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CONTRIBUTING.md

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Contributing to TT-BUDA-DEMOS

Thank you for your interest in this project. We want to make contributing to this project as easy and transparent as possible.

If you are interested in making a contribution, then please familiarize yourself with our technical contribution standards as set forth in this guide.

Next, please request appropriate write permissions by opening an issue for GitHub permissions.

All contributions require:

  • an issue
    • Your issue should be filed under an appropriate project. Please file a feature support request or bug report under Issues to get help with finding an appropriate project to get a maintainer's attention.
  • a pull request (PR).
  • Your PR must be approved by appropriate reviewers.

Setting up environment

Install all dependencies listed in requirements-dev.txt and requirements.txt, and set up pre-commit hooks in a Python environment with PyBuda installed.

cd model_demos
pip install -r requirements-dev.txt
pip install -r requirements.txt
pre-commit install

Developing model_demos

Adding models

Contribute to the model demos by include Python script files under the respective model type directories in model_demos. If it's a new model architecture, please create a directory for that model. The script should be self-contained and include pre/post-processing steps.

model_demos/
├── cv_demos/
│ ├── resnet/
│ │ └── pytorch_resnet.py
│ ├── new_model_arch/
│ │ └── pytorch_new_model.py

If external dependencies are required, please add the dependencies to the requriements.txt file.

Cleaning the dev environment

make clean and make clean_tt clears out model and build artifacts. Please make sure no artifacts are being pushed.

Running pre-commit hooks

You must run hooks before you commit something.

To manually run the style formatting, run:

make style

Adding tests

For new model demos, please include a test case under tests/ with the naming format of test_[framework]_[model].py.

Also include a pytest marker for each model family and update the markers list in pyproject.toml.

For example,

tests/test_pytorch_bert.py

@pytest.mark.bert
def test_bert_masked_lm_pytorch(clear_pybuda):
    run_bert_masked_lm_pytorch()

Updating Models Table

For new model demos, please include an entry in the Models Table along with the supported hardware.

Model Weights:

In general, we avoid including files that contain data, weights, etc within the files. Instead, these should be incorporated into the model script at runtime. For a practical illustration of this approach, please refer to this example.

Contribution standards

Code reviews

We actively welcome your pull requests.

  • A PR must be opened for any code change with the following criteria:
    • Be approved, by a maintaining team member and any codeowners whose modules are relevant for the PR.
    • Run pre-commit hooks.
    • Pass any acceptance criteria mandated in the original issue.
    • Pass automated github actions worksflow test
    • Pass any testing criteria mandated by codeowners whose modules are relevant for the PR.

For more information on the GitHub Actions and Pull Request Workflow, please see the GitHub Actions and Pull Request Workflow section within the document.

GitHub Actions and Pull Request Workflow

Automated Linting with GitHub Actions

Linting, styling, and cleaning checks are automatically performed on pull requests using GitHub Actions. This ensures that contributed code meets standard Python coding standards before it's merged into the main branch.

  1. Pull Request Process: When you open a pull request, GitHub Actions will automatically trigger linting, styling, and cleaning checks on the changes made within the model_demos directory.

  2. Approval Requirement: In order to merge a pull request, it must pass the GitHub Actions workflow test. This ensures that all contributions adhere to our coding standards and maintain consistency throughout our tt-buda-demos repository.

  3. Interpreting Results: If linting fails on your pull request, review the output to identify and fix any issues. You'll need to address these issues before the pull request can be approved and merged. In case of repeated failures or failures within the GitHub Actions workflow files, please reach out to one of the repository maintainers from the Maintainers.md.

Automated Commit by GitHub Actions

The GitHub Actions workflow also automatically makes a commit with the message *** AUTOMATED COMMIT | Applied Code Formatting and Cleanup ✨ 🍰 ✨*** authored by [anirudTT] when it performs code formatting and cleanup. If you open a pull request and subsequently push more changes, we suggest rebasing or pulling again from the pull request branch before pushing your changes again to avoid conflicts.