Felipe97/llama-cpp-compiled

1#include "models.h"2 3void llama_model_qwen::load_arch_hparams(llama_model_loader & ml) {4    ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, hparams.f_norm_rms_eps);5 6    switch (hparams.n_layer()) {7        case 32: type = LLM_TYPE_7B; break;8        case 40: type = LLM_TYPE_13B; break;9        default: type = LLM_TYPE_UNKNOWN;10    }11}12 13void llama_model_qwen::load_arch_tensors(llama_model_loader &) {14    LLAMA_LOAD_LOCALS;15 16    tok_embd = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, 0);17 18    // output19    output_norm = create_tensor(tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd}, 0);20    output      = create_tensor(tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab}, 0);21 22    for (int i = 0; i < n_layer; ++i) {23        auto & layer = layers[i];24 25        layer.attn_norm = create_tensor(tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd}, 0);26 27        layer.wqkv = create_tensor(tn(LLM_TENSOR_ATTN_QKV, "weight", i), {n_embd, n_embd*3}, 0);28        layer.wqkv_b = create_tensor(tn(LLM_TENSOR_ATTN_QKV, "bias", i), {n_embd*3}, 0);29        layer.wo   = create_tensor(tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd}, 0);30 31        layer.ffn_norm = create_tensor(tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd}, 0);32 33        layer.ffn_gate = create_tensor(tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd, n_ff/2}, 0);34        layer.ffn_down = create_tensor(tn(LLM_TENSOR_FFN_DOWN, "weight", i), {n_ff/2, n_embd}, 0);35        layer.ffn_up   = create_tensor(tn(LLM_TENSOR_FFN_UP,   "weight", i), {n_embd, n_ff/2}, 0);36    }37}38 39std::unique_ptr<llm_graph_context> llama_model_qwen::build_arch_graph(const llm_graph_params & params) const {40    return std::make_unique<graph>(*this, params);41}42 43llama_model_qwen::graph::graph(const llama_model & model, const llm_graph_params & params) : llm_graph_context(params) {44    const int64_t n_embd_head = hparams.n_embd_head_v();45 46    GGML_ASSERT(n_embd_head == hparams.n_embd_head_k());47 48    ggml_tensor * cur;49    ggml_tensor * inpL;50 51    inpL = build_inp_embd(model.tok_embd);52 53    // inp_pos - contains the positions54    ggml_tensor * inp_pos = build_inp_pos();55 56    auto * inp_attn = build_attn_inp_kv();57 58    ggml_tensor * inp_out_ids = build_inp_out_ids();59 60    for (int il = 0; il < n_layer; ++il) {61        ggml_tensor * inpSA = inpL;62 63        cur = build_norm(inpL,64                model.layers[il].attn_norm, NULL,65                LLM_NORM_RMS, il);66        cb(cur, "attn_norm", il);67 68        // self-attention69        {70            auto [Qcur, Kcur, Vcur] = build_qkv(model.layers[il], cur,71                    n_embd_head, n_head, n_head_kv, il);72 73            // using mode = 2 for neox mode74            Qcur = ggml_rope_ext(75                    ctx0, Qcur, inp_pos, nullptr,76                    n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,77                    ext_factor, attn_factor, beta_fast, beta_slow78                    );79 80            Kcur = ggml_rope_ext(81                    ctx0, Kcur, inp_pos, nullptr,82                    n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,83                    ext_factor, attn_factor, beta_fast, beta_slow84                    );85 86            cb(Qcur, "Qcur", il);87            cb(Kcur, "Kcur", il);88            cb(Vcur, "Vcur", il);89 90            cur = build_attn(inp_attn,91                    model.layers[il].wo, NULL, model.layers[il].wo_s,92                    Qcur, Kcur, Vcur, nullptr, nullptr, nullptr, 1.0f/sqrtf(float(n_embd_head)), il);93        }94        if (il == n_layer - 1 && inp_out_ids) {95            cur   = ggml_get_rows(ctx0,   cur, inp_out_ids);96            inpSA = ggml_get_rows(ctx0, inpSA, inp_out_ids);97        }98        ggml_tensor * ffn_inp = ggml_add(ctx0, cur, inpSA);99        cb(ffn_inp, "ffn_inp", il);100 101        // feed-forward forward102        {103            cur = build_norm(ffn_inp,104                    model.layers[il].ffn_norm, NULL,105                    LLM_NORM_RMS, il);106            cb(cur, "ffn_norm", il);107 108            cur = build_ffn(cur,109                    model.layers[il].ffn_up,   NULL, NULL,110                    model.layers[il].ffn_gate, NULL, NULL,111                    model.layers[il].ffn_down, NULL, NULL,112                    NULL,113                    LLM_FFN_SILU, LLM_FFN_PAR, il);114            cb(cur, "ffn_out", il);115        }116        cur = ggml_add(ctx0, cur, ffn_inp);117 118        cur = build_cvec(cur, il);119        cb(cur, "l_out", il);120 121        // input for next layer122        inpL = cur;123    }124    cur = inpL;125 126    cur = build_norm(cur,127            model.output_norm, NULL,128            LLM_NORM_RMS, -1);129 130    cb(cur, "result_norm", -1);131    res->t_embd = cur;132 133    // lm_head134    cur = build_lora_mm(model.output, cur, model.output_s);135 136    cb(cur, "result_output", -1);137    res->t_logits = cur;138 139    ggml_build_forward_expand(gf, cur);140}141