Update requirements.txt

[beliaev-maksim]

Hi KF team,
there was a PR #6755 which broke import of tf.keras

the issue is following:
if you have TF==2.9.3 then it requires keras>2.9
if you pin keras to 2.4.3, then it gets deleted and notebooks based on jupyter-tensorflow-full image will not be able to run notebooks where keras is imported

overall, new tensorflow versions come with supported version of keras via dependency, thus, pinning it in another file is dangerous.
also, keras as standalone module is deprecated and the migration path is to use tf.keras

It for sure should be deleted in components/example-notebook-servers/jupyter-tensorflow-full/requirements.txt

the simplest way to check:

python3 -m venv venv_tf
source venv_tf/bin/activate
pip install tensorflow==2.9.3
pip install keras==2.4.3
python -c "import tensorflow.keras"

while the same code without pinning (allowing pip to resolve dependency) works:

python3 -m venv venv_tf
source venv_tf/bin/activate
pip install tensorflow==2.9.3
python -c "import tensorflow.keras"

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[kimwnasptd]

Nice catch @beliaev-maksim!

What worries me is that we don't have a way for catching such conflicts right now. Do you have any suggestions on how to automatically catch these in the future?

/lgtm
/approve

[kimwnasptd]

Let me create an issue to discuss, maybe other people in the community have some feedback as well

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[beliaev-maksim]

@kimwnasptd the first thing that comes into mind is an integration test on the image
however, during docker build stage we can check for the error from pip

another thing is that we can build all the images independently. It will be a bit more work on syncing, but ensure integrity.

I think it is a good idea to open an issue for the broader discussion and community involvement :) I assume we are not the first who solves this issue ;)