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model : refactor QKV into common build_qkv and create_tensor_qkv helpers (#21245)
* model : refactor QKV into common build_qkv and create_tensor_qkv helpers * model : extend build_qkv to bert/mpt/dbrx/olmo/lfm2/nemotron-h/granite-hybrid/gemma3n-iswa/t5-dec and fix wqkv_s
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@@ -2,7 +2,6 @@
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llm_build_codeshell::llm_build_codeshell(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_gqa = hparams.n_embd_v_gqa();
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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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@@ -28,15 +27,8 @@ llm_build_codeshell::llm_build_codeshell(const llama_model & model, const llm_gr
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// self-attention
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{
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cur = build_lora_mm(model.layers[il].wqkv, cur);
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cb(cur, "wqkv", il);
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cur = ggml_add(ctx0, cur, model.layers[il].bqkv);
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cb(cur, "bqkv", il);
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ggml_tensor * Qcur = ggml_view_3d(ctx0, cur, n_embd_head, n_head, n_tokens, n_embd_head*sizeof(float), cur->nb[1], 0*sizeof(float)*(n_embd));
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ggml_tensor * Kcur = ggml_view_3d(ctx0, cur, n_embd_head, n_head_kv, n_tokens, n_embd_head*sizeof(float), cur->nb[1], 1*sizeof(float)*(n_embd));
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ggml_tensor * Vcur = ggml_view_3d(ctx0, cur, n_embd_head, n_head_kv, n_tokens, n_embd_head*sizeof(float), cur->nb[1], 1*sizeof(float)*(n_embd + n_embd_gqa));
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auto [Qcur, Kcur, Vcur] = build_qkv(model.layers[il], cur,
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n_embd_head, n_head, n_head_kv, il);
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Qcur = ggml_rope_ext(
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ctx0, Qcur, inp_pos, nullptr,
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