Felipe97/llama-cpp-compiled

1#include "models.h"2 3void llama_model_bloom::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 24: type = LLM_TYPE_1B; break;8        case 30:9            switch (hparams.n_embd) {10                case 2560: type = LLM_TYPE_3B; break;11                case 4096: type = LLM_TYPE_7B; break;12                default: type = LLM_TYPE_UNKNOWN;13            } break;14        default: type = LLM_TYPE_UNKNOWN;15    }16 17    // TODO: become GGUF KV parameter18    hparams.f_max_alibi_bias = 8.0f;19}20 21void llama_model_bloom::load_arch_tensors(llama_model_loader &) {22    LLAMA_LOAD_LOCALS;23 24    tok_embd   = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD,      "weight"), {n_embd, n_vocab}, 0);25    tok_norm   = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD_NORM, "weight", 0), {n_embd}, 0);26    tok_norm_b = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD_NORM, "bias",   0), {n_embd}, 0);27 28    // output29    output_norm   = create_tensor(tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd}, 0);30    output_norm_b = create_tensor(tn(LLM_TENSOR_OUTPUT_NORM, "bias"),   {n_embd}, 0);31    output        = create_tensor(tn(LLM_TENSOR_OUTPUT,      "weight"), {n_embd, n_vocab}, TENSOR_NOT_REQUIRED);32 33    // if output is NULL, init from the input tok embed34    if (output == NULL) {35        output = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, TENSOR_DUPLICATED);36    }37 38    for (int i = 0; i < n_layer; ++i) {39        auto & layer = layers[i];40 41        layer.attn_norm   = create_tensor(tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd}, 0);42        layer.attn_norm_b = create_tensor(tn(LLM_TENSOR_ATTN_NORM, "bias",   i), {n_embd}, 0);43 44        layer.wqkv = create_tensor(tn(LLM_TENSOR_ATTN_QKV, "weight", i), {n_embd, n_embd + 2*n_embd_gqa}, 0);45        layer.wqkv_b = create_tensor(tn(LLM_TENSOR_ATTN_QKV, "bias", i), {n_embd + 2*n_embd_gqa}, 0);46 47        layer.wo   = create_tensor(tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd}, 0);48        layer.wo_b = create_tensor(tn(LLM_TENSOR_ATTN_OUT, "bias",   i), {n_embd}, 0);49 50        layer.ffn_norm   = create_tensor(tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd}, 0);51        layer.ffn_norm_b = create_tensor(tn(LLM_TENSOR_FFN_NORM, "bias",   i), {n_embd}, 0);52 53        layer.ffn_down   = create_tensor(tn(LLM_TENSOR_FFN_DOWN, "weight", i), {n_ff, n_embd}, 0);54        layer.ffn_down_b = create_tensor(tn(LLM_TENSOR_FFN_DOWN, "bias",   i), {n_embd}, 0);55 56        layer.ffn_up     = create_tensor(tn(LLM_TENSOR_FFN_UP, "weight", i), {n_embd, n_ff}, 0);57        layer.ffn_up_b   = create_tensor(tn(LLM_TENSOR_FFN_UP, "bias",   i), {n_ff}, 0);58    }59}60 61std::unique_ptr<llm_graph_context> llama_model_bloom::build_arch_graph(const llm_graph_params & params) const {62    return std::make_unique<graph>(*this, params);63}64 65llama_model_bloom::graph::graph(const llama_model & model, const llm_graph_params & params) : llm_graph_context(params) {66    const int64_t n_embd_head = hparams.n_embd_head_v();67 68    GGML_ASSERT(n_embd_head == hparams.n_embd_head_k());69 70    ggml_tensor * cur;71    ggml_tensor * inpL;72 73    inpL = build_inp_embd(model.tok_embd);74 75    auto * inp_attn = build_attn_inp_kv();76 77    inpL = build_norm(inpL,78            model.tok_norm,79            model.tok_norm_b,80            LLM_NORM, 0);81    cb(inpL, "inp_norm", 0);82 83    ggml_tensor * inp_out_ids = build_inp_out_ids();84 85    for (int il = 0; il < n_layer; ++il) {86        cur = build_norm(inpL,87                model.layers[il].attn_norm,88                model.layers[il].attn_norm_b,89                LLM_NORM, il);90        cb(cur, "attn_norm", il);91 92        // self-attention93        {94            auto [Qcur, Kcur, Vcur] = build_qkv(model.layers[il], cur,95                    n_embd_head, n_head, n_head_kv, il);96 97            cur = build_attn(inp_attn,98                    model.layers[il].wo, model.layers[il].wo_b, model.layers[il].wo_s,99                    Qcur, Kcur, Vcur, nullptr, nullptr, nullptr, 1.0f/sqrtf(float(n_embd_head)), il);100        }101 102        if (il == n_layer - 1 && inp_out_ids) {103            cur  = ggml_get_rows(ctx0,  cur, inp_out_ids);104            inpL = ggml_get_rows(ctx0, inpL, inp_out_ids);105        }106 107        // Add the input108        ggml_tensor * ffn_inp = ggml_add(ctx0, cur, inpL);109        cb(ffn_inp, "ffn_inp", il);110 111        // FF112        {113            cur = build_norm(ffn_inp,114                    model.layers[il].ffn_norm,115                    model.layers[il].ffn_norm_b,116                    LLM_NORM, il);117            cb(cur, "ffn_norm", il);118 119            cur = build_ffn(cur,120                    model.layers[il].ffn_up,   model.layers[il].ffn_up_b,   NULL,121                    NULL,                      NULL,                        NULL,122                    model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL,123                    NULL,124                    LLM_FFN_GELU, LLM_FFN_SEQ, il);125            cb(cur, "ffn_out", il);126        }127 128        cur = ggml_add(ctx0, cur, ffn_inp);129 130        cur = build_cvec(cur, il);131        cb(cur, "l_out", il);132 133        // input for next layer134        inpL = cur;135    }136 137    cur = build_norm(inpL,138            model.output_norm,139            model.output_norm_b,140            LLM_NORM, -1);141 142    cb(cur, "result_norm", -1);143    res->t_embd = cur;144 145    cur = build_lora_mm(model.output, cur, model.output_s);146 147    cb(cur, "result_output", -1);148    res->t_logits = cur;149 150    ggml_build_forward_expand(gf, cur);151}152