Fixes to per-layer lr-scale

[RaymondLi0]

✨ Description

Specify different lr-scales per layer.

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📝 Changes

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2. Change B

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📊 Performance Impact Details

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[oleksost]

I think this can be closed as this has been merged in #258

[RaymondLi0]

Sorry for the delay on this one. @oleksost could you have another look?
Seems some fixes were not included in #258

[oleksost]

Thanks for finding these bugs! These should be merged asap I think

[jlamypoirier]

This will have unintended consequences on the initialization scale.

[RaymondLi0]

This only affects the prediction-heads for i>0 (thus not the next-token prediction)

[jlamypoirier]

Yes, but the layer index is used elsewhere. It looks like it's only used in the backup attention regularization though, so it doesn't matter much https://github.com/ServiceNow/Fast-LLM/blob/main/fast_llm/layers/transformer/attention.py#L181. I got mixed up with num_layers which does matter for initialization.