2 ms·
This looks really cool, and it's good to see Keras come full circle back to being an ergonomic interface with support for multiple frameworks. I remember being
by hedgehog 3y ago
This looks really cool, and it's good to see Keras come full circle back to being an ergonomic interface with support for multiple frameworks. I remember being pretty disappointed when pluggable back ends went away. I appreciate that in the NLP module there is the most humane and concise LORA implementation I'm aware of. The ability to embed Keras components into models using other frameworks is pretty key.
Question: What's the model export story? If I want to export for CoreML or use the new PyTorch model compilation is there a straight forward way to do that?
- kerasteam 3y agoThanks! Hope you'll find the new Keras useful! So far the export story focuses on SavedModel and the services that consume that format, e.g. TFLite, TFjs and TFServing. You can just do `model.export(path)`, and you also have access to the `ExportArchive` class for fine-grained configuration. We have not tried CoreML export yet. PyTorch `.compile()` works with Keras models. It may not necessarily result in a speedup however.