mirror of
https://github.com/ggml-org/whisper.cpp.git
synced 2026-10-18 04:35:33 +02:00
talk-llama : sync llama.cpp
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@@ -1,10 +1,10 @@
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#include "models.h"
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llm_build_qwen3::llm_build_qwen3(const llama_model & model, const llm_graph_params & params) : llm_graph_context(params) {
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const int64_t n_embd_head = hparams.n_embd_head_v;
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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_ASSERT(n_embd_head == hparams.n_rot);
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GGML_ASSERT(n_embd_head == hparams.n_embd_head_k());
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GGML_ASSERT(n_embd_head == n_rot);
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ggml_tensor * cur;
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ggml_tensor * inpL;
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@@ -30,13 +30,13 @@ llm_build_qwen3::llm_build_qwen3(const llama_model & model, const llm_graph_para
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// self-attention
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{
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// compute Q and K and RoPE them
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ggml_tensor * Qcur = build_lora_mm(model.layers[il].wq, cur);
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ggml_tensor * Qcur = build_lora_mm(model.layers[il].wq, cur, model.layers[il].wq_s);
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cb(Qcur, "Qcur", il);
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ggml_tensor * Kcur = build_lora_mm(model.layers[il].wk, cur);
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ggml_tensor * Kcur = build_lora_mm(model.layers[il].wk, cur, model.layers[il].wk_s);
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cb(Kcur, "Kcur", il);
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ggml_tensor * Vcur = build_lora_mm(model.layers[il].wv, cur);
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ggml_tensor * Vcur = build_lora_mm(model.layers[il].wv, cur, model.layers[il].wv_s);
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cb(Vcur, "Vcur", il);
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Qcur = ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head, n_tokens);
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@@ -68,6 +68,9 @@ llm_build_qwen3::llm_build_qwen3(const llama_model & model, const llm_graph_para
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cur = build_attn(inp_attn,
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model.layers[il].wo, model.layers[il].bo,
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Qcur, Kcur, Vcur, nullptr, nullptr, nullptr, 1.0f/sqrtf(float(n_embd_head)), il);
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if (model.layers[il].wo_s) {
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cur = ggml_mul(ctx0, cur, model.layers[il].wo_s);
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}
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}
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if (il == n_layer - 1 && inp_out_ids) {
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cur = ggml_get_rows(ctx0, cur, inp_out_ids);
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@@ -83,9 +86,9 @@ llm_build_qwen3::llm_build_qwen3(const llama_model & model, const llm_graph_para
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cb(cur, "ffn_norm", il);
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cur = build_ffn(cur,
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model.layers[il].ffn_up, NULL, NULL,
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model.layers[il].ffn_gate, NULL, NULL,
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model.layers[il].ffn_down, NULL, NULL,
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model.layers[il].ffn_up, NULL, model.layers[il].ffn_up_s,
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model.layers[il].ffn_gate, NULL, model.layers[il].ffn_gate_s,
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model.layers[il].ffn_down, NULL, model.layers[il].ffn_down_s,
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NULL,
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LLM_FFN_SILU, LLM_FFN_PAR, il);
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cb(cur, "ffn_out", il);
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