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
-11
@@ -30,17 +30,8 @@ llm_build_llada::llm_build_llada(const llama_model & model, const llm_graph_para
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// self-attention
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{
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// compute separate Q, K, V projections without bias, matching LLaDALlamaBlock
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ggml_tensor * Qcur = build_lora_mm(model.layers[il].wq, cur);
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ggml_tensor * Kcur = build_lora_mm(model.layers[il].wk, cur);
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ggml_tensor * Vcur = build_lora_mm(model.layers[il].wv, cur);
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cb(Qcur, "Qcur", il);
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cb(Kcur, "Kcur", il);
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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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Kcur = ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens);
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Vcur = ggml_reshape_3d(ctx0, Vcur, n_embd_head, n_head_kv, n_tokens);
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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(ctx0, Qcur, inp_pos, nullptr, n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,
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ext_factor, attn_factor, beta_fast, beta_slow);
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