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Fix typo in average optimizers callback (#2692)
Apr 12, 2022
a0b6ecb · Apr 12, 2022

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README.md
README.md
Oct 14, 2019
_template.ipynb
_template.ipynb
Sep 11, 2020
_toc.yaml
_toc.yaml
Jun 5, 2021
average_optimizers_callback.ipynb
average_optimizers_callback.ipynb
Apr 12, 2022
image_ops.ipynb
image_ops.ipynb
Sep 11, 2020
layers_normalizations.ipynb
layers_normalizations.ipynb
Nov 16, 2021
layers_weightnormalization.ipynb
layers_weightnormalization.ipynb
Sep 11, 2020
losses_triplet.ipynb
losses_triplet.ipynb
Sep 11, 2020
networks_seq2seq_nmt.ipynb
networks_seq2seq_nmt.ipynb
May 13, 2021
optimizers_conditionalgradient.ipynb
optimizers_conditionalgradient.ipynb
Sep 11, 2020
optimizers_cyclicallearningrate.ipynb
optimizers_cyclicallearningrate.ipynb
Sep 15, 2021
optimizers_lazyadam.ipynb
optimizers_lazyadam.ipynb
Sep 9, 2020
time_stopping.ipynb
time_stopping.ipynb
Sep 9, 2020
tqdm_progress_bar.ipynb
tqdm_progress_bar.ipynb
Sep 9, 2020

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