addons/docs/tutorials
..
README.md
_template.ipynb
_toc.yaml
average_optimizers_callback.ipynb
image_ops.ipynb
layers_normalizations.ipynb
layers_weightnormalization.ipynb
losses_triplet.ipynb
networks_seq2seq_nmt.ipynb
optimizers_conditionalgradient.ipynb
optimizers_cyclicallearningrate.ipynb
optimizers_lazyadam.ipynb
time_stopping.ipynb
tqdm_progress_bar.ipynb

README.md

TensorFlow Addons Tutorials

TensorFlow Addons welcomes and highly encourages tutorial contributions.

How To Contribute

Addons tutorials are created using Google Colab and the jupyter notebooks are saved to this directory in the repository. To do this, follow the below steps:

  1. Create a new branch on your fork of TensorFlow Addons
  2. Goto Google Colab and start a new notebook using addons example template: docs/tutorials/_template.ipynb
  3. Edit the links for the "View source on GitHub" and "Run in Google Colab" URL boxes so that they match the name of your new example notebook
  4. Follow the guidelines of the template
  5. "Save a copy in GitHub" and select your new branch. The notebook should be named subpackage_submodule
  6. Submit the branch as a PR on the TF-Addons GitHub