🚀 Contributing to Keras 🚀

[fchollet]

Keras 3 is a high-velocity open-source project. We welcome contributions! Here's what you can do:

Take up one of these items:

Here are some features that we'd love to see implemented by the Keras community:

• Add cuDNN support for PyTorch RNNs by implementing keras/backend/torch/rnn.py:cudnn_lstm and cudnn_gru.
• Add support for ONNX in model.export() and ExportArchive. On the TF and JAX side, we can transit via SavedModel. On the torch side, we can do a native export.
• Implement tool for saved Keras model file inspection, diff, and patching. It could:
  • Take a fname.keras file and display the manifest of its contents (including weights file structure)
  • Take a fname.weights.h5 and display the manifest of its content.
  • Diff two weights files, highlighting what's in one and not in the other.
  • Patch a file, by replacing a given weight with a different value provided by the user.
• Add all models from keras.applications to keras_cv.models, e.g. Xception, ConvNeXt, etc.
• Update KerasCV models to make sure they also work in channels_first mode.
• Add a new Flash Attention op, as keras.ops.nn.flash_attention. See #19418

Check out TODOs

There are various TODOs in the codebase. You can do a quick search (e.g. grep "TODO" keras/ -r) and see if anything looks interesting to you. Make sure to ask in this thread before starting work on any item!

Bring new pretrained model implementations to KerasCV and KerasNLP

The Keras ecosystem packages KerasCV and KerasNLP are looking for contributors!

If you'd like to port a pretrained model implementation to the Keras ecosystem, these packages are great projects to join.

Convert an example from keras.io to Keras 3

keras.io/examples offers many great tutorials, but many of them are still based on Keras 2. We'd like to bring over in the shiny new world of multi-framework ML.

There are two stages of conversion:

1. Converting a Keras 2 example so that it can run on Keras 3 with the TF backend.
2. Converting a Keras 2 example so that it can run on Keras 3 with any backend.

If you see an example marked as "v2" on keras.io/examples, you can open a PR on keras-team/keras-io to convert it to Keras 3. Keep in mind:

• Start by only including the Python file in the PR, not the md and ipynb files, because you may have to regenerate those after review comments come in.
• To convert the code, you can refer to the Keras 3 migration guide.

Add new examples to keras.io

Have a great ML project you'd like to use to teach others about ML? You can add a new tutorial on keras.io/examples! Just follow the instructions at keras-team/keras-io.

Increase test coverage

Keras doesn't have 100% code coverage in unit tests just yet. You can try to run a code coverage tool like codecov and see if there are any unit tests you could add to improve Keras.

[chanduvkp]

@sampathweb @fran6co - I have seen last comments on file 'keras/src/layers/preprocessing/string_lookup_test.py' . I have grep'ed for 'TODO' and list this file . I am new for Keras contrib and setup Keras in local successfully. Would any one give me insight on this file and changes needed for 'TODO' sections .

[ghsanti]

Hi @fchollet,

Is there any intention to add types (type information) to the library ?