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https://github.com/ggml-org/whisper.cpp.git
synced 2026-10-18 21:55:18 +02:00
talk-llama : sync llama.cpp
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@@ -2,8 +2,8 @@
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llm_build_nemotron_h::llm_build_nemotron_h(const llama_model & model, const llm_graph_params & params) :
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llm_build_mamba_base(params) {
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const int64_t n_embd_head = hparams.n_embd_head_v;
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GGML_ASSERT(n_embd_head == hparams.n_embd_head_k);
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const int64_t n_embd_head = hparams.n_embd_head_v();
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GGML_ASSERT(n_embd_head == hparams.n_embd_head_k());
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ggml_tensor * cur;
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ggml_tensor * inpL;
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@@ -114,9 +114,18 @@ ggml_tensor * llm_build_nemotron_h::build_ffn_layer(ggml_tensor * cur, const lla
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LLM_FFN_RELU_SQR, LLM_FFN_PAR, il);
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cb(cur, "ffn_out", il);
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} else {
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ggml_tensor * ffn_inp = cur;
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ggml_tensor * inp_emb = cur;
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ggml_tensor * inp_latent = cur;
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if (model.layers[il].ffn_latent_down) {
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inp_latent = ggml_mul_mat(ctx0, model.layers[il].ffn_latent_down, cur);
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}
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ggml_tensor * router_logits = build_lora_mm(model.layers[il].ffn_gate_inp, cur);
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cb(router_logits, "ffn_moe_logits", il);
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ggml_tensor * moe_out =
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build_moe_ffn(ffn_inp,
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build_moe_ffn(inp_latent,
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model.layers[il].ffn_gate_inp,
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model.layers[il].ffn_up_exps,
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nullptr, // no gate
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@@ -124,12 +133,17 @@ ggml_tensor * llm_build_nemotron_h::build_ffn_layer(ggml_tensor * cur, const lla
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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_RELU_SQR, hparams.expert_weights_norm,
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true, hparams.expert_weights_scale,
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hparams.expert_weights_scale,
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LLAMA_EXPERT_GATING_FUNC_TYPE_SIGMOID,
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il);
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il,
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router_logits);
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cb(moe_out, "ffn_moe_out", il);
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ggml_tensor * ffn_shexp = build_ffn(ffn_inp,
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if (model.layers[il].ffn_latent_up) {
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moe_out = ggml_mul_mat(ctx0, model.layers[il].ffn_latent_up, moe_out);
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}
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ggml_tensor * ffn_shexp = build_ffn(inp_emb,
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model.layers[il].ffn_up_shexp, NULL, NULL,
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NULL /* no gate */ , NULL, NULL,
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model.layers[il].ffn_down_shexp, NULL, NULL,
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