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chore: Switch to SimplexLab organization (#504)
* Rename `TorchJD/torchjd` to `SimplexLab/TorchJD`. * Rename `TorchJD/documentation` to `SimplexLab/TorchJD-documentation`. --------- Co-authored-by: Valérian Rey <31951177+ValerianRey@users.noreply.github.com>
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.github/workflows/build-deploy-docs.yml

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@@ -49,27 +49,27 @@ jobs:
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env:
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TORCHJD_VERSION: ${{ steps.deploy_folder.outputs.TORCHJD_VERSION }}
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- name: Deploy to DEPLOY_DIR of TorchJD/documentation
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- name: Deploy to DEPLOY_DIR of SimplexLab/TorchJD-documentation
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uses: peaceiris/actions-gh-pages@v4
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with:
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deploy_key: ${{ secrets.PROD_DOCUMENTATION_DEPLOY_KEY }}
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publish_dir: docs/build/dirhtml
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destination_dir: ${{ steps.deploy_folder.outputs.DEPLOY_DIR }}
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external_repository: TorchJD/documentation
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external_repository: SimplexLab/TorchJD-documentation
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publish_branch: main
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- name: Kill ssh-agent
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# See: https://github.com/peaceiris/actions-gh-pages/issues/909
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run: killall ssh-agent
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- name: Deploy to stable of TorchJD/documentation
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- name: Deploy to stable of SimplexLab/TorchJD-documentation
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if: startsWith(github.ref, 'refs/tags/')
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uses: peaceiris/actions-gh-pages@v4
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with:
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deploy_key: ${{ secrets.PROD_DOCUMENTATION_DEPLOY_KEY }}
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publish_dir: docs/build/dirhtml
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destination_dir: stable
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external_repository: TorchJD/documentation
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external_repository: SimplexLab/TorchJD-documentation
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publish_branch: main
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- name: Add documentation link to summary

README.md

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[![Doc](https://img.shields.io/badge/Doc-torchjd.org-blue?logo=data%3Aimage%2Fsvg%2Bxml%3Bbase64%2CPD94bWwgdmVyc2lvbj0iMS4wIiBlbmNvZGluZz0iVVRGLTgiIHN0YW5kYWxvbmU9Im5vIj8%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%2BCiAgPGRlZnMKICAgICBpZD0iZGVmczEiIC8%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)](https://torchjd.org)
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[![Static Badge](https://img.shields.io/badge/%F0%9F%92%AC_ChatBot-chat.torchjd.org-blue?logo=%F0%9F%92%AC)](https://chat.torchjd.org)
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[![Tests](https://github.com/TorchJD/torchjd/actions/workflows/checks.yml/badge.svg)](https://github.com/TorchJD/torchjd/actions/workflows/checks.yml)
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[![codecov](https://codecov.io/gh/TorchJD/torchjd/graph/badge.svg?token=8AUCZE76QH)](https://codecov.io/gh/TorchJD/torchjd)
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[![pre-commit.ci status](https://results.pre-commit.ci/badge/github/TorchJD/torchjd/main.svg)](https://results.pre-commit.ci/latest/github/TorchJD/torchjd/main)
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[![Tests](https://github.com/SimplexLab/TorchJD/actions/workflows/checks.yml/badge.svg)](https://github.com/SimplexLab/TorchJD/actions/workflows/checks.yml)
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[![codecov](https://codecov.io/gh/SimplexLab/TorchJD/graph/badge.svg?token=8AUCZE76QH)](https://codecov.io/gh/SimplexLab/TorchJD)
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[![pre-commit.ci status](https://results.pre-commit.ci/badge/github/SimplexLab/TorchJD/main.svg)](https://results.pre-commit.ci/latest/github/SimplexLab/TorchJD/main)
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[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/torchjd)](https://pypi.org/project/torchjd/)
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[![Static Badge](https://img.shields.io/badge/Discord%20-%20community%20-%20%235865F2?logo=discord&logoColor=%23FFFFFF&label=Discord)](https://discord.gg/76KkRnb3nk)
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docs/source/conf.py

