Add Optimization Cookbook

[samanklesaria]

What does this PR do?

This PR adds a guide that shows some common techniques for working with Flax models during optimization. These include:

• Calculation of Exponential Moving Averages
• Optimizing only a low rank addition to certain weights (LORA)
• Using different learning rates for different parameters to implement the maximal update parameterization
• Using second order optimizers like LBFGS.
• Specifying sharding for optimization state that differs from that of parameter state
• Gradient accumulation

This is a work in progress: the guide will be much further fleshed out over time.

This document emphasizes a style as close to pure jax as possible: to that end, it shows how the flax version of each technique only requires minor deviation from the often more intuitive pure-jax version.

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