[tt-train] Add kahan summation in AdamW #15518
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Problem description
bfloat16 has wide range, but is not as precise as float32. Some of the parameters are not updated due to small magnitude of the gradients (after multiplication by learning rate), as an example: gamma in LayerNorm.
What's changed
Add kahan summation flag to enable kahan summation when update weights.
Checklist
https://github.com/tenstorrent/tt-metal/actions/runs/12128966379