September 21, 2026 · LayerGenius
Keras 3 can quantize a model's weights in place with model.quantize("int8") — no converter, no second toolchain. What it touches, what it skips, how to measure the accuracy cost, and when GPTQ or a calibration pass is worth the trouble.
Read moreSeptember 18, 2026 · LayerGenius
Overriding train_step used to mean a GradientTape. In Keras 3 each backend wants a different shape of code — stateless in JAX, autograd in PyTorch, tape in TensorFlow. How to write it, and how to keep it portable.
Read moreSeptember 14, 2026
Keras 3 runs the same model on three backends, but the right one is a measurement, not an opinion. A harness that compares step time, memory, and convergence honestly — plus the constraints that usually decide it before the numbers do.
Read moreMay 12, 2026
Most model definitions port to Keras 3 with minor edits — the pain concentrates in custom ops, keras.backend usage, serialization, and training loops. A field checklist for the migration.
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