Fix warnings + Add test workflow

.github/workflows/ci.yaml

@@ -5,6 +5,14 @@ on:
   push:
     branches: [ master ]
 
+concurrency:
+  # github.workflow: name of the workflow
+  # github.event.pull_request.number || github.ref: pull request number or branch name if not a pull request
+  group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
+
+  # Cancel in-progress runs when a new workflow with the same group name is triggered
+  cancel-in-progress: true
+
 jobs:
   ci:
     runs-on: ubuntu-latest
@@ -24,12 +32,13 @@ jobs:
         uses: actions/setup-python@v5
         with:
           python-version: "3.10"
+          cache: "pip"
 
       - name: Pre-commit checks
         uses: pre-commit/[email protected]
 
       - name: Install package & dependencies
-        run: pip install --editable '.[dev, docs, tests, examples]'
+        run: pip install '.[tests]'
 
       - name: Launch tests & generate coverage report
         run: coverage run -m pytest tests
@@ -39,6 +48,10 @@ jobs:
         uses: py-cov-action/python-coverage-comment-action@v3
         with:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          # If the coverage percentage is above or equal to this value, the badge will be green.
+          MINIMUM_GREEN: 90
+          # If the coverage percentage is below this value, the badge will be red.
+          MINIMUM_ORANGE: 80
 
       - name: Store Pull Request comment to be posted
         uses: actions/upload-artifact@v4

.github/workflows/coverage.yaml

@@ -22,9 +22,12 @@ jobs:
       # artifact that contains the comment to be published
       actions: read
     steps:
-
       - name: Post comment
         uses: py-cov-action/python-coverage-comment-action@v3
         with:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
           GITHUB_PR_RUN_ID: ${{ github.event.workflow_run.id }}
+          # If the coverage percentage is above or equal to this value, the badge will be green.
+          MINIMUM_GREEN: 90
+          # If the coverage percentage is below this value, the badge will be red.
+          MINIMUM_ORANGE: 80

.github/workflows/publish.yaml

@@ -4,7 +4,7 @@ on:
   workflow_dispatch:
   push:
     tags:
-      - v.**
+      - 'v[0-9]+\.[0-9]+\.[0-9]+'
 
 jobs:
   publish:

.github/workflows/test.yaml

@@ -0,0 +1,48 @@
+name: Run tests
+
+on:
+  pull_request:
+  push:
+    branches: [ master ]
+
+concurrency:
+  # github.workflow: name of the workflow
+  # github.event.pull_request.number || github.ref: pull request number or branch name if not a pull request
+  group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
+
+  # Cancel in-progress runs when a new workflow with the same group name is triggered
+  cancel-in-progress: true
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: [ "3.9", "3.10", "3.11" ]
+        TORCH_VERSION: [ "1.13.1", "2.0.1", "2.1.2", "2.2.2", "2.3.1", "2.4.0" ]
+        include:
+          - python-version: "3.12"
+            TORCH_VERSION: "2.4.0"
+        exclude:
+          - python-version: "3.11"
+            TORCH_VERSION: "1.13.1"
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+          cache: "pip"
+
+      - name: Install dependencies and PyTorch ${{ matrix.TORCH_VERSION }}
+        run: |
+          pip install --upgrade pip
+          pip install torch==${{ matrix.TORCH_VERSION }} '.[tests]'
+
+      - name: Launch tests
+        # Only run the unit tests, not the pipeline tests.
+        # Pipeline tests are too expensive to run for every python/PyTorch version.
+        # However, they are run as part the coverage job in the CI workflow
+        run: pytest --ignore=tests/pipeline tests

.pre-commit-config.yaml

@@ -19,7 +19,7 @@ repos:
         files: \.py$
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.5.6
+    rev: v0.5.7
     hooks:
       - id: ruff
         types_or: [ python, pyi, jupyter ]

CITATION.cff

@@ -7,6 +7,8 @@ authors:
       given-names: "Juan"
     - family-names: "Hashemizadeh"
       given-names: "Meraj"
+    - family-names: "Lacoste-Julien"
+      given-names: "Simon"
 title: "Cooper: a toolkit for Lagrangian-based constrained optimization"
 date-released: 2022-03-15
 url: "https://github.com/cooper-org/cooper"

