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🚀 Contributing to Keras 🚀 #18442
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Taking up the Moving Dataset utils task as a priority! Should I make a draft PR? |
No need for a draft -- you can just send the PR when you have something you want a review on. Thank you! |
@fchollet regarding dataset utils, since all three frameworks since in first option we import framework specific modules and built on top but these will stay in @suvadityamuk can please also share your thoughts in which direction you are choosing. 😊 |
I'm currently looking into trying to move the |
@suvadityamuk Thanks for responding, since this will be a big change let's track it in a new issue with specific changes needed to be done since even in |
Hello, |
Yes, that's right. The public API is programmatically generated using those decorators. |
Can someone help me with keras_core/layers/layer.py:439: # TODO: handle layout.What does it mean to handle the layout? |
@fchollet bump |
This was referring to the implementation of a future distribution API -- but this has been handled since. Nothing to do here. |
Hi, I am willing to take a shot at the solve operation implementation, still setting up a development environment. One clarification question. What is the error value for a matrix input that is singular (i.e., no inverse matrix exists), not full rank, or not square? To be sure, I look forward to contributing as a hobby and will circle back when I have something satisfactory for review. Thanks, |
Hello @fchollet, I wanted to reach out and update you on the progress I've made with the ERF function. I've made significant changes to the code and have already uploaded them to my forked repository. I'm confident that these updates will improve the function's performance, but please take a look and let me know if there's anything else you'd like me to do. 1.) Changes to keras-core/ops/math.py 2.) Changes to keras-core/ops/math_test.py 3.) Changes to keras-core/backend/tensorflow/math.py |
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It will also need to be implemented for the JAX, torch, and numpy backends. Can you open a PR? We can carry on on the PR. |
Sure, I will do that. Thanks. |
@fchollet ,I was trying to port this example of mixup augmentation https://keras.io/examples/vision/mixup/, while defining Hyperparameters in keras-core, what should we replace this line with AUTO = tf.data.AUTOTUNE? Could you please help clarify the same. |
@fchollet I am interested in solving the todo, can you give me more detail of how it should be done. |
Hi, @fchollet , For my first commit to Keras, I picked a simple one, addressing two small TODO items in reduction_metrics_test.py. Here's the PR: #18812 I believe what the comment "# TODO: Check save and restore config" meant is that an object (Sum or Mean) must be re-constructed from config, and be tested. Please let me know if I misunderstood the requirements, or otherwise made any mistakes. Thank you! I'm very excited about working on this very important library. |
Is anyone working on JAX CTC? If not, I can take it up |
I will take the ops.correlate if nobody is working on it. |
@fchollet I could take dice loss if nobody else is working on it. @vulkomilev did you start with ops.correlate? |
@fchollet can you or someone add me as a contributor? I need to make a push to the remote branch for the dice loss. |
@fchollet I have the first version of the DiceLoss in the tf backend. I need to be made a contributor to make a push to the remote branch so that the code review can take place. |
@fchollet any updates for the DiceLoss? I have the TF implementation ready. |
yes I did |
@vulkomilev Thanks for the answer. Are you a contributor? How do you do the push to the branch? I have this dice loss done, but cannot push since I am not a contributor. |
Please Can I have a french version !? |
@fchollet Hi, I think I invented something interesting. I implemented it in pytorch and I opened an issue there. |
you make a MR and waiting for approval |
@vulkomilev I cannot push. I don't have the rights. |
sorry I meant pull request |
Hello @fchollet, |
I will get the "Add a new Flash Attention op" task |
@fchollet for every back-end I must introduce the implementation mentioned in the ticket right ? |
@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 . |
Hi @fchollet, Is there any intention to add types (type information) to the library ? |
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:
keras/backend/torch/rnn.py:cudnn_lstm
andcudnn_gru
.model.export()
andExportArchive
. On the TF and JAX side, we can transit viaSavedModel
. On the torch side, we can do a native export.mlx
branch on the repo, which does not yet have full operation converge inkeras/src/backend/mlx/
. Add missing ops and help get the new MLX backend closer to the finish line!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 KerasHub
The Keras ecosystem package KerasHub is looking for contributors!
If you'd like to port a pretrained model implementation to the Keras ecosystem, that's a great project 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:
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:
md
andipynb
files, because you may have to regenerate those after review comments come in.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.The text was updated successfully, but these errors were encountered: