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Add Echo-Memory codebase used for this run (CC BY 4.0, JD Echo Team) (part 3)
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# Simple GLA
Gating mechanism in [Gated RFA](https://arxiv.org/abs/2103.02143), [Mamba2](https://arxiv.org/abs/2405.21060) and [YOCO](https://arxiv.org/abs/2405.05254) (a.k.a., Gated RetNet).
Compared to GLA, the gating is head-wise instead of elementwise.
As a result, we can adapt the RetNet kernel for training using matmul w/o numerical instability.
It is faster than GLA but has less expressive power.
I will use it as a baseline for the GLA.
$S_{t+1} = g_{t+1} \odot S_{t} + K_{t+1} V_{t+1}^{\top}$ where $g$ is a scalar.