README.md

@@ -1,11 +1,17 @@
 # Cooper
 
-[![LICENSE](https://img.shields.io/badge/license-MIT-blue.svg)](https://github.com/cooper-org/cooper/tree/master/LICENSE)
+[![LICENSE](https://img.shields.io/pypi/l/cooper-optim)](https://github.com/cooper-org/cooper/tree/master/LICENSE)
+[![Version](https://img.shields.io/pypi/v/cooper-optim?label=version)](https://pypi.python.org/pypi/cooper-optim)
+[![Downloads](https://static.pepy.tech/badge/cooper-optim)](https://pypi.python.org/pypi/cooper-optim)
+[![Python](https://img.shields.io/pypi/pyversions/cooper-optim)](https://pypi.python.org/pypi/cooper-optim)
 [![DOCS](https://readthedocs.org/projects/cooper/badge/?version=latest)](https://cooper.readthedocs.io/en/latest/?version=latest)
-[![Build and Test](https://github.com/cooper-org/cooper/actions/workflows/build.yml/badge.svg)](https://github.com/cooper-org/cooper/actions/workflows/build.yml)
-[![Coverage](https://codecov.io/gh/cooper-org/cooper/graph/badge.svg?token=4U41P8JCE1)](https://codecov.io/gh/cooper-org/cooper)
-[![HitCount](https://hits.dwyl.com/cooper-org/cooper.svg?style=flat-square)](https://cooper.readthedocs.io/en/latest/?version=latest)
+[![Coverage badge](https://raw.githubusercontent.com/cooper-org/cooper/python-coverage-comment-action-data/badge.svg)](https://github.com/cooper-org/cooper/tree/python-coverage-comment-action-data)
+[![Continuous Integration](https://github.com/cooper-org/cooper/actions/workflows/ci.yml/badge.svg)](https://github.com/cooper-org/cooper/actions/workflows/ci.yml)
+[![Stars](https://img.shields.io/github/stars/cooper-org/cooper)](https://github.com/cooper-org/cooper)
+[![HitCount](https://img.shields.io/endpoint?url=https://hits.dwyl.com/cooper-org/cooper.json&color=brightgreen)](https://cooper.readthedocs.io/en/latest/?version=latest)
 [![contributions welcome](https://img.shields.io/badge/contributions-welcome-brightgreen.svg?style=flat)](https://github.com/cooper-org/cooper/issues)
+[![Discord](https://img.shields.io/badge/Discord-%235865F2.svg?logo=discord&logoColor=white)](https://discord.gg/Aq5PjH8m6E)
+[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)
 
 ## About
 
@@ -103,20 +109,21 @@ for epoch_num in range(50):
 ### Basic Installation
 
 ```bash
-pip install git+https://github.com/cooper-org/cooper.git
+pip install cooper-optim
 ```
 
 ### Development Installation
 
 First, clone the [repository](https://github.com/cooper-org/cooper), navigate
 to the **Cooper** root directory and install the package in development mode by running:
 
-| Setting     | Command                                  | Notes                                     |
-| ----------- | ---------------------------------------- | ----------------------------------------- |
-| Development | `pip install --editable ".[dev, tests]"` | Editable mode. Matches test environment.  |
-| Docs        | `pip install --editable ".[docs]"`       | Used to re-generate the documentation.    |
-| Tutorials   | `pip install --editable ".[examples]"`   | Install dependencies for running examples |
-| No Tests    | `pip install --editable .`               | Editable mode, without tests.             |
+| Setting     | Command                                 | Notes                                           |
+|-------------|-----------------------------------------|-------------------------------------------------|
+| No Tests    | `pip install --editable .`              | Editable mode, without tests.                   |
+| Development | `pip install --editable ".[test]"`      | Editable mode. Matches test environment.        |
+| Development | `pip install --editable ".[dev]"`       | Editable mode. Matches development environment. |
+| Tutorials   | `pip install --editable ".[notebooks]"` | Install dependencies for running notebooks.     |
+| Docs        | `pip install --editable ".[docs]"`      | Used to generate the documentation.             |
 
