Request for support for Protobuf Java 4.x.x (specifically 4.32.1) in TensorFlow Java
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- Langage dominant
- Java
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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
Hi Everyone 👋
I have a project where I am using a java/python hybrid of Tensorflow in a Machine Learning. My project was based on
System information
- TensorFlow version (you are using): 1.2.0-SNAPSHOT
- Are you willing to contribute it (Yes/No): No
Describe the feature and the current behavior/state.
In my project, I am working with a hybrid TensorFlow setup using both Python and Java. The Python side uses TensorFlow 2.15 and protobuf 3.20.3, while the Java side uses TensorFlow 0.5.0 and protobuf 3.21.7.
Due to a security vulnerability (CVE-2025-4565), I need to update the Python protobuf from 3.20.3 to 4.25.8. After upgrading, I encountered an intermittent issue stemming from descriptor changes between protobuf versions 3.x.x and 4.x.x. TensorFlow Python supports protobuf 4.25.8, but TensorFlow Java (1.2.0-SNAPSHOT) only supports protobuf Java 3.21.9.
Given that protobuf Java has since been updated (to version 4.32.1 as of this writing), I would like to request official support for protobuf Java 4.x.x, particularly 4.32.1, in TensorFlow Java to ensure compatibility with the updated Python side of my project.
Will this change the current api? How?
Yes, this change will require updating the dependencies in the TensorFlow Java ecosystem to include protobuf Java 4.x.x support. This update may involve changes to how descriptors and certain functions are handled, so users may need to adjust their code to accommodate those changes.
Who will benefit with this feature?
- Developers using TensorFlow in hybrid Python/Java environments.
- Developers who need to update to the latest protobuf versions for security (CVE-2025-4565) or compatibility with other libraries.
- Users facing compatibility issues due to mismatched versions of protobuf between Python and Java.
Any Other info.
The issue is critical as it directly impacts security and cross-platform compatibility. It would be beneficial if this update could be rolled into a future release of TensorFlow Java, or at least made available in a stable branch for users who rely on protobuf Java 4.x.x.
Guide de contribution
Ouvrir le guide de contribution
Par où commencer
- Lisez l'issue en entier, puis le guide de contribution du projet.
- Signalez en commentaire que vous la prenez — cela évite que deux personnes fassent le même travail.
- Forkez le dépôt et travaillez sur une branche.
- Ouvrez une pull request qui référence le numéro de l'issue.
Piste de recherche
Commencez par examiner la configuration des dépendances de TensorFlow Java et sa compatibilité avec la partie Python décrite dans l’issue. Comparez la prise en charge actuelle de protobuf Java 3.21.9 avec celle demandée pour 4.32.1, y compris le comportement lié aux descripteurs ; le travail est considéré comme terminé lorsque la compatibilité avec la configuration hybride Java/Python est documentée et fonctionnelle.
Rédigé par le modèle d'indexation à partir du texte de l'issue.
Évaluation
- Stack technique
- java, python
- Domaine
- build-system, machine-learning
- Type d'issue
- Fonctionnalité
- Difficulté
- 5/5
- Temps estimé
- Plus d'une semaine
- Activité
- À l'abandon
- Clarté
- Plutôt claire
- Accessibilité débutants
- 25/100