Felipe97/llama-cpp-compiled

1#include "models.h"2 3void llama_model_gptneox::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_USE_PARALLEL_RESIDUAL,   hparams.use_par_res);6 7    switch (hparams.n_layer()) {8        case 6:9            switch (hparams.n_ff()) {10                case 512:  type = LLM_TYPE_14M; break;11                case 2048: type = LLM_TYPE_70M; break;12                default:   type = LLM_TYPE_UNKNOWN;13            } break;14        case 12:15            switch (hparams.n_ff()) {16                case 3072: type = LLM_TYPE_160M; break;17                default: type = LLM_TYPE_UNKNOWN;18            } break;19        case 16:20            switch (hparams.n_ff()) {21                case 8192: type = LLM_TYPE_1B; break;22                default: type = LLM_TYPE_UNKNOWN;23            } break;24        case 24:25            switch (hparams.n_ff()) {26                case 4096: type = LLM_TYPE_410M; break;27                case 8192: type = LLM_TYPE_1_4B; break;28                default: type = LLM_TYPE_UNKNOWN;29            } break;30        case 32:31            switch (hparams.n_ff()) {32                case 10240: type = LLM_TYPE_2_8B; break;33                case 16384: type = LLM_TYPE_6_9B; break;34                default: type = LLM_TYPE_UNKNOWN;35            } break;36        case 36:37            switch (hparams.n_ff()) {38                case 20480: type = LLM_TYPE_12B; break;39                default: type = LLM_TYPE_UNKNOWN;40            } break;41        case 44:42            switch (hparams.n_ff()) {43                case 24576: type = LLM_TYPE_20B; break;44                default: type = LLM_TYPE_UNKNOWN;45            } break;46        default: type = LLM_TYPE_UNKNOWN;47    }48}49 50void llama_model_gptneox::load_arch_tensors(llama_model_loader &) {51    LLAMA_LOAD_LOCALS;52 53    tok_embd = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, 0);54 55    // output56    output_norm   = create_tensor(tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd}, 0);57    output_norm_b = create_tensor(tn(LLM_TENSOR_OUTPUT_NORM, "bias"),   {n_embd}, 0);58    output        = create_tensor(tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab}, 0);59 60    for (int i = 0; i < n_layer; ++i) {61        auto & layer = layers[i];62 63        layer.attn_norm   = create_tensor(tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd}, 0);64        layer.attn_norm_b = create_tensor(tn(LLM_TENSOR_ATTN_NORM, "bias", i),   {n_embd}, 0);65 66        layer.wqkv = create_tensor(tn(LLM_TENSOR_ATTN_QKV, "weight", i), {n_embd, n_embd + 2*n_embd_gqa}, 0);67        layer.wqkv_b = create_tensor(tn(LLM_TENSOR_ATTN_QKV, "bias", i), {n_embd + 2*n_embd_gqa}, 0);68 69        layer.wo   = create_tensor(tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd}, 0);70        layer.wo_b = create_tensor(tn(LLM_TENSOR_ATTN_OUT, "bias", i),   {n_embd}, 0);71 72        layer.ffn_norm   = create_tensor(tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd}, 0);73        layer.ffn_norm_b = create_tensor(tn(LLM_TENSOR_FFN_NORM, "bias", i),   {n_embd}, 0);74 75        layer.ffn_down   = create_tensor(tn(LLM_TENSOR_FFN_DOWN, "weight", i), {n_ff, n_embd}, 0);76        layer.ffn_down_b = create_tensor(tn(LLM_TENSOR_FFN_DOWN, "bias", i),   {n_embd}, 0);77 78        layer.ffn_up     = create_tensor(tn(LLM_TENSOR_FFN_UP,   "weight", i), {n_embd, n_ff}, 0);79        layer.ffn_up_b   = create_tensor(tn(LLM_TENSOR_FFN_UP,   "bias", i),   {n_ff}, 0);80    }81}82 83std::unique_ptr<llm_graph_context> llama_model_gptneox::build_arch_graph(const llm_graph_params & params) const {84    return std::make_unique<graph>(*this, params);85}86 87llama_model_gptneox::graph::graph(const llama_model & model, const llm_graph_params & params) : llm_graph_context(params) {88    const int64_t n_embd_head = hparams.n_embd_head_v();89 90    GGML_ASSERT(n_embd_head == hparams.n_embd_head_k());91 92    ggml_tensor * cur;93    ggml_tensor * inpL;94 95    inpL = build_inp_embd(model.tok_embd);96 97    // inp_pos - contains the positions98    ggml_tensor * inp_pos = build_inp_pos();99 100    auto * inp_attn = build_attn_inp_kv();101 102    