1#include "models.h"
  2
  3llm_build_openelm::llm_build_openelm(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
  8    ggml_tensor * cur;
  9    ggml_tensor * inpL;
 10    inpL = build_inp_embd(model.tok_embd);
 11
 12    // inp_pos - contains the positions
 13    ggml_tensor * inp_pos = build_inp_pos();
 14
 15    auto * inp_attn = build_attn_inp_kv();
 16
 17    ggml_tensor * inp_out_ids = build_inp_out_ids();
 18
 19    for (int il = 0; il < n_layer; ++il) {
 20        const int64_t n_head    = hparams.n_head(il);
 21        const int64_t n_head_kv = hparams.n_head_kv(il);
 22        const int64_t n_head_qkv = 2*n_head_kv + n_head;
 23
 24        cur = inpL;
 25        ggml_tensor * residual = cur;
 26
 27        // norm
 28        cur = build_norm(inpL,
 29                model.layers[il].attn_norm, NULL,
 30                LLM_NORM_RMS, il);
 31        cb(cur, "attn_norm", il);
 32
 33        // self-attention
 34        {
 35            cur = build_lora_mm(model.layers[il].wqkv, cur);
 36            cb(cur, "wqkv", il);
 37
 38            cur = ggml_reshape_3d(ctx0, cur, n_embd_head_k, n_head_qkv, n_tokens);
 39
 40            ggml_tensor * Qcur = ggml_view_3d(ctx0, cur, n_embd_head, n_head,    n_tokens, cur->nb[1], cur->nb[2], 0);
 41            cb(Qcur, "Qcur", il);
 42
 43            ggml_tensor * Kcur = ggml_view_3d(ctx0, cur, n_embd_head, n_head_kv, n_tokens, cur->nb[1], cur->nb[2], cur->nb[1]*n_head);
 44            cb(Kcur, "Kcur", il);
 45
 46            ggml_tensor * Vcur = ggml_view_3d(ctx0, cur, n_embd_head, n_head_kv, n_tokens, cur->nb[1], cur->nb[2], cur->nb[1]*(n_head+n_head_kv));
 47            cb(Vcur, "Vcur", il);
 48
 49            Qcur = build_norm(Qcur,
 50                    model.layers[il].attn_q_norm, NULL,
 51                    LLM_NORM_RMS, il);
 52            cb(Qcur, "Qcur", il);
 53
 54            Kcur = build_norm(Kcur,
 55                    model.layers[il].attn_k_norm, NULL,
 56                    LLM_NORM_RMS, il);
 57            cb(Kcur, "Kcur", il);
 58
 59            Qcur = ggml_rope_ext(
 60                    ctx0, Qcur, inp_pos, NULL,
 61                    n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,
 62                    ext_factor, attn_factor, beta_fast, beta_slow
 63                    );
 64
 65            Kcur = ggml_rope_ext(
 66                    ctx0, Kcur, inp_pos, NULL,
 67                    n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,
 68                    ext_factor, attn_factor, beta_fast, beta_slow
 69                    );
 70
 71            cb(Qcur, "Qcur", il);
 72            cb(Kcur, "Kcur", il);
 73            cb(Qcur, "Vcur", il);
 74
 75            cur = build_attn(inp_attn,
 76                    model.layers[il].wo, NULL,
 77                    Qcur, Kcur, Vcur, nullptr, nullptr, nullptr, 1.0f/sqrtf(float(n_embd_head)), il);
 78        }
 79        if (il == n_layer - 1 && inp_out_ids) {
 80            residual = ggml_get_rows(ctx0, residual, inp_out_ids);
 81            cur      = ggml_get_rows(ctx0, cur,      inp_out_ids);
 82        }
 83        ggml_tensor * ffn_inp = ggml_add(ctx0, residual, cur);
 84        cb(ffn_inp, "ffn_inp", il);
 85
 86        // feed-forward network
 87        {
 88            cur = build_norm(ffn_inp,
 89                    model.layers[il].ffn_norm, NULL,
 90                    LLM_NORM_RMS, il);
 91            cb(cur, "ffn_norm", il);
 92
 93            cur = build_ffn(cur,
 94                    model.layers[il].ffn_up,   NULL, NULL,
 95                    model.layers[il].ffn_gate, NULL, NULL,
 96                    model.layers[il].ffn_down, NULL, NULL,
 97                    NULL,
 98                    LLM_FFN_SILU, LLM_FFN_PAR, il);
 99            cb(cur, "ffn_out", il);
100        }
101        cur = ggml_add(ctx0, cur, ffn_inp);
102
103        cur = build_cvec(cur, il);
104        cb(cur, "l_out", il);
105
106        inpL = cur;
107    }
108    cur = inpL;
109
110    // norm
111    cur = build_norm(cur,
112            model.output_norm, NULL,
113            LLM_NORM_RMS, -1);
114
115    cb(cur, "result_norm", -1);
116    res->t_embd = cur;
117
118    cur = build_lora_mm(model.output, cur);
119
120    cb(cur, "result_output", -1);
121    res->t_logits = cur;
122
123    ggml_build_forward_expand(gf, cur);
124}