the logo should not exceed 55

dpnp/dpnp_iface.py

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def get_include():
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r"""Return the directory that contains the DPNP C++ backend \*.h header files."""
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r"""
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Return the directory that contains \*.h header files of dpnp C++ backend.
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dpnp_path = os.path.join(os.path.dirname(__file__), "backend", "include")
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An extension module that needs to be compiled against dpnp backend
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should use this function to locate the appropriate include directory.
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return dpnp_path
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"""
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return os.path.join(os.path.dirname(__file__), "backend", "include")
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def get_normalized_queue_device(obj=None, device=None, sycl_queue=None):

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