| 3 | |
| 4 | |
| 5 | llm_build_mpt::llm_build_mpt(const llama_model & model, const llm_graph_params & params) : llm_graph_context(params) { |
| 6 | const int64_t n_embd_head = hparams.n_embd_head_v; |
| 7 | const int64_t n_embd_gqa = hparams.n_embd_v_gqa(); |
| 8 | |
| 9 | GGML_ASSERT(n_embd_head == hparams.n_embd_head_k); |
| 10 | |
| 11 | ggml_tensor * cur; |
| 12 | ggml_tensor * pos; |
| 13 | ggml_tensor * inpL; |
| 14 | |
| 15 | inpL = build_inp_embd(model.tok_embd); |
| 16 | |
| 17 | auto * inp_attn = build_attn_inp_kv(); |
| 18 | |
| 19 | if (model.pos_embd) { |
| 20 | // inp_pos - contains the positions |
| 21 | ggml_tensor * inp_pos = build_inp_pos(); |
| 22 | pos = ggml_get_rows(ctx0, model.pos_embd, inp_pos); |
| 23 | cb(pos, "pos_embd", -1); |
| 24 | |
| 25 | inpL = ggml_add(ctx0, inpL, pos); |
| 26 | cb(inpL, "inpL", -1); |
| 27 | } |
| 28 | |
| 29 | ggml_tensor * inp_out_ids = build_inp_out_ids(); |
| 30 | |
| 31 | for (int il = 0; il < n_layer; ++il) { |
| 32 | ggml_tensor * attn_norm; |
| 33 | |
| 34 | attn_norm = build_norm(inpL, model.layers[il].attn_norm, model.layers[il].attn_norm_b, LLM_NORM, il); |
| 35 | cb(attn_norm, "attn_norm", il); |
