TrenTorch
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Contributing

TrenTorch is an educational framework: every contribution should make a concept clearer, preserve the learning progression, or make the systems-thinking angle (memory, performance, scaling) sharper, without adding production complexity that doesn't teach anything.

Setting up a dev environment

# macOS / Linux
git clone https://github.com/TrenTorch/TrenTorch.git
cd TrenTorch

python3 -m venv .venv
source .venv/bin/activate

pip install -r requirements.txt
pip install -e .

tren --version
tren system health

# Windows (PowerShell)
git clone https://github.com/TrenTorch/TrenTorch.git
cd TrenTorch

python -m venv .venv
.venv\Scripts\Activate.ps1

pip install -r requirements.txt
pip install -e .

tren --version
tren system health

See Getting Started for the full walkthrough if you're new to the CLI itself.

Where things live

  • Curriculum content: data/src/NN_name/NN_name.py. This is what a module actually teaches; edit here, not in a generated notebook.
  • Milestone scripts: data/milestones/
  • The CLI: platforms/cli/ (cli_platform/ for setup and dev/CI tooling, processes/ for the student-facing workflow)
  • Tests: module-level tests sit next to their module (data/src/NN_name/tests/); cross-module and CLI tests live under tests/ and platforms/cli/tests/

Before you push

tren dev test --unit               # fast: your module's own tests
tren dev test --integration        # cross-module checks
tren dev preflight --full          # broader pre-release verification

The full CI suite (.github/workflows/validate.yml) runs all of this and more on every push; see Architecture for what each stage checks. It's fast (well under 4 minutes end to end as of the last optimization pass), so there's little reason not to let it run rather than trying to fully replicate it locally.

Types of contributions

  • Module fixes: bugs in an implementation, clearer explanations, better examples
  • Testing: edge cases, checkpoint validation, fixing a flaky test
  • Documentation: clearer module write-ups, better systems-insight sections
  • CI/tooling: the CLI itself, the pipeline, dev scripts

A note on scope

This is a solo/small-team fork with its own conventions (see docs/design.md for what was deliberately removed from upstream: no grading pipeline, no multi-cloud notebook targets, no community backend). If you're used to the upstream TinyTorch project's contribution process, check docs/CONTRIBUTING.md and docs/design.md in this repo first, some of it has diverged.

Questions

Open an issue, or check docs/; most "how does X actually work" questions are already answered there in more depth than fits here.