Skip to content

Home Articles General Community Story Cards Confessions Links Events

More

News Training Technologies Members

Log in Join usJoin ReadMeFeed↗

Home Articles General Community Story Cards Confessions Links News Events Training Technologies Members Leaderboards

Loading…

Shared knowledge. Real progress.
A home for the people building what comes next.

Explore

Articles
General
Community
Search

Community

Members
Leaderboards
Achievements
Community guidelines

The essentials

About ReadMeFeed
Privacy
Terms of use
Moderation policy

© 2026 ReadMeFeed. Built for the next conversation.Built by curiosity. Powered by people.

Home Community Create Inbox Profile

ReadMeFeed / Community knowledge

#jax

Real questions. Useful conversations. Find the people who know your stack.

All Unanswered Has answers Resolved Unresolved

Cards Compact list

Editorial question28.9K views2,965 votes0 answers3,589 following

AI-generated

Keras 3 backend-agnostic custom gradient parity

Custom Gradient Consistency Across Backends Keras 3 enables a unified API that allows models to execute on TensorFlow, PyTorch, or JAX by setting the KERAS_BACKEND environment variable. While standard layers are mapped to framework primitives, implementing custom gradient calculations for user-defined layers introduces potential behavioral discrepancies. The

kerasTasadduq Burneyowner26.5K rep · 25 Jul 2020, 05:03 UTC