Add an always-active shared expert

Read the equation

The shared expert processes identity, the input representation saved before the routed expert computation. Its output is added to the weighted routed sum. It therefore contributes a parallel transformation of the original input; it does not take the routed output as its input.

Terms & definitions

How it works

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Assumptions & limits

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Original context

y = self.moe_infer(hidden_states, topk_idx,
                               topk_weight).view(*orig_shape)
        if self.config.n_shared_experts is not None:
            y = y + self.shared_experts(identity)
        return y

    @torch.no_grad()

y = y + self.shared_experts(identity)

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