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line_str = _get_line_str(obj)
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version_str = _get_version_str()
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link = f"https://github.com/TorchJD/torchjd/blob/{version_str}/{file_name}{line_str}"
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link = f"https://github.com/SimplexLab/TorchJD/blob/{version_str}/{file_name}{line_str}"
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return link
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docs/source/examples/rnn.rst

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.. note::
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At the time of writing, there seems to be an incompatibility between ``torch.vmap`` and
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``torch.nn.RNN`` when running on CUDA (see `this issue
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<https://github.com/TorchJD/torchjd/issues/220>`_ for more info), so we advise to set the
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<https://github.com/SimplexLab/TorchJD/issues/220>`_ for more info), so we advise to set the
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``parallel_chunk_size`` to ``1`` to avoid using ``torch.vmap``. To improve performance, you can
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check whether ``parallel_chunk_size=None`` (maximal parallelization) works on your side.

docs/source/index.rst

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:doc:`Instance-Wise Risk Multi-Task Learning <examples/iwmtl>` (IWMTL).
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TorchJD is open-source, under MIT License. The source code is available on
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`GitHub <https://github.com/TorchJD/torchjd>`_.
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`GitHub <https://github.com/SimplexLab/TorchJD>`_.
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.. toctree::
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:caption: Getting Started

pyproject.toml

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[project.urls]
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Homepage = "https://torchjd.org/"
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Documentation = "https://torchjd.org/"
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Source = "https://github.com/TorchJD/torchjd"
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Changelog = "https://github.com/TorchJD/torchjd/blob/main/CHANGELOG.md"
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Source = "https://github.com/SimplexLab/TorchJD"
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Changelog = "https://github.com/SimplexLab/TorchJD/blob/main/CHANGELOG.md"
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[dependency-groups]
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check = [

src/torchjd/autojac/_backward.py

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To differentiate in parallel, ``backward`` relies on ``torch.vmap``, which has some
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limitations: `it does not work on the output of compiled functions
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<https://github.com/pytorch/pytorch/issues/138422>`_, `when some tensors have
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<https://github.com/TorchJD/torchjd/issues/184>`_ ``retains_grad=True`` or `when using an
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RNN on CUDA <https://github.com/TorchJD/torchjd/issues/220>`_, for instance. If you
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<https://github.com/SimplexLab/TorchJD/issues/184>`_ ``retains_grad=True`` or `when using an
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RNN on CUDA <https://github.com/SimplexLab/TorchJD/issues/220>`_, for instance. If you
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experience issues with ``backward`` try to use ``parallel_chunk_size=1`` to avoid relying on
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``torch.vmap``.
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"""

src/torchjd/autojac/_mtl_backward.py

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To differentiate in parallel, ``mtl_backward`` relies on ``torch.vmap``, which has some
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limitations: `it does not work on the output of compiled functions
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<https://github.com/pytorch/pytorch/issues/138422>`_, `when some tensors have
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<https://github.com/TorchJD/torchjd/issues/184>`_ ``retains_grad=True`` or `when using an
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RNN on CUDA <https://github.com/TorchJD/torchjd/issues/220>`_, for instance. If you
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<https://github.com/SimplexLab/TorchJD/issues/184>`_ ``retains_grad=True`` or `when using an
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RNN on CUDA <https://github.com/SimplexLab/TorchJD/issues/220>`_, for instance. If you
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experience issues with ``backward`` try to use ``parallel_chunk_size=1`` to avoid relying on
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``torch.vmap``.
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"""

src/torchjd/autojac/_utils.py

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# This implementation more or less follows what is advised in
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# https://discuss.pytorch.org/t/autograd-graph-traversal/213658 and what was suggested in
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# https://github.com/TorchJD/torchjd/issues/216.
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# https://github.com/SimplexLab/TorchJD/issues/216.
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while nodes_to_traverse:
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node = nodes_to_traverse.popleft() # Breadth-first
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