ggml_tensor * inp_out_ids = build_inp_out_ids();103 104    for (int il = 0; il < n_layer; ++il) {105        cur = build_norm(inpL,106                model.layers[il].attn_norm,107                model.layers[il].attn_norm_b,108                LLM_NORM, il);109        cb(cur, "attn_norm", il);110 111        // self-attention112        {113            auto [Qcur, Kcur, Vcur] = build_qkv(model.layers[il], cur,114                    n_embd_head, n_head, n_head_kv, il);115 116            Qcur = ggml_rope_ext(117                    ctx0, Qcur, inp_pos, nullptr,118                    n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,119                    ext_factor, attn_factor, beta_fast, beta_slow120                    );121 122            Kcur = ggml_rope_ext(123                    ctx0, Kcur, inp_pos, nullptr,124                    n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,125                    ext_factor, attn_factor, beta_fast, beta_slow126                    );127 128            cb(Qcur, "Qcur", il);129            cb(Kcur, "Kcur", il);130            cb(Vcur, "Vcur", il);131 132            cur = build_attn(inp_attn,133                    model.layers[il].wo, model.layers[il].wo_b, model.layers[il].wo_s,134                    Qcur, Kcur, Vcur, nullptr, nullptr, nullptr, 1.0f/sqrtf(float(n_embd_head)), il);135        }136 137        if (il == n_layer - 1 && inp_out_ids) {138            cur  = ggml_get_rows(ctx0,  cur, inp_out_ids);139            inpL = ggml_get_rows(ctx0, inpL, inp_out_ids);140        }141 142        // ffn143        if (hparams.use_par_res) {144            // attention and ffn are computed in parallel145            // x = x + attn(ln1(x)) + ffn(ln2(x))146 147            ggml_tensor * attn_out = cur;148 149            cur = build_norm(inpL,150                    model.layers[il].ffn_norm,151                    model.layers[il].ffn_norm_b,152                    LLM_NORM, il);153            cb(cur, "ffn_norm", il);154 155            cur = build_ffn(cur,156                    model.layers[il].ffn_up,   model.layers[il].ffn_up_b,   NULL,157                    NULL,                      NULL,                        NULL,158                    model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL,159                    NULL,160                    LLM_FFN_GELU, LLM_FFN_SEQ, il);161            cb(cur, "ffn_out", il);162 163            cur = ggml_add(ctx0, cur, inpL);164            cb(cur, "ffn_out", il);165 166            cur = ggml_add(ctx0, cur, attn_out);167 168            cur = build_cvec(cur, il);169            cb(cur, "l_out", il);170 171            // input for next layer172            inpL = cur;173        } else {174            // attention and ffn are computed sequentially175            // x = x + attn(ln1(x))176            // x = x + ffn(ln2(x))177 178            ggml_tensor * ffn_inp = ggml_add(ctx0, cur, inpL);179            cb(ffn_inp, "ffn_inp", il);180 181            cur = build_norm(ffn_inp,182                    model.layers[il].ffn_norm,183                    model.layers[il].ffn_norm_b,184                    LLM_NORM, il);185            cb(cur, "ffn_norm", il);186 187            cur = build_ffn(cur,188                    model.layers[il].ffn_up,   model.layers[il].ffn_up_b,   NULL,189                    NULL,                      NULL,                        NULL,190                    model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL,191                    NULL,192                    LLM_FFN_GELU, LLM_FFN_SEQ, il);193            cb(cur, "ffn_out", il);194 195            cur = ggml_add(ctx0, cur, ffn_inp);196 197            cur = build_cvec(cur, il);198            cb(cur, "l_out", il);199 200            // input for next layer201            inpL = cur;202        }203    }204 205    cur = build_norm(inpL,206            model.output_norm,207            model.output_norm_b,208            LLM_NORM, -1);209 210    cb(cur, "result_norm", -1);211    res->t_embd = cur;212 213    cur = build_lora_mm(model.output, cur, model.output_s);214 215    cb(cur, "result_output", -1);216    res->t_logits = cur;217 218    ggml_build_forward_expand(gf, cur);219}220