graph : remove redundant scale_w parameter (#20235)
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+10
-4
@@ -23,10 +23,16 @@ llm_build_lfm2<iswa>::llm_build_lfm2(const llama_model & model, const llm_graph_
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};
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auto build_moe_feed_forward = [&model, this](ggml_tensor * cur, int il) -> ggml_tensor * {
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return build_moe_ffn(cur,
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model.layers[il].ffn_gate_inp, model.layers[il].ffn_up_exps,
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model.layers[il].ffn_gate_exps, model.layers[il].ffn_down_exps,
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model.layers[il].ffn_exp_probs_b, n_expert, n_expert_used, LLM_FFN_SILU, true, false, 0.0,
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static_cast<llama_expert_gating_func_type>(hparams.expert_gating_func), il);
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model.layers[il].ffn_gate_inp,
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model.layers[il].ffn_up_exps,
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model.layers[il].ffn_gate_exps,
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model.layers[il].ffn_down_exps,
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model.layers[il].ffn_exp_probs_b,
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n_expert, n_expert_used,
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LLM_FFN_SILU, true,
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hparams.expert_weights_scale,
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static_cast<llama_expert_gating_func_type>(hparams.expert_gating_func),
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il);
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};
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auto build_attn_block = [&model, this](ggml_tensor * cur,
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ggml_tensor * inp_pos,
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