tensorflow / tensorflow/java

What happened to the tensorflow.keras package?

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Dominant language
Java
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Forks
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Description

Please make sure that this is a feature request. As per our GitHub Policy, we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub. tag:feature_template

System information

  • TensorFlow version (you are using):
  • Are you willing to contribute it (Yes/No):

TF 2.3.1
Yes, if able

Describe the feature and the current behavior/state.

There used to be a separate repo tensorflow-keras. That page said the worked got merged into this. Yet, I don't see a org.tensorflow.keras package and my ide complains when I try to access stuff from it. I want to be able to, at a minimum, load models from Keras. But yes, it would also be nice to create models on the Java side as well.

Will this change the current api? How?
I suppose so because I do not see a org.tensorflow.keras package currently.

Who will benefit with this feature?
Everyone who is already familiar with Keras. But also those newer to deep learning as well because Keras is higher level and easier to use than vanilla tensorflow.

Any Other info.
If there have been massive conversations and decisions made behind the scenes, I would hope that at least the README.md is updated to say the level of support, if any, for Keras and why that decision was made so that people aren't scratching their heads.

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by reviewing the tensorflow-keras repository history and the Java API around the requested org.tensorflow.keras package. Check README.md for the current level of Keras support and determine whether the goal is model loading, Java-side model creation, or both; done should be defined as a documented support decision or a complete feature scope.

Written by the indexing model from the issue text.

Assessment

Tech stack
java, tensorflow
Domain
machine-learning
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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