1#include "models.h"
  2
  3llm_build_maincoder::llm_build_maincoder(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 == hparams.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 positions
 15    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        ggml_tensor * inpSA = inpL;
 23
 24        // norm
 25        cur = build_norm(inpL,
 26                model.layers[il].attn_norm, NULL,
 27                LLM_NORM_RMS, il);
 28        cb(cur, "attn_norm", il);
 29
 30        // self-attention
 31        {
 32            // compute Q and K and RoPE them
 33            ggml_tensor * Qcur = build_lora_mm(model.layers[il].wq, cur);
 34            cb(Qcur, "Qcur", il);
 35
 36            ggml_tensor * Kcur = build_lora_mm(model.layers[il].wk, cur);
 37            cb(Kcur, "Kcur", il);
 38
 39            ggml_tensor * Vcur = build_lora_mm(model.layers[il].wv, cur);
 40            cb(Vcur, "Vcur", il);
 41
 42            Qcur = ggml_reshape_3d(ctx0, Qcur, n_embd_head, n_head,    n_tokens);
 43            Kcur = ggml_reshape_3d(ctx0, Kcur, n_embd_head, n_head_kv, n_tokens);
 44            Vcur = ggml_reshape_3d(ctx0, Vcur, n_embd_head, n_head_kv, n_tokens);
 45
 46            Qcur = ggml_rope_ext(
 47                    ctx0, Qcur, inp_pos, nullptr,
 48                    n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,
 49                    ext_factor, attn_factor, beta_fast, beta_slow
 50                    );
 51
 52            Kcur = ggml_rope_ext(
 53                    ctx0, Kcur, inp_pos, nullptr,
 54                    n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,
 55                    ext_factor, attn_factor, beta_fast, beta_slow
 56                    );
 57
 58            Qcur = build_norm(Qcur, model.layers[il].attn_q_norm, NULL, LLM_NORM_RMS, il);
 59            cb(Qcur, "Qcur_normed", il);
 60
 61            Kcur = build_norm(Kcur, model.layers[il].attn_k_norm, NULL, LLM_NORM_RMS, il);
 62            cb(Kcur, "Kcur_normed", il);
 63
 64            cb(Qcur, "Qcur", il);
 65            cb(Kcur, "Kcur", il);
 66            cb(Vcur, "Vcur", il);
 67
 68            cur = build_attn(inp_attn,
 69                    model.layers[il].wo, model.layers[il].bo,
 70                    Qcur, Kcur, Vcur, nullptr, nullptr, nullptr, 1.0f/sqrtf(float(n_embd_head)), il);
 71        }
 72        if (il == n_layer - 1 && inp_out_ids) {
 73            cur   = ggml_get_rows(ctx0,   cur, inp_out_ids);
 74            inpSA = ggml_get_rows(ctx0, inpSA, inp_out_ids);
 75        }
 76        ggml_tensor * ffn_inp = ggml_add(ctx0, cur, inpSA);
 77        cb(ffn_inp, "ffn_inp", il);
 78
 79        // feed-forward network
 80        cur = build_norm(ffn_inp,
 81                model.layers[il].ffn_norm, NULL,
 82                LLM_NORM_RMS, il);
 83        cb(cur, "ffn_norm", il);
 84
 85        cur = build_ffn(cur,
 86                model.layers[il].ffn_up,   NULL, NULL,
 87                model.layers[il].ffn_gate, NULL, NULL,
 88                model.layers[il].ffn_down, NULL, NULL,
 89                NULL,
 90                LLM_FFN_SILU, LLM_FFN_PAR, il);
 91        cb(cur, "ffn_out", il);
 92
 93        cur = ggml_add(ctx0, cur, ffn_inp);
 94
 95        cur = build_cvec(cur, il);
 96        cb(cur, "l_out", il);
 97
 98        // input for next layer
 99        inpL = cur;
100    }
101    cur = inpL;
102
103    cur = build_norm(cur,
104            model.output_norm, NULL,
105            LLM_NORM_RMS, -1);
106
107    cb(cur, "result_norm", -1);
108    res->t_embd = cur;
109
110    // lm_head
111    cur = build_lora_mm(model.output, cur);
112
113    cb(cur, "result_output", -1);
114    res->t_logits = cur;
115
116    ggml_build_forward_expand(gf, cur);
117}