Installing L5Kit

Installing as a User

Follow this workflow if:

  • you’re not interested in developing and/or contributing to L5Kit;

  • you don’t need any features from a specific branch or latest master and you’re fine with the latest release;

1. Install the package from pypy (in your project venv)

pip install l5kit

You should now be able to import from L5Kit (e.g. from l5kit.data import ChunkedDataset should work)

2. Run example

Examples are not shipped with the package, but you can download the zip release from: L5Kit Releases

Please download the zip matching your installed version (you can run pip freeze | grep l5kit to get the right version) Unzip the files and grab the example folder in the root of the project.

jupyter notebook examples/visualisation/visualise_data.ipynb

Installing as a Developer

Follow this workflow if:

  • you want to test latest master or another branch;

  • you want to contribute to L5Kit;

  • you want to test the examples using a non-release version of the code;

1. Clone the repo

git clone https://github.com/lyft/l5kit.git
cd l5kit/l5kit

Please note the double l5kit in the path, as we need to cd where setup.py file is.

2. Install L5Kit

2.1 Deterministic Build (Suggested)

We support deterministic build through pipenv.

Once you’ve installed pipenv (or made it available in your env) run:

pipenv sync --dev

This will install all dependencies (--dev includes dev-packages too) from the lock file.

2.2 Latest Build

If you don’t care about determinist builds or you’re having troubles with packages resolution (Windows, Python<3.7, etc..), you can install directly from the setup.py by running:

pip install -e ."[dev]"

If you run into trouble installing L5Kit on Windows, you may need to

  • install Pytorch and torchvision manually first (select the correct version required by your system, i.e. GPU or CPU-only), then run L5Kit install (remove the packages torch and torchvision from setup.py)

  • install Microsoft C++ Build Tools.

3. Generate L5Kit code html documentation (optional)

sphinx-apidoc --module-first --separate -o docs/API/ l5kit/l5kit l5kit/l5kit/tests*
sphinx-build docs docs_built

4. Run example

jupyter notebook examples/visualisation/visualise_data.ipynb