echodict/llama.cpp

1#include "models.h"2 3llm_build_codeshell::llm_build_codeshell(const llama_model & model, const llm_graph_params & params) : llm_graph_context(params) {4    const int64_t n_embd_head = hparams.n_embd_head_v();5 6    GGML_ASSERT(n_embd_head == hparams.n_embd_head_k());7    GGML_ASSERT(n_embd_head == n_rot);8 9    ggml_tensor * cur;10    ggml_tensor * inpL;11 12    inpL = build_inp_embd(model.tok_embd);13 14    // inp_pos - contains the positions15    ggml_tensor * inp_pos = build_inp_pos();16 17    auto * inp_attn = build_attn_inp_kv();18 19    ggml_tensor * inp_out_ids = build_inp_out_ids();20 21    for (int il = 0; il < n_layer; ++il) {22        cur = build_norm(inpL,23                model.layers[il].attn_norm,24                model.layers[il].attn_norm_b,25                LLM_NORM, il);26        cb(cur, "attn_norm", il);27 28        // self-attention29        {30            auto [Qcur, Kcur, Vcur] = build_qkv(model.layers[il], cur,31                    n_embd_head, n_head, n_head_kv, il);32 33            Qcur = ggml_rope_ext(34                    ctx0, Qcur, inp_pos, nullptr,35                    n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,36                    ext_factor, attn_factor, beta_fast, beta_slow37                    );38 39            Kcur = ggml_rope_ext(40                    ctx0, Kcur, inp_pos, nullptr,41                    n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,42                    ext_factor, attn_factor, beta_fast, beta_slow43                    );44 45            cb(Qcur, "Qcur", il);46            cb(Kcur, "Kcur", il);47            cb(Vcur, "Vcur", il);48 49            cur = build_attn(inp_attn,50                    model.layers[il].wo, model.layers[il].wo_b, model.layers[il].wo_s,51                    Qcur, Kcur, Vcur, nullptr, nullptr, nullptr, 1.0f/sqrtf(float(n_embd_head)), il);52        }53 54        if (il == n_layer - 1 && inp_out_ids) {55            cur  = ggml_get_rows(ctx0,  cur, inp_out_ids);56            inpL = ggml_get_rows(ctx0, inpL, inp_out_ids);57        }58 59        // add the input60        ggml_tensor * ffn_inp = ggml_add(ctx0, cur, inpL);61        cb(ffn_inp, "ffn_inp", il);62 63        // FF64        {65            cur = build_norm(ffn_inp,66                    model.layers[il].ffn_norm,67                    model.layers[il].ffn_norm_b,68                    LLM_NORM, il);69            cb(cur, "ffn_norm", il);70 71            cur = build_ffn(cur,72                    model.layers[il].ffn_up,   model.layers[il].ffn_up_b,   NULL,73                    NULL,                      NULL,                        NULL,74                    model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL,75                    NULL,76                    LLM_FFN_GELU, LLM_FFN_SEQ, il);77            cb(cur, "ffn_out", il);78        }79 80        cur = ggml_add(ctx0, cur, ffn_inp);81 82        cur = build_cvec(cur, il);83        cb(cur, "l_out", il);84 85        // input for next layer86        inpL = cur;87    }88 89    cur = build_norm(inpL,90            model.output_norm,91            model.output_norm_b,92            LLM_NORM, -1);93 94    cb(cur, "result_norm", -1);95    res->t_embd = cur;96 97    cur = build_lora_mm(model.output, cur);98 99    cb(cur, "result_output", -1);100    res->t_logits = cur;101 102    ggml_build_forward_expand(gf, cur);103}104