OpenNMT-py is a community developed project and we love developer contributions.


Before sending a PR, please do this checklist first:

  • Please run onmt/tests/ and fix any errors. When adding new functionality, also add tests to this script. Included checks:

    1. flake8 check for coding style;

    2. unittest;

    3. continuous integration tests listed in .travis.yml.

  • When adding/modifying class constructor, please make the arguments as same naming style as its superclass in PyTorch.

  • If your change is based on a paper, please include a clear comment and reference in the code (more on that below).


Above all, try to follow the Google docstring format (Napoleon example, Google styleguide). This makes it easy to include your contributions in the Sphinx documentation. And, do feel free to autodoc your contributions in the API .rst files in the docs/source folder! If you do, check that your additions look right.

How to build the docs locally?

cd docs
# install some dependencies if necessary:
# recommonmark, sphinx_rtd_theme, sphinxcontrib-bibtex
pip install requirements.txt
make html
firefox build/html/main.html  # or your browser of choice

Some particular advice:

  • Try to follow Python 3 typing module conventions when documenting types.

    • Exception: use “or” instead of unions for more readability

    • For external types, use the full “import name”. Common abbreviations (e.g. np) are acceptable. For torch.Tensor types, the torch. is optional.

    • Please don’t use tics like (`str`) or rst directives like (:obj:`str`). Napoleon handles types very well without additional help, so avoid the clutter.

  • Google docstrings don’t support multiple returns. For multiple returns, the following works well with Sphinx and is still very readable.

    def foo(a, b):
        """This is my docstring.
            a (object): Something.
            b (class): Another thing.
            (object, class):
            * a: Something or rather with a long
              description that spills over.
            * b: And another thing.
        return a, b
  • When citing a paper, avoid directly linking in the docstring! Add a Bibtex entry to docs/source/refs.bib. E.g., to cite “Attention Is All You Need”, visit arXiv, choose the bibtext link, search docs/source/refs.bib using CTRL-F for DBLP:journals/corr/VaswaniSPUJGKP17, and if you do not find it then copy-paste the citation into refs.bib. Then, in your docstring, use :cite:`DBLP:journals/corr/VaswaniSPUJGKP17` .

    • However, a link is better than nothing.

  • Please document tensor shapes. Prefer the format ``(a, b, c)``. This style is easy to read, allows using x for multplication, and is common (PyTorch uses a few variations on the parentheses format, AllenNLP uses exactly this format, Fairseq uses the parentheses format with single ticks).

    • Again, a different style is better than no shape documentation.

  • Please avoid unnecessary space characters, try to capitalize, and try to punctuate.

    For multi-line docstrings, add a blank line after the closing """. Don’t use a blank line before the closing quotes.

    """ not this """ """This."""

        Not this.

    This note is the least important. Focus on content first, but remember that consistent docs look good.

  • Be sensible about the first line. Generally, one stand-alone summary line (per the Google guidelines) is good. Sometimes, it’s better to cut directly to the args or an extended description. It’s always acceptable to have a “trailing” citation.