Felipe97/llama-cpp-compiled

1#include "models.h"2 3void llama_model_plamo::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 40: type = LLM_TYPE_13B; break;8        default: type = LLM_TYPE_UNKNOWN;9   }10}11 12void llama_model_plamo::load_arch_tensors(llama_model_loader &) {13    LLAMA_LOAD_LOCALS;14 15    tok_embd = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, 0);16 17    // output18    output_norm = create_tensor(tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd}, 0);19    output      = create_tensor(tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab}, 0);20 21    for (int i = 0; i < n_layer; ++i) {22        auto & layer = layers[i];23 24        layer.attn_norm = create_tensor(tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd}, 0);25 26        create_tensor_qkv(layer, i, n_embd, n_embd, n_embd_gqa, n_embd_gqa, 0);27        layer.wo = create_tensor(tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd}, 0);28 29        layer.ffn_gate = create_tensor(tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd,   n_ff}, 0);30        layer.ffn_down = create_tensor(tn(LLM_TENSOR_FFN_DOWN, "weight", i), {  n_ff, n_embd}, 0);31        layer.ffn_up   = create_tensor(tn(LLM_TENSOR_FFN_UP,   "weight", i), {n_embd,   n_ff}, 0);32    }33}34 35std::unique_ptr<llm_graph_context> llama_model_plamo::build_arch_graph(const llm_graph_params & params) const {36    return std::make_unique<graph>(*this, params);37}38 39llama_model_plamo::graph::graph(const llama_model & model, const llm_graph_params & params) : llm_graph_context(params) {40    const int64_t n_embd_head = hparams.n_embd_head_v();41 42    GGML_ASSERT(n_embd_head == hparams.n_embd_head_k());43    GGML_ASSERT(n_embd_head == n_rot);44 45    ggml_tensor * cur;46    ggml_tensor * inpL;47 48    inpL = build_inp_embd(model.tok_embd);49 50    // inp_pos - contains the positions51    ggml_tensor * inp_pos = build_inp_pos();52 53    auto * inp_attn = build_attn_inp_kv();54 55    ggml_tensor * inp_out_ids = build_inp_out_ids();56 57    for (int il = 0; il < n_layer; ++il) {58        // norm59        cur = build_norm(inpL,60                model.layers[il].attn_norm, NULL,61                LLM_NORM_RMS, il);62        cb(cur, "attn_norm", il);63 64        ggml_tensor * sa_inp = cur;65 66        // self-attention67        {68            // compute Q and K and RoPE them69            auto [Qcur, Kcur, Vcur] = build_qkv(model.layers[il], cur,70                    n_embd_head, n_head, n_head_kv, il);71 72            Qcur = ggml_rope_ext(73                    ctx0, Qcur, inp_pos, nullptr,74                    n_embd_head, rope_type, n_ctx_orig, freq_base, freq_scale,75                    ext_factor, attn_factor, beta_fast, beta_slow76                    );77 78            Kcur = ggml_rope_ext(79                    ctx0, Kcur, inp_pos, nullptr,80                    n_embd_head, rope_type, n_ctx_orig, freq_base, freq_scale,81                    ext_factor, attn_factor, beta_fast, beta_slow82                    );83 84            cb(Qcur, "Qcur", il);85            cb(Kcur, "Kcur", il);86            cb(Vcur, "Vcur", il);87 88            cur = build_attn(inp_attn,89                    model.layers[il].wo, NULL, model.layers[il].wo_s,90                    Qcur, Kcur, Vcur, nullptr, nullptr, nullptr, 1.0f/sqrtf(float(n_embd_head)), il);91        }92        if (il == n_layer - 1 && inp_out_ids) {93            cur    = ggml_get_rows(ctx0,    cur, inp_out_ids);94            sa_inp = ggml_get_rows(ctx0, sa_inp, inp_out_ids);95            inpL   = ggml_get_rows(ctx0,   inpL, inp_out_ids);96        }97        ggml_tensor * sa_out = cur;98 99        cur = sa_inp;100 101        // feed-forward network102        {103            cur = build_ffn(cur,104                    model.layers[il].ffn_up,   NULL, NULL,105                    model.layers[il].ffn_gate, NULL, NULL,106                    model.layers[il].ffn_down, NULL, NULL,107                    NULL,108                    LLM_FFN_SILU, LLM_FFN_PAR, il);109            cb(cur, "ffn_out", il);110        }111        cur = ggml_add(ctx0, cur, sa_out);112        cur = ggml_add(ctx0, cur, inpL);113 114        cur = build_cvec(cur, il);115        cb(cur, "l_out", il);116 117        // input for next layer118        inpL = cur;119    }120    cur = inpL;121 122    cur = build_norm(cur,123            model.output_norm, NULL,124            LLM_NORM_RMS, -1);125 126    cb(cur, "result_norm", -1);127    res->t_embd = cur;128 129    // lm_head130    cur = build_lora_mm(model.output, cur, model.output_s);131 132    cb(cur, "result_output", -1);133    res->t_logits = cur;134 135    ggml_build_forward_expand(gf, cur);136}137