Upgrade TensorFlow newer version on both GPU and TPU.

RE-POST on Kaggle.

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I’m not sure if this is the right place to ask, if it’s not then please redirect.

🚀 Feature

Here are the two requests

1. Upgrade TensorFlow Version same as the Colab.
2. Upgrade TensorFlow Version for both GPU and TPU

Motivation

About (1), while doing an experiment on the kaggle environment, it’s known that users usually switch between kaggle and colab. Now, when TensorFlow teams release a newer version of TensorFlow, it immediately upgrades Colab but the process on Kaggle is too slow. And that creates some problems on a mismatch with the newer feature, mostly with tensorflow.experimental.* with tensorflow.<something_stable> for example. So, by ensuring the newer version on the Kaggle environment along with the Colab, it surely gonna be great to the end sure.

About (2), same as the no. 1; currently kaggle upgrades TensorFlow v. 2.6 for GPU but for TPU, it uses 2.4.1. The newer version provides more features. The problem is, if a user uses those new features on GPU (tf v. 2.6), he/she can’t use them on TPU (tf v.2.4) for the comparatively older tensorflow versions.

Additional context

I understand it may be complicated on that side to maintain. But please consider the above issues in the best way possible.

[darien-schettler]

@Philmod - If you want this to be the main thread for grief related to the environments that’s fine… but in that case, it probably shouldn’t have been abandoned for 3 months.

Either reopen the other issue or start making progress on this one. Please.

[innat]

@rosbo Thanks for the response. Please note, it’s not about TensorFlow version 2.7. The issues are described in detail above. In short,

• always ensuring the latest tensorflow version
• tensorflow version consistency between GPU and TPU.