Keras 3.12.4 Keras 3.12.4 is a security patch release that hardens dataset loading and model file handling against insecure deserialization and decompression-bomb attacks. Security Fixes Restrict unpickling when loading IMDB and Reuters datasets — Replaces np.load(allow_pickle=True) with a restricted unpickler that only permits numpy array reconstruction, preventing arbitrary code execution via cr…
Release Notes Keras 3.15.1 is a patch release containing important security hardening, bug fixes, and Python 3.14 compatibility improvements. Security Fixes Restrict unpickling when loading IMDB and Reuters datasets — Prevents insecure deserialization (CWE-502) by replacing bare np.load(allow_pickle=True) with a restricted unpickler that only permits numpy array reconstruction. (#23047) by @LinZiy…
Keras 3.12.3 is a security patch release that hardens model saving, loading, and deserialization against a range of attack vectors. HDF5 Hardening Eject ExternalLink/SoftLink groups in KerasFileEditor (#22899) Prevents HDF5 external/soft links from being exploited to read arbitrary files during model editing. Reject ExternalLink/SoftLink on legacy .h5 dispatcher (#22900) Extends HDF5 link rejectio…
Highlights Keras-to-Torch Export: New export_torch enables exporting Keras models to native PyTorch nn.Module format, along with LiteRT (TFLite) export support for the PyTorch backend. Sliding Window Attention: Added sliding_window parameter to MultiHeadAttention and GroupedQueryAttention for efficient long-context attention. Flash / Fused SDPA: Causal-only MHA/GQA now automatically dispatches to…
Saving & Reloading Harden path and link resolution when extracting files from archives (#22839) Fixed link resolution bug when validating links extracted from TAR archives. Fixed path confusion bug when validating files extracted from ZIP and TAR archives (including .keras files). Added path validation when extracting assets from Orbax checkpoints. Harden H5 validation code and apply it to legacy…
Saving & Reloading Harden path and link resolution when extracting files from archives (#22194 & #22839) Fixed based folder used when validating files extracted from ZIP and TAR archives. Fixed link resolution bug when validating links extracted from TAR archives. Fixed path confusion bug when validating files extracted from ZIP and TAR archives (including .keras files). Added path validation when…
Highlights Orbax Checkpoint Integration: Full support for Orbax checkpoints, including sharding, remote paths, and step recovery. Quantization Upgrades: Added support for Activation-aware Weight Quantization (AWQ) and Asymmetric INT4 Sub-Channel Quantization. Batch Renormalization in BatchNorm: Added batch renormalization feature to the BatchRenormalization layer. New Optimizer: Added ScheduleFree…
Security Fixes & Hardening This release introduces critical security hardening for model loading and saving, alongside improvements to the JAX backend metadata handling. Disallow TFSMLayer deserialization in safe_mode (#22035) Previously, TFSMLayer could load external TensorFlow SavedModels during deserialization without respecting Keras safe_mode. This could allow the execution of attacker-contro…
Security Fixes & Hardening This release introduces critical security hardening for model loading and saving, alongside improvements to the JAX backend metadata handling. Disallow TFSMLayer deserialization in safe_mode (#22035) Previously, TFSMLayer could load external TensorFlow SavedModels during deserialization without respecting Keras safe_mode. This could allow the execution of attacker-contro…
Bug Fixes & Improvements General Removed a persistent warning triggered during import keras when using NumPy 2.0 or higher. (#21949) Backends JAX: Fixed an issue where CUDNN flash attention was broken when using JAX versions greater than 0.6.2. (#21970) Export & Serialization Resolved a regression in the export pipeline that incorrectly forced batch sizes to be dynamic. The export process now corr…
BREAKING changes Starting with version 3.13.0, Keras now requires Python 3.11 or higher. Please ensure your environment is updated to Python 3.11+ to install the latest version. Highlights LiteRT Export You can now export Keras models directly to the LiteRT format (formerly TensorFlow Lite) for on-device inference. This changes comes with improvements to input signature handling and export utility…
Highlights Keras has a new model distillation API! You now have access to an easy-to-use API for distilling large models into small models while minimizing performance drop on a reference dataset -- compatible with all existing Keras models. You can specify a range of different distillation losses, or create your own losses. The API supports multiple concurrent distillation losses at the same time…