Felipe97/llama-cpp-compiled

1#include "models.h"2 3void llama_model_gpt2::load_arch_hparams(llama_model_loader & ml) {4    ml.get_key(LLM_KV_ATTENTION_LAYERNORM_EPS, hparams.f_norm_eps);5 6    switch (hparams.n_layer()) {7        case 12: type = LLM_TYPE_SMALL; break;8        case 24: type = LLM_TYPE_MEDIUM; break;9        case 36: type = LLM_TYPE_LARGE; break;10        case 48: type = LLM_TYPE_XL; break;11        default: type = LLM_TYPE_UNKNOWN;12    }13}14 15void llama_model_gpt2::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    pos_embd = create_tensor(tn(LLM_TENSOR_POS_EMBD,   "weight"), {n_embd, n_ctx_train}, 0);20 21    // output22    output_norm   = create_tensor(tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd}, 0);23    output_norm_b = create_tensor(tn(LLM_TENSOR_OUTPUT_NORM, "bias"),   {n_embd}, 0);24    output        = create_tensor(tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab}, TENSOR_NOT_REQUIRED);25 26    // if output is NULL, init from the input tok embed27    if (output == NULL) {28        output = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, TENSOR_DUPLICATED);29    }30 31    for (int i = 0; i < n_layer; ++i) {32        auto & layer = layers[i];33 34        layer.attn_norm   = create_tensor(tn(LLM_TENSOR_ATTN_NORM,   "weight", i), {n_embd}, 0);35        layer.attn_norm_b = create_tensor(tn(LLM_TENSOR_ATTN_NORM,   "bias", i),   {n_embd}, 0);36 37        layer.wqkv = create_tensor(tn(LLM_TENSOR_ATTN_QKV, "weight", i), {n_embd, n_embd + 2*n_embd_gqa}, 0);38        layer.wqkv_b = create_tensor(tn(LLM_TENSOR_ATTN_QKV, "bias", i), {n_embd + 2*n_embd_gqa}, 0);39 40        layer.wo   = create_tensor(tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd}, 0);41        layer.wo_b = create_tensor(tn(LLM_TENSOR_ATTN_OUT, "bias", i),   {n_embd}, 0);42 43        layer.ffn_norm   = create_tensor(tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd}, 0);44        layer.ffn_norm_b = create_tensor(tn(LLM_TENSOR_FFN_NORM, "bias", i),   {n_embd}, 0);45 46        layer.ffn_down   = create_tensor(tn(LLM_TENSOR_FFN_DOWN, "weight", i), {n_ff, n_embd}, 0);47        layer.ffn_down_b = create_tensor(tn(LLM_TENSOR_FFN_DOWN, "bias", i),   {n_embd}, 0);48 49        layer.ffn_up     = create_tensor(tn(LLM_TENSOR_FFN_UP,   "weight", i), {n_embd, n_ff}, 0);50        layer.ffn_up_b   = create_tensor(tn(LLM_TENSOR_FFN_UP,   "bias", i),   {n_ff}, 0);51    }52}53 54std::unique_ptr<llm_graph_context> llama_model_gpt2::build_arch_graph(const llm_graph_params & params) const {55    return std::make_unique<graph>(*this, params);56}57 58llama_model_gpt2::graph::graph(const llama_model & model, const llm_graph_params & params) : llm_graph_context(params) {59    const int64_t n_embd_head = hparams.n_embd_head_v();60 61    GGML_ASSERT(n_embd_head == hparams.n_embd_head_k());62 63    ggml_tensor * cur;64    ggml_tensor * pos;65    ggml_tensor * inpL;66 67    inpL = build_inp_embd(model.tok_embd);68 69    // inp_pos - contains the positions70    ggml_tensor * inp_pos = build_inp_pos();71 72    auto * inp_attn = build_attn_inp_kv();73 74    pos = ggml_get_rows(ctx0, model.pos_embd, inp_pos);75    cb(pos, "pos_embd", -1);76 77    inpL = ggml_add(ctx0, inpL, pos);78    cb(inpL, "inpL", -1);79 80    ggml_tensor * inp_out_ids = build_inp_out_ids();81 82    for (int il = 0; il < n_layer; ++il) {83        cur = build_norm(inpL,84                model.layers[il].attn_norm,85                model.layers[il].attn_norm_b,86                LLM_NORM, il);87        cb(cur, "attn_norm", il);88 89        // self-attention90        {91            auto [Qcur, Kcur, Vcur] = build_qkv(model.layers[il], cur,92                    n_embd_head, n_head, n_head_kv, il);93 94            cur = build_attn(inp_attn,95                    model.layers[il].wo, model.layers[il].wo_b, model.layers[il].wo_s,96                    Qcur, Kcur, Vcur, nullptr, nullptr, nullptr, 1.0f/sqrtf(float(n_embd_head)), il);97        }98 99        if (il == n_layer - 1 && inp_out_ids) {100            cur  = ggml_get_rows(ctx0,  cur, inp_out_ids);101            inpL = ggml_get_rows(ctx0, inpL, inp_out_ids);102        }103 104        // add the input105        ggml_tensor * ffn_inp = ggml_add(ctx0, cur, inpL);106        cb(ffn_inp, "ffn_inp", il);107 108        // FF109        {110            cur = build_norm(ffn_inp,111                    model.layers[il].ffn_norm,112                    model.layers[il].ffn_norm_b,113                    LLM_NORM, il);114            cb(cur, "ffn_norm", il);115 116            cur = build_ffn(cur,117                    model.layers[il].ffn_up,   model.layers[il].ffn_up_b,   NULL,118                    NULL,                      NULL,                        NULL,119                    model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL,120                    NULL,121                    LLM_FFN_GELU, LLM_FFN_SEQ, il);122            cb(cur, "ffn_out", il);123        }124 125        cur = ggml_add(ctx0, cur, ffn_inp);126 127        cur = build_cvec(cur, il);128        cb(cur, "l_out", il);129 130        // input for next layer131        inpL = cur;132    }133 134    cur = build_norm(inpL,135            model.output_norm,136            model.output_norm_b,137            LLM_NORM, -1);138 139    cb(cur, "result_norm", -1);140    res->t_embd = cur;141 142    cur = build_lora_mm(model.output, cur, model.output_s);143 144    cb(cur, "result_output", -1);145    res->t_logits = cur;146 147    ggml_build_forward_expand(gf, cur);148}149