Add inverse sqrt learning rate scheduler
Author: Sager611
Pull request: yes

# What does this PR do?

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Adds the original invserse sqrt learning rate scheduler from [Vaswani et al. (2017)](https://arxiv.org/abs/1706.03762).

It is argued that this scheduler achieves the best performance when scaling ViTs on indefinite training times ([Zhai et al. (2022)](https://arxiv.org/abs/2106.04560)).

This PR ads a `get_inverse_sqrt_schedule` function and also updates the test in `tests/optimization/test_optimization.py` and the docs.

The implementation is adapted from:

- [https://github.com/google-research/big_vision/blob/f071ce68852d56099437004fd70057597a95f6ef/big_vision/utils.py#L930](https://github.com/google-research/big_vision/blob/f071ce68852d56099437004fd70057597a95f6ef/big_vision/utils.py#L930)

Timescale equals the no. of warmup steps by default as in:

- [https://github.com/google-research/big_vision/blob/fd2d3bd2efc9d89ea959f16cd2f58ae8a495cd44/big_vision/configs/proj/clippo/train_clippo.py#L144](https://github.com/google-research/big_vision/blob/fd2d3bd2efc9d89ea959f16cd2f58ae8a495cd44/big_vision/configs/proj/clippo/train_clippo.py#L144)
- [https://github.com/google-research/big_vision/blob/6ff6d080d62c1f47e2e4eeb8b6474deb38dfe406/big_vision/configs/proj/scaling_laws/train_vit_g.py#L79](https://github.com/google-research/big_vision/blob/6ff6d080d62c1f47e2e4eeb8b6474deb38dfe406/big_vision/configs/proj/scaling_laws/train_vit_g.py#L79)

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