Switch to SimplexLab organization

.github/workflows/build-deploy-docs.yml

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

README.md

@@ -2,10 +2,10 @@
 
 [![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)
 [![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)
-[![Tests](https://github.com/TorchJD/torchjd/actions/workflows/tests.yml/badge.svg)](https://github.com/TorchJD/torchjd/actions/workflows/tests.yml)
-[![codecov](https://codecov.io/gh/TorchJD/torchjd/graph/badge.svg?token=8AUCZE76QH)](https://codecov.io/gh/TorchJD/torchjd)
-[![mypy](https://img.shields.io/github/actions/workflow/status/TorchJD/torchjd/tests.yml?label=mypy)](https://github.com/TorchJD/torchjd/actions/workflows/tests.yml)
-[![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)
+[![Tests](https://github.com/SimplexLab/torchjd/actions/workflows/tests.yml/badge.svg)](https://github.com/SimplexLab/torchjd/actions/workflows/tests.yml)
+[![codecov](https://codecov.io/gh/SimplexLab/torchjd/graph/badge.svg?token=8AUCZE76QH)](https://codecov.io/gh/SimplexLab/torchjd)
+[![mypy](https://img.shields.io/github/actions/workflow/status/SimplexLab/torchjd/tests.yml?label=mypy)](https://github.com/SimplexLab/torchjd/actions/workflows/tests.yml)
+[![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)
 [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/torchjd)](https://pypi.org/project/torchjd/)
 [![Static Badge](https://img.shields.io/badge/Discord%20-%20community%20-%20%235865F2?logo=discord&logoColor=%23FFFFFF&label=Discord)](https://discord.gg/76KkRnb3nk)
 

docs/source/conf.py

@@ -96,7 +96,7 @@ def linkcode_resolve(domain: str, info: dict[str, str]) -> str | None:
     line_str = _get_line_str(obj)
     version_str = _get_version_str()
 
-    link = f"https://github.com/TorchJD/torchjd/blob/{version_str}/{file_name}{line_str}"
+    link = f"https://github.com/SimplexLab/torchjd/blob/{version_str}/{file_name}{line_str}"
     return link
 
 

docs/source/examples/rnn.rst

@@ -33,6 +33,6 @@ descent can be leveraged to enhance optimization.
 .. note::
     At the time of writing, there seems to be an incompatibility between ``torch.vmap`` and
     ``torch.nn.RNN`` when running on CUDA (see `this issue
-    <https://github.com/TorchJD/torchjd/issues/220>`_ for more info), so we advise to set the
+    <https://github.com/SimplexLab/torchjd/issues/220>`_ for more info), so we advise to set the
     ``parallel_chunk_size`` to ``1`` to avoid using ``torch.vmap``. To improve performance, you can
     check whether ``parallel_chunk_size=None`` (maximal parallelization) works on your side.

docs/source/index.rst

@@ -54,7 +54,7 @@ of the batch and per task, in the context of multi-task learning. We call this
 :doc:`Instance-Wise Risk Multi-Task Learning <examples/iwmtl>` (IWMTL).
 
 TorchJD is open-source, under MIT License. The source code is available on
-`GitHub <https://github.com/TorchJD/torchjd>`_.
+`GitHub <https://github.com/SimplexLab/torchjd>`_.
 
 .. toctree::
     :caption: Getting Started

pyproject.toml

@@ -61,8 +61,8 @@ SOFTWARE.
 [project.urls]
 Homepage = "https://torchjd.org/"
 Documentation = "https://torchjd.org/"
-Source = "https://github.com/TorchJD/torchjd"
-Changelog = "https://github.com/TorchJD/torchjd/blob/main/CHANGELOG.md"
+Source = "https://github.com/SimplexLab/torchjd"
+Changelog = "https://github.com/SimplexLab/torchjd/blob/main/CHANGELOG.md"
 
 [dependency-groups]
 check = [

src/torchjd/autojac/_backward.py

@@ -61,8 +61,8 @@ def backward(
         To differentiate in parallel, ``backward`` relies on ``torch.vmap``, which has some
         limitations: `it does not work on the output of compiled functions
         <https://github.com/pytorch/pytorch/issues/138422>`_, `when some tensors have
-        <https://github.com/TorchJD/torchjd/issues/184>`_ ``retains_grad=True`` or `when using an
-        RNN on CUDA <https://github.com/TorchJD/torchjd/issues/220>`_, for instance. If you
+        <https://github.com/SimplexLab/torchjd/issues/184>`_ ``retains_grad=True`` or `when using an
+        RNN on CUDA <https://github.com/SimplexLab/torchjd/issues/220>`_, for instance. If you
         experience issues with ``backward`` try to use ``parallel_chunk_size=1`` to avoid relying on
         ``torch.vmap``.
     """

src/torchjd/autojac/_mtl_backward.py

@@ -61,8 +61,8 @@ def mtl_backward(
         To differentiate in parallel, ``mtl_backward`` relies on ``torch.vmap``, which has some
         limitations: `it does not work on the output of compiled functions
         <https://github.com/pytorch/pytorch/issues/138422>`_, `when some tensors have
-        <https://github.com/TorchJD/torchjd/issues/184>`_ ``retains_grad=True`` or `when using an
-        RNN on CUDA <https://github.com/TorchJD/torchjd/issues/220>`_, for instance. If you
+        <https://github.com/SimplexLab/torchjd/issues/184>`_ ``retains_grad=True`` or `when using an
+        RNN on CUDA <https://github.com/SimplexLab/torchjd/issues/220>`_, for instance. If you
         experience issues with ``backward`` try to use ``parallel_chunk_size=1`` to avoid relying on
         ``torch.vmap``.
     """

src/torchjd/autojac/_utils.py

@@ -77,7 +77,7 @@ def _get_descendant_accumulate_grads(
 
     # This implementation more or less follows what is advised in
     # https://discuss.pytorch.org/t/autograd-graph-traversal/213658 and what was suggested in
-    # https://github.com/TorchJD/torchjd/issues/216.
+    # https://github.com/SimplexLab/torchjd/issues/216.
     while nodes_to_traverse:
         node = nodes_to_traverse.popleft()  # Breadth-first