 ## Package structure
 
@@ -172,7 +179,7 @@ the snippet below:
 
 ```bibtex
 @misc{gallegoPosada2022cooper,
-    author={Gallego-Posada, Jose and Ramirez, Juan},
+    author={Gallego-Posada, Jose and Ramirez, Juan and Hashemizadeh, Meraj and Lacoste-Julien, Simon},
     title={Cooper: a toolkit for Lagrangian-based constrained optimization},
     howpublished={\url{https://github.com/cooper-org/cooper}},
     year={2022}

docs/source/additional_features.md

@@ -8,8 +8,6 @@ In this section we provide details on using "advanced features" such as
 alternating updates, or the Augmented Lagrangian method, in conjunction with a
 {py:class}`~cooper.optim.constrained_optimizers.ConstrainedOptimizer`.
 
-______________________________________________________________________
-
 (alternating-updates)=
 
 ## Alternating updates
@@ -25,21 +23,19 @@ variables. This two-stage process is handled by **Cooper** inside the
 
 One can perform alternating updates in which the primal parameters are updated first. We
 refer to this update strategy as `cooper.optim.AlternationType.PRIMAL_DUAL`.
-.. math:
 
-```
+$$
 x_{t+1} &= \texttt{primal_optimizers_update} \left( x_{t}, \nabla_{x} \mathcal{L}_{c_t}(x, \lambda_t)|_{x=x_t} \right)\\
 \lambda_{t+1} &= \texttt{dual_optimizer_update} \left( \lambda_{t}, {\color{red} \mathbf{-}} \nabla_{\lambda} \mathcal{L}({\color{red} x_{t+1}}, \lambda)|_{\lambda=\lambda_t} \right)
-```
+$$
 
 Alternative, `cooper.optim.AlternationType.DUAL_PRIMAL` carries out an update of the
 dual parameters first.
-.. math:
 
-```
+$$
 \lambda_{t+1} &= \texttt{dual_optimizer_update} \left( \lambda_{t}, {\color{red} \mathbf{-}} \nabla_{\lambda} \mathcal{L}({\color{red} x_{t}}, \lambda)|_{\lambda=\lambda_t} \right) \\
 x_{t+1} &= \texttt{primal_optimizers_update} \left( x_{t}, \nabla_{x} \mathcal{L}_{c_t}(x, \lambda_{t+1})|_{x=x_t} \right)
-```
+$$
 
 :::{important}
 Selecting `alternation_type=AlternationType.DualPrimal` does not double the number
@@ -57,8 +53,6 @@ allows for updating the Lagrange multiplier without having to re-evaluate
 the loss function, but rather only the constraints.
 :::
 
-______________________________________________________________________
-
 (augmented-lagrangian-const-opt)=
 
 ## Augmented Lagrangian method
@@ -172,8 +166,6 @@ for step_id in range(1000):
     coop.dual_scheduler.step()
 ```
 
-______________________________________________________________________
-
 (multiple-primal-optimizers)=
 
 # Multiple primal optimizers

docs/source/constrained_optimizer.md

@@ -211,8 +211,7 @@ will be equivalent to performing `optimizer.step()` on all of the
 primal parameters.
 :::
 
-```{eval-rst}
-.. include:: additional_features.rst
+```{include} additional_features.md
 ```
 
 ```{eval-rst}

docs/source/lagrangian_formulation.md

@@ -90,7 +90,6 @@ in Fig 1. of {cite:t}`cotter2019JMLR`.
 ```{eval-rst}
 .. autoclass:: LagrangianFormulation
     :members:
-
 ```
 
 ```{eval-rst}
@@ -144,8 +143,6 @@ in **Cooper** as a
 ```{eval-rst}
 .. autoclass:: AugmentedLagrangianFormulation
     :members:
-
-
 ```
 
 ```{eval-rst}

docs/source/notebooks/plot_mnist_logistic_regression.ipynb

@@ -136,7 +136,7 @@
     "    start_epoch = 0\n",
     "    all_metrics = defaultdict(list)\n",
     "else:\n",
-    "    checkpoint = torch.load(checkpoint_path + \"/checkpoint.pth\")\n",
+    "    checkpoint = torch.load(checkpoint_path + \"/checkpoint.pth\", weights_only=True)\n",
     "    batch_ix = checkpoint[\"batch_ix\"]\n",
     "    start_epoch = checkpoint[\"epoch\"] + 1\n",
     "    all_metrics = checkpoint[\"all_metrics\"]\n",
@@ -182,7 +182,7 @@
     "del batch_ix, all_metrics, model, cmp, cooper_optimizer\n",
     "\n",
     "# Post-training analysis and plotting\n",
-    "all_metrics = torch.load(checkpoint_path + \"/checkpoint.pth\")[\"all_metrics\"]\n",
+    "all_metrics = torch.load(checkpoint_path + \"/checkpoint.pth\", weights_only=True)[\"all_metrics\"]\n",
     "\n",
     "fig, (ax0, ax1, ax2, ax3) = plt.subplots(nrows=1, ncols=4, sharex=True, figsize=(18, 4))\n",
     "\n",

docs/source/notebooks/plot_mnist_logistic_regression.md

@@ -121,7 +121,7 @@ if not os.path.isfile(checkpoint_path + "/checkpoint.pth"):
     start_epoch = 0
     all_metrics = defaultdict(list)
 else:
-    checkpoint = torch.load(checkpoint_path + "/checkpoint.pth")
+    checkpoint = torch.load(checkpoint_path + "/checkpoint.pth", weights_only=True)
     batch_ix = checkpoint["batch_ix"]
     start_epoch = checkpoint["epoch"] + 1
     all_metrics = checkpoint["all_metrics"]
@@ -167,7 +167,7 @@ for epoch_num in range(start_epoch, 7):
 del batch_ix, all_metrics, model, cmp, cooper_optimizer
 
 # Post-training analysis and plotting
-all_metrics = torch.load(checkpoint_path + "/checkpoint.pth")["all_metrics"]
+all_metrics = torch.load(checkpoint_path + "/checkpoint.pth", weights_only=True)["all_metrics"]
 
 fig, (ax0, ax1, ax2, ax3) = plt.subplots(nrows=1, ncols=4, sharex=True, figsize=(18, 4))