echodict/llama.cpp

1#include "models.h"2 3template <bool iswa>4llm_build_plamo3<iswa>::llm_build_plamo3(const llama_model & model, const llm_graph_params & params) :5    llm_graph_context(params) {6    const int64_t head_dim_q = hparams.n_embd_head_k();7    const int64_t head_dim_v = hparams.n_embd_head_v();8 9    ggml_tensor * cur;10    ggml_tensor * inpL = build_inp_embd(model.tok_embd);11    ggml_tensor * inp_pos = build_inp_pos();12 13    using inp_attn_type = std::conditional_t<iswa, llm_graph_input_attn_kv_iswa, llm_graph_input_attn_kv>;14    inp_attn_type * inp_attn = nullptr;15 16    if constexpr (iswa) {17        inp_attn = build_attn_inp_kv_iswa();18    } else {19        inp_attn = build_attn_inp_kv();20    }21 22    ggml_tensor * inp_out_ids = build_inp_out_ids();23 24    for (int il = 0; il < n_layer; ++il) {25        ggml_tensor * residual = inpL;26 27        float freq_base_l  = 0.0f;28        float freq_scale_l = 0.0f;29        if constexpr (iswa) {30            freq_base_l  = model.get_rope_freq_base (cparams, il);31            freq_scale_l = model.get_rope_freq_scale(cparams, il);32        } else {33            freq_base_l  = freq_base;34            freq_scale_l = freq_scale;35        }36 37        cur = build_norm(inpL, model.layers[il].attn_norm, NULL, LLM_NORM_RMS, il);38        cb(cur, "attn_norm", il);39 40        ggml_tensor * qkv = build_lora_mm(model.layers[il].wqkv, cur);41        cb(cur, "wqkv", il);42 43        const int32_t n_head    = hparams.n_head(il);44        const int32_t n_head_kv = hparams.n_head_kv(il);45 46        const int64_t q_offset = 0;47        const int64_t k_offset = head_dim_q * n_head;48        const int64_t v_offset = k_offset + head_dim_q * n_head_kv;49 50        ggml_tensor * Qcur = ggml_view_3d(ctx0, qkv, head_dim_q, n_head, n_tokens,51                head_dim_q * sizeof(float), qkv->nb[1], q_offset * ggml_element_size(qkv));52        ggml_tensor * Kcur = ggml_view_3d(ctx0, qkv, head_dim_q, n_head_kv, n_tokens,53                head_dim_q * sizeof(float), qkv->nb[1], k_offset * ggml_element_size(qkv));54        ggml_tensor * Vcur = ggml_view_3d(ctx0, qkv, head_dim_v, n_head_kv, n_tokens,55                head_dim_v * sizeof(float), qkv->nb[1], v_offset * ggml_element_size(qkv));56 57        cb(Qcur, "Qcur", il);58        cb(Kcur, "Kcur", il);59        cb(Vcur, "Vcur", il);60 61        Qcur = build_norm(Qcur, model.layers[il].attn_q_norm, NULL, LLM_NORM_RMS, il);62        cb(Qcur, "attn_q_norm", il);63        Kcur = build_norm(Kcur, model.layers[il].attn_k_norm, NULL, LLM_NORM_RMS, il);64        cb(Kcur, "attn_k_norm", il);65 66        Qcur = ggml_rope_ext(ctx0, Qcur, inp_pos, nullptr,67                n_rot, rope_type, n_ctx_orig, freq_base_l, freq_scale_l,68                ext_factor, attn_factor, beta_fast, beta_slow);69        Kcur = ggml_rope_ext(ctx0, Kcur, inp_pos, nullptr,70                n_rot, rope_type, n_ctx_orig, freq_base_l, freq_scale_l,71                ext_factor, attn_factor, beta_fast, beta_slow);72 73        const float attn_scale = 1.0f / sqrtf(float(head_dim_q));74 75        cur = build_attn(inp_attn,76                model.layers[il].wo, NULL, model.layers[il].wo_s,77                Qcur, Kcur, Vcur, nullptr, nullptr, nullptr, attn_scale, il);78        cb(cur, "attn_out", il);79 80        if (il == n_layer - 1 && inp_out_ids) {81            cur      = ggml_get_rows(ctx0, cur, inp_out_ids);82            residual = ggml_get_rows(ctx0, residual, inp_out_ids);83        }84 85        cur = build_norm(cur, model.layers[il].attn_post_norm, NULL, LLM_NORM_RMS, il);86        cb(cur, "attn_post_norm", il);87 88        cur = ggml_add(ctx0, cur, residual);89        cb(cur, "attn_residual", il);90 91        residual = cur;92 93        cur = build_norm(cur, model.layers[il].ffn_norm, NULL, LLM_NORM_RMS, il);94        cb(cur, "ffn_norm", il);95 96        cur = build_ffn(cur,97                model.layers[il].ffn_up,   NULL, NULL,98                NULL,                      NULL, NULL,99                model.layers[il].ffn_down, NULL, NULL,100                NULL,101                LLM_FFN_SWIGLU, LLM_FFN_SEQ, il);102        cb(cur, "ffn_out", il);103 104        cur = build_norm(cur, model.layers[il].ffn_post_norm, NULL, LLM_NORM_RMS, il);105        cb(cur, "ffn_post_norm", il);106 107        cur = ggml_add(ctx0, cur, residual);108        cb(cur, "ffn_residual", il);109 110        cur = build_cvec(cur, il);111        cb(cur, "l_out", il);112 113        // input for next layer114        inpL = cur;115    }116 117    cur = inpL;118 119    cur = build_norm(cur, model.output_norm, NULL, LLM_NORM_RMS, -1);120    res->t_embd = cur;121 122    cur = build_lora_mm(model.output, cur);123    res->t_logits = cur;124 125    ggml_build_forward_expand(gf, cur);126}127 128// Explicit template instantiations129template struct llm_build_plamo3<false>;130template struct llm_build_plamo3<true>;131