Felipe97/llama-cpp-compiled

1#include "models.h"2 3void llama_model_mamba::load_arch_hparams(llama_model_loader & ml) {4    ml.get_key(LLM_KV_SSM_CONV_KERNEL,    hparams.ssm_d_conv);5    ml.get_key(LLM_KV_SSM_INNER_SIZE,     hparams.ssm_d_inner);6    ml.get_key(LLM_KV_SSM_STATE_SIZE,     hparams.ssm_d_state);7    ml.get_key(LLM_KV_SSM_TIME_STEP_RANK, hparams.ssm_dt_rank);8    ml.get_key(LLM_KV_SSM_DT_B_C_RMS,     hparams.ssm_dt_b_c_rms, false);9 10    ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, hparams.f_norm_rms_eps);11 12    switch (hparams.n_layer()) {13        case 24:14            switch (hparams.n_embd) {15                case 768: type = LLM_TYPE_SMALL; break;16                default: type = LLM_TYPE_UNKNOWN;17            } break;18        case 48:19            switch (hparams.n_embd) {20                case 1024: type = LLM_TYPE_MEDIUM; break;21                case 1536: type = LLM_TYPE_LARGE; break;22                case 2048: type = LLM_TYPE_XL; break;23                default:   type = LLM_TYPE_UNKNOWN;24            } break;25        case 64:26            switch (hparams.n_embd) {27                case 2560: type = LLM_TYPE_3B; break;28                default: type = LLM_TYPE_UNKNOWN;29            } break;30        default: type = LLM_TYPE_UNKNOWN;31    }32}33 34void llama_model_mamba::load_arch_tensors(llama_model_loader &) {35    LLAMA_LOAD_LOCALS;36 37    const int64_t d_conv  = hparams.ssm_d_conv;38    const int64_t d_inner = hparams.ssm_d_inner;39    const int64_t d_state = hparams.ssm_d_state;40    const int64_t dt_rank = hparams.ssm_dt_rank;41 42    // only an expansion factor of 2 is supported for now43    if (2 * n_embd != d_inner) {44        throw std::runtime_error("only an expansion factor of 2 is supported for now");45    }46 47    tok_embd = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, 0);48 49    // output50    output_norm = create_tensor(tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd}, 0);51 52    output = create_tensor(tn(LLM_TENSOR_OUTPUT, "weight"), {n_embd, n_vocab}, TENSOR_NOT_REQUIRED);53    // if output is NULL, init from the input tok embed, duplicated to allow offloading54    if (output == NULL) {55        output = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, TENSOR_DUPLICATED);56    }57 58    for (int i = 0; i < n_layer; ++i) {59        auto & layer = layers[i];60 61        // norm62        layer.attn_norm = create_tensor(tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd}, 0);63 64        layer.ssm_in = create_tensor(tn(LLM_TENSOR_SSM_IN, "weight", i), {n_embd, 2*d_inner}, 0);65 66        layer.ssm_conv1d = create_tensor(tn(LLM_TENSOR_SSM_CONV1D, "weight", i), {d_conv, d_inner}, 0);67        layer.ssm_conv1d_b = create_tensor(tn(LLM_TENSOR_SSM_CONV1D, "bias", i), {d_inner}, 0);68 69        layer.ssm_x = create_tensor(tn(LLM_TENSOR_SSM_X, "weight", i), {d_inner, dt_rank + 2*d_state}, 0);70 71        layer.ssm_dt = create_tensor(tn(LLM_TENSOR_SSM_DT, "weight", i), {dt_rank, d_inner}, 0);72        layer.ssm_dt_b = create_tensor(tn(LLM_TENSOR_SSM_DT, "bias", i), {d_inner}, 0);73 74        // no "weight" suffix for these75        layer.ssm_a = create_tensor(tn(LLM_TENSOR_SSM_A, i), {d_state, d_inner}, 0);76        layer.ssm_d = create_tensor(tn(LLM_TENSOR_SSM_D, i), {d_inner}, 0);77 78        // out_proj79        layer.ssm_out = create_tensor(tn(LLM_TENSOR_SSM_OUT, "weight", i), {d_inner, n_embd}, 0);80    }81}82 83std::unique_ptr<llm_graph_context> llama_model_mamba::build_arch_graph(const llm_graph_params & params) const {84    return std::make_unique<graph>(*this, params);85}86 87llama_model_mamba::graph::graph(const llama_model & model, const llm_graph_params & params) : llm_build_mamba_base(params) {88    ggml_tensor * cur;89    ggml_tensor * inpL;90 91    // {n_embd, n_tokens}92    inpL = build_inp_embd(model.tok_embd);93 94    auto * rs_inp = build_rs_inp();95 96    ggml_tensor * inp_out_ids = build_inp_out_ids();97 98    for (int il = 0; il < n_layer; ++il) {99        // norm100        cur = build_norm(inpL, model.layers[il].attn_norm, NULL, LLM_NORM_RMS, il);101        cb(cur, "attn_norm", il);102 103        if (model.arch == LLM_ARCH_MAMBA2) {104            cur = build_mamba2_layer(rs_inp, cur, model, ubatch, il);105        } else {106            cur = build_mamba_layer(rs_inp, cur, model, ubatch, il);107        }108 109        if (il == n_layer - 1 && inp_out_ids) {110            cur  = ggml_get_rows(ctx0, cur, inp_out_ids);111            inpL = ggml_get_rows(ctx0, inpL, inp_out_ids);112        }113 114        // residual115        cur = ggml_add(ctx0, cur, inpL);116 117        cur = build_cvec(cur, il);118        cb(cur, "l_out", il);119 120        // input for next layer121        inpL = cur;122    }123 124    // final rmsnorm125    cur = build_norm(inpL, model.output_norm, NULL, LLM_NORM_RMS, -1);126 127    cb(cur, "result_norm", -1);128    res->t_embd = cur;129 130    // lm_head131    cur = build_lora_mm(model.output, cur, model.output_s);132 133    cb(cur, "result_output", -1);134    res->t_logits = cur;135 136    ggml_build_forward_expand(gf, cur);137}138