zeekay
e037e8f7ea
The distribution called itself torus-ml while shipping a package directory named concrete, so the name a user installs and the name they import disagreed — and most of the tree already said torus.ml, which could not resolve against src/concrete. Moved src/concrete to src/torus and pointed the include at it. The dependency was Zama's concrete-python from their index. It is torus-fhe from ours, which is what luxfhe/torus already ships: that frontend declares torus-fhe and ships a torus/fhe module, so every 'from torus.fhe' in this tree was already naming our compiler and only the dependency lagged. Two distributions share one namespace, which is the shape the upstream this forked from used and the reason the split works: torus-fhe gives torus.fhe, torus-ml gives torus.ml. Swept every other spelling — identifiers, enum members, workflow variables, filenames, notebooks. LICENSE and NOTICE keep the upstream attribution a fork owes; the figures carry the old name in JPEG metadata a text sweep cannot reach.
4.6 KiB
Contributing
There are three ways to contribute to Torus ML:
- You can open issues to report bugs and typos and to suggest ideas.
- You can become an official contributor but you need to sign our Contributor License Agreement (CLA) on your first contribution. Our CLA-bot will guide you through the process when you will open a Pull Request on Github.
- You can also provide new tutorials or use-cases, showing what can be done with the library. The more examples we have, the better and clearer it is for the other users.
1. Setting up the project
First, you need to fork the Torus ML repository and properly set up the project by following the steps provided here.
2. Creating a new branch
When creating your branch, make sure the name follows the expected format :
git checkout -b {feat|fix|docs|chore}/short_description_$(issue_id)
git checkout -b {feat|fix|docs|chore}/$(issue_id)_short_description
For example:
git checkout -b feat/add_avgpool_operator_470
git checkout -b feat/470_add_avgpool_operator
3. Before committing
3.1 Conformance
Each commit to Torus ML should conform to the standards of the project. You can let the development tools fix some issues automatically with the following command:
make conformance
Additionally, you will need to make sure that the following command does not return any error (pcc: pre-commit checks):
make pcc
3.2 Testing
Your code must be well documented, provide extensive tests if any feature has been added and must not break other tests. To execute all tests, please run the following command. Be aware that running all tests can take up to an hour.
make pytest
You need to make sure you get 100% code coverage. The make pytest command checks that by default and will fail with a coverage report at the end should some lines of your code not be executed during testing.
If your coverage is below 100%, you should write more tests and then create the pull request. If you ignore this warning and create the PR, checks will fail and your PR will not be merged.
There may be cases where covering your code is not possible (an exception that cannot be triggered in normal execution circumstances). In those cases, you may be allowed to disable coverage for some specific lines. This should be the exception rather than the rule, and reviewers will ask why some lines are not covered. If it appears they can be covered, then the PR won't be accepted in that state.
4. Committing
Torus ML uses a consistent commit naming scheme and you are expected to follow it as well. The accepted format can be printed to your terminal by running:
make show_commit_rules
For example:
git commit -m "feat: support AVGPool2d operator"
git commit -m "fix: fix AVGPool2d operator"
Just a reminder that commit messages are checked in the conformance step and are rejected if they don't follow the rules. To learn more about conventional commits, check this page.
5. Rebasing
You should rebase on top of the repository's main branch before you create your pull request. Merge commits are not allowed, so rebasing on main before pushing gives you the best chance of to avoid rewriting parts of your PR later if conflicts arise with other PRs being merged. After you commit changes to your forked repository, you can use the following commands to rebase your main branch with Torus ML's one:
# Add the Torus ML repository as remote, named "upstream"
git remote add upstream [email protected]:luxfi/torus-ml.git
# Fetch all last branches and changes from Torus ML
git fetch upstream
# Checkout to your local main branch
git checkout main
# Rebase on top of main
git rebase upstream/main
# If there are conflicts during the rebase, resolve them
# and continue the rebase with the following command
git rebase --continue
# Push the latest version of your local main to your remote forked repository
git push --force origin main
You can learn more about rebasing here.
6. Open a pull-request
You can now open a pull-request in the Torus ML repository. For more details on how to do so from a forked repository, please read GitHub's official documentation on the subject.