KerasHub has mandatory dependency on tensorflow-text but it isn't mandatory

[jamesmyatt]

Can tensorflow-text be removed as a mandatory dependency, please? e.g. move it to an optional dependency group, e.g. "nlp"

As far as I can tell, this dependency makes it impossible to either:

• have a tensorflow-free environment
• install KerasHub at all on Windows

Both of these seem to be contrary to Keras 3's mission, especially if you only want the CV parts of KerasHub.

Furthermore, the NoTensorflow integration tests show that it's acceptable to manually uninstall tensorflow and tensorflow-text after installing keras-hub. But it's not possible to never install them in the first place.

I think this was tolerable when this package was KerasNLP (e.g. #1585, keras-team/keras#19542), but now that it's KerasHub, it's a serious issue.

[Lundez]

+1 agree

Can't install keras-hub when I have enforced tensorflow<2.18 on MacOS as tensorflow-text don't support that.
It's quite annoying as I'm using keras-hub for its CV use-case.

[abheesht17]

Thanks for bringing this up!

[jamesmyatt]

Thanks

[mattdangerw]

Shoot! I think we actually might need to roll this back. tensorflow and tensorflow-text are indeed optional at import time, but really just as a power user feature. No task will work without tensorflow installed because we currently use tf.data for all preprocessing in the library. The no-tensorflow approach only works if you want to do all preprocessing and task setup yourself (very valid to do, but not our biggest usage path).

On a clean system, if you run pip install keras-hub and then the following...

import keras_hub
classifier = keras_hub.models.ImageClassifier.from_preset(
    "resnet_50_imagenet",
)

You would now get an error saying tensorflow is required (when trying to create image preprocessing layers). That's a breaking change I don't think we want! And even more confusing that the fix is to append "nlp" to the install line.

[mattdangerw]

Instead I think we need the following for now.

1. pip install keras-hub should pull in tensorflow-text and tensorflow for now. We want a usable experience out of the box.
2. We can exclude tensorflow-text on the windows platform since tensorflow dropped support. Of course that means keras-hub is barely usable on native windows, but our recommend path for windows development is WSL.
3. For power users that know what they are doing and do not want the task API, the no tf approach will require pip install keras-hub --no-deps.

The better solution will need to be one of the following.

1. If https://peps.python.org/pep-0771/ gets approved, then pip install keras-hub can keep giving a usable out of box experience, and pip install keras-hub[base] can give the pared down installation.
2. If not, we could consider a separate package, so pip install keras-hub is what most people use, and pip install keras-hub-base gives you the pared down list of requirements.
3. Finally, and ideally, we could ditch our dependency on tensorflow for preprocessing. We would love to do this honestly, and then tensorflow could really be optional for the average user! However this is a larger undertaking.

I know this is less than ideal, but hopefully we can start making progress towards making tf.data actually optional, and till then use --no-deps as work around.

[jamesmyatt]

This disappointing. There really needs to be a version of KerasHub that doesn't have a mandatory dependency on tensorflow, for either of the reasons listed above.

Even on linux, if KerasHub has a mandatory dependency on tensorflow, then it negates any the benefit of the multi-backend capability of Keras 3. For example, do you really want to spend time coordinating which versions of tensorflow and pytorch can be installed in the same venv with the same version of cuda/nocuda and all of the other dependencies?

One interim question is whether it will work with tensorflow "core" as a mandatory (linux) dependency and tensorflow-text as an optional "nlp" dependency, if the main issue is tf.data? At least that avoids the extra complexity of the tensorflow-text project.

KerasHub (as successor to KerasCV and KerasNLP) is advertised as a replacement for the discontinued tf.addons project, and that has to be taken into account too. It's not just a Keras wrapper for third-party models. At least as I understand it.

[Lundez]

Agreed, this too me is a big problem as I'd like to use another backend for my CV project... Which is one of the major "selling-points" of Keras 3.