Felipe97/llama-cpp-compiled

1#include "models.h"2 3void llama_model_xverse::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        case 80: type = LLM_TYPE_65B; break;10        default: type = LLM_TYPE_UNKNOWN;11    }12}13 14void llama_model_xverse::load_arch_tensors(llama_model_loader &) {15    LLAMA_LOAD_LOCALS;16 17    tok_embd = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, 0);18 19    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        create_tensor_qkv(layer, i, n_embd, n_embd, n_embd_gqa, n_embd_gqa, 0);28        layer.wo = create_tensor(tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd}, 0);29 30        layer.ffn_norm = create_tensor(tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd}, 0);31        layer.ffn_gate = create_tensor(tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd,   n_ff}, 0);32        layer.ffn_down = create_tensor(tn(LLM_TENSOR_FFN_DOWN, "weight", i), {  n_ff, n_embd}, 0);33        layer.ffn_up   = create_tensor(tn(LLM_TENSOR_FFN_UP,   "weight", i), {n_embd,   n_ff}, 0);34    }35}36 37std::unique_ptr<llm_graph_context> llama_model_xverse::build_arch_graph(const llm_graph_params & params) const {38    return std::make_unique<graph>(*this, params);39}40 41llama_model_xverse::graph::graph(const llama_model & model, const llm_graph_params & params) : llm_graph_context(params) {42    const int64_t n_embd_head = hparams.n_embd_head_v();43 44    GGML_ASSERT(n_embd_head == hparams.n_embd_head_k());45    GGML_ASSERT(n_embd_head == n_rot);46 47    ggml_tensor * cur;48    ggml_tensor * inpL;49 50    inpL = build_inp_embd(model.tok_embd);51 52    // inp_pos - contains the positions53    ggml_tensor * inp_pos = build_inp_pos();54 55    auto * inp_attn = build_attn_inp_kv();56 57    ggml_tensor * inp_out_ids = build_inp_out_ids();58 59    for (int il = 0; il < n_layer; ++il) {60        ggml_tensor * inpSA = inpL;61 62        cur = build_norm(inpL,63                model.layers[il].attn_norm, NULL,64                LLM_NORM_RMS, il);65        cb(cur, "attn_norm", il);66 67        // self-attention68        {69            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_rot, 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_rot, 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            inpSA = ggml_get_rows(ctx0, inpSA, inp_out_ids);95        }96        ggml_tensor * ffn_inp = ggml_add(ctx0, cur, inpSA);97        cb(ffn_inp, "ffn_inp", il);98 99        // feed-forward network100        {101            cur = build_norm(ffn_inp,102                    model.layers[il].ffn_norm, NULL,103                    LLM_NORM_RMS, il);104            cb(cur, "ffn_norm", il);105 106            cur = build_ffn(cur,107                    model.layers[il].ffn_up,   NULL, NULL,108                    model.layers[il].ffn_gate, NULL, NULL,109                    model.layers[il].ffn_down, NULL, NULL,110                    NULL,111                    LLM_FFN_SILU, LLM_FFN_PAR, il);112            cb(cur, "ffn_out", il);113        }114        cur = ggml_add(ctx0, cur, ffn_inp);115 116        cur = build_cvec(cur, il);117        cb(cur, "l_out", il);118 119        // input for next layer120        inpL = cur;121    }122    cur = inpL;123 124    cur = build_norm(cur, model.output_norm, NULL, 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