model : use ggml_swiglu_split for Mamba

Co-authored-by: Sigbjørn Skjæret <[email protected]>

Author: compilade

src/llama-model.cpp

@@ -10057,7 +10057,7 @@ struct llm_graph_context_mamba : public llm_graph_context {
             // TODO: skip computing output earlier for unused tokens
 
             y = ggml_add(ctx0, y, ggml_mul(ctx0, cur, layer.ssm_d));
-            y = ggml_mul(ctx0, y, ggml_silu(ctx0, ggml_cont(ctx0, z)));
+            y = ggml_swiglu_split(ctx0, ggml_cont(ctx0, z), y);
 
             // {d_inner, n_embd} @ {d_inner, n_seq_tokens, n_seqs} => {n_embd, n_seq_tokens, n_seqs}
             cur = build_lora_mm(layer.ssm_out, y);
@@ -10181,7 +10181,7 @@ struct llm_graph_context_mamba : public llm_graph_context {
             // TODO: skip computing output earlier for unused tokens
 
             y = ggml_add(ctx0, y, ggml_mul(ctx0, x, model.layers[il].ssm_d));
-            y = ggml_mul(ctx0, y, ggml_silu(ctx0, ggml_cont(ctx0, z)));
+            y = ggml_swiglu_split(ctx0, ggml_cont(ctx0, z), y);
 
             // grouped RMS norm
             y = ggml_reshape_4d(ctx0, y, d_inner / n_group, n_group, n_seq_tokens, n_seqs);