Felipe97/llama-cpp-compiled

1#include "models.h"2 3void llama_model_jais::load_arch_hparams(llama_model_loader & ml) {4    ml.get_key(LLM_KV_ATTENTION_LAYERNORM_EPS, hparams.f_norm_eps);5    ml.get_key(LLM_KV_ATTENTION_MAX_ALIBI_BIAS, hparams.f_max_alibi_bias, false);6 7    switch (hparams.n_layer()) {8        case 24: type = LLM_TYPE_1_3B; break;9        case 40: type = LLM_TYPE_13B; break;10        /* TODO: add variants */11        default: type = LLM_TYPE_UNKNOWN;12    }13}14 15void llama_model_jais::load_arch_tensors(llama_model_loader &) {16    LLAMA_LOAD_LOCALS;17 18    tok_embd = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, 0);19 20    // output21    output_norm   = create_tensor(tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd}, 0);22    output_norm_b = create_tensor(tn(LLM_TENSOR_OUTPUT_NORM, "bias"),   {n_embd}, 0);23    output        = create_tensor(tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab}, 0);24 25    for (int i = 0; i < n_layer; ++i) {26        auto & layer = layers[i];27 28        layer.attn_norm   = create_tensor(tn(LLM_TENSOR_ATTN_NORM,   "weight", i), {n_embd}, 0);29        layer.attn_norm_b = create_tensor(tn(LLM_TENSOR_ATTN_NORM,   "bias", i),   {n_embd}, 0);30 31        layer.wqkv = create_tensor(tn(LLM_TENSOR_ATTN_QKV, "weight", i), {n_embd, n_embd + 2*n_embd_gqa}, 0);32        layer.wqkv_b = create_tensor(tn(LLM_TENSOR_ATTN_QKV, "bias", i), {n_embd + 2*n_embd_gqa}, 0);33 34        layer.wo = create_tensor(tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd}, 0);35        layer.wo_b = create_tensor(tn(LLM_TENSOR_ATTN_OUT, "bias", i), {n_embd}, 0);36 37        layer.ffn_norm   = create_tensor(tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd}, 0);38        layer.ffn_norm_b = create_tensor(tn(LLM_TENSOR_FFN_NORM, "bias", i),   {n_embd}, 0);39 40        layer.ffn_down   = create_tensor(tn(LLM_TENSOR_FFN_DOWN, "weight", i), {n_ff, n_embd}, 0);41        layer.ffn_down_b = create_tensor(tn(LLM_TENSOR_FFN_DOWN, "bias", i),   {n_embd}, 0);42 43        layer.ffn_gate   = create_tensor(tn(LLM_TENSOR_FFN_GATE,   "weight", i), {n_embd, n_ff}, 0);44        layer.ffn_gate_b = create_tensor(tn(LLM_TENSOR_FFN_GATE,   "bias", i),   {n_ff}, 0);45 46        layer.ffn_up     = create_tensor(tn(LLM_TENSOR_FFN_UP,   "weight", i), {n_embd, n_ff}, 0);47        layer.ffn_up_b   = create_tensor(tn(LLM_TENSOR_FFN_UP,   "bias", i),   {n_ff}, 0);48    }49}50 51std::unique_ptr<llm_graph_context> llama_model_jais::build_arch_graph(const llm_graph_params & params) const {52    return std::make_unique<graph>(*this, params);53}54 55llama_model_jais::graph::graph(const llama_model & model, const llm_graph_params & params) : llm_graph_context(params) {56    const int64_t n_embd_head = hparams.n_embd_head_v();57 58    GGML_ASSERT(n_embd_head == hparams.n_embd_head_k());59 60    ggml_tensor * cur;61    ggml_tensor * inpL;62 63    inpL = build_inp_embd(model.tok_embd);64 65    auto * inp_attn = build_attn_inp_kv();66 67    ggml_tensor * inp_out_ids = build_inp_out_ids();68 69    for (int il = 0; il < n_layer; ++il) {70        cur = build_norm(inpL,71                model.layers[il].attn_norm,72                model.layers[il].attn_norm_b,73                LLM_NORM, il);74        cb(cur, "attn_norm", il);75 76        // self-attention77        {78            auto [Qcur, Kcur, Vcur] = build_qkv(model.layers[il], cur,79                    n_embd_head, n_head, n_head_kv, il);80 81            cur = build_attn(inp_attn,82                    model.layers[il].wo, model.layers[il].wo_b, model.layers[il].wo_s,83                    Qcur, Kcur, Vcur, nullptr, nullptr, nullptr, 1.0f/float(n_embd_head), il);84        }85        if (il == n_layer - 1 && inp_out_ids) {86            cur  = ggml_get_rows(ctx0,  cur, inp_out_ids);87            inpL = ggml_get_rows(ctx0, inpL, inp_out_ids);88        }89        // add the input90        ggml_tensor * ffn_inp = ggml_add(ctx0, cur, inpL);91        cb(ffn_inp, "ffn_inp", il);92 93        // FF94        {95            cur = build_norm(ffn_inp,96                    model.layers[il].ffn_norm,97                    model.layers[il].ffn_norm_b,98                    LLM_NORM, il);99            cb(cur, "ffn_norm", il);100 101            cur = build_ffn(cur,102                    model.layers[il].ffn_up,   model.layers[il].ffn_up_b,   NULL,103                    model.layers[il].ffn_gate, model.layers[il].ffn_gate_b, NULL,104                    model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL,105                    NULL,106                    LLM_FFN_SILU, LLM_FFN_PAR, il);107            cb(cur, "ffn_out", il);108        }109 110        cur = ggml_add(ctx0, cur, ffn_inp);111 112        cur = build_cvec(cur, il);113        cb(cur, "l_out", il);114 115        // input for next layer116        inpL = cur;117    }118    cur = build_norm(inpL,119            model.output_norm,120            model.output_norm_b,121            LLM_NORM, -1);122 123    cb(cur, "result_norm", -1);124    res->t_embd = cur;125 126    cur = build_lora_mm(model.output, cur, model.output_s);127 128    cb(cur, "result_output", -1);129    res->t_logits = cur;130 131    ggml_build_forward_expand(gf, cur);132}133