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Francois from the Keras team here -- happy to answer questions!

daturkel 3y ago
Hey Francois, congrats to you and the team on the launch! I've generally chosen Pytorch over Tensorflow for my day to day, but now that Keras is framework agnostic I'm excited to revisit it. One thing I'm wondering about is if it's possible (or necessary?) to use Keras in concert with Pytorch Lightning. In some ways, Lightning evolved to be "Keras for Pytorch," so what is the path forward in a world where both exist as options for Pytorch users—do they interoperate or are they competitors/alternatives to each other?
- kerasteam 3y ago
  Both Keras models/layers (with the PyTorch backend) and Lightning Modules are PyTorch Modules, so they should be able to interoperate with each other in a PyTorch workflow. We have not tried this with Lightning, but we've had a good experience with custom PyTorch Modules. More broadly, it's feasible to use Keras components with any framework built on PyTorch or JAX in the sense that it's always possible to write "adapter layers" that wrap a Keras layer and make it usable by another framework, or the other way around. We have folks doing this to use Flax components (from JAX) as Keras layers, and inversely, to use Keras layers as Flax Modules.
minihat 3y ago
Any chance a keras.linalg suite of ops is in the works? Cross-platform differences between the behavior of tf.linalg and torch.linalg have cost me a lot of time over the years.
- kerasteam 3y ago
  We don't have a separate `ops.linalg` package, but we do include `numpy.linalg` ops as part of `keras.ops`. For now only 2 ops are supported: `qr` and `solve`. We're open to adding any `numpy.linalg` op that turns out to be useful (or you could open a PR for any op you need).
srvmshr 3y ago
Hi Francois, will there be breaking changes between 2.0 & 3.0 API
- kerasteam 3y ago
  All breaking changes are listed here: https://github.com/keras-team/keras/issues/18467 https://github.com/keras-team/keras/issues/18467 You can use this migration guide to identify and fix each of these issues (and further, making your code run on JAX or PyTorch): https://keras.io/guides/migrating_to_keras_3/ https://keras.io/guides/migrating_to_keras_3/
revskill 3y ago
You're my favorite Python developer. Very intuitive API design.
dave_sullivan 3y ago
Congrats on the release!
__rito__ 3y ago
How much focus was there in the direction of TFLite? Were any improvements made?
- kerasteam 3y ago
  We made sure that TFLite workflows would run smoothly with Keras 3 models. We did not come up with any TFLite related improvements. The focus was on the multi-backend architecture, distribution, and training performance.
  - __rito__ 3y ago
    Thanks for info. I hugely rely on TFLite for a bunch of hobby projects.
esafak 3y ago
What is Keras 3.0 (not) ideal for? Why not use pyTorch or Flax?

Hey Francois, congrats to you and the team on the launch! I've generally chosen Pytorch over Tensorflow for my day to day, but now that Keras is framework agnostic I'm excited to revisit it. One thing I'm wondering about is if it's possible (or necessary?) to use Keras in concert with Pytorch Lightning. In some ways, Lightning evolved to be "Keras for Pytorch," so what is the path forward in a world where both exist as options for Pytorch users—do they interoperate or are they competitors/alternatives to each other?

kerasteam 3y ago
Both Keras models/layers (with the PyTorch backend) and Lightning Modules are PyTorch Modules, so they should be able to interoperate with each other in a PyTorch workflow. We have not tried this with Lightning, but we've had a good experience with custom PyTorch Modules. More broadly, it's feasible to use Keras components with any framework built on PyTorch or JAX in the sense that it's always possible to write "adapter layers" that wrap a Keras layer and make it usable by another framework, or the other way around. We have folks doing this to use Flax components (from JAX) as Keras layers, and inversely, to use Keras layers as Flax Modules.

minihat 3y ago

Any chance a keras.linalg suite of ops is in the works? Cross-platform differences between the behavior of tf.linalg and torch.linalg have cost me a lot of time over the years.

kerasteam 3y ago
We don't have a separate `ops.linalg` package, but we do include `numpy.linalg` ops as part of `keras.ops`. For now only 2 ops are supported: `qr` and `solve`. We're open to adding any `numpy.linalg` op that turns out to be useful (or you could open a PR for any op you need).

srvmshr 3y ago

Hi Francois, will there be breaking changes between 2.0 & 3.0 API

kerasteam 3y ago
All breaking changes are listed here: https://github.com/keras-team/keras/issues/18467 https://github.com/keras-team/keras/issues/18467 You can use this migration guide to identify and fix each of these issues (and further, making your code run on JAX or PyTorch): https://keras.io/guides/migrating_to_keras_3/ https://keras.io/guides/migrating_to_keras_3/

revskill 3y ago

You're my favorite Python developer. Very intuitive API design.

dave_sullivan 3y ago

Congrats on the release!

__rito__ 3y ago

How much focus was there in the direction of TFLite? Were any improvements made?

kerasteam 3y ago
We made sure that TFLite workflows would run smoothly with Keras 3 models. We did not come up with any TFLite related improvements. The focus was on the multi-backend architecture, distribution, and training performance.
- __rito__ 3y ago
  Thanks for info. I hugely rely on TFLite for a bunch of hobby projects.

esafak 3y ago

What is Keras 3.0 (not) ideal for? Why not use pyTorch or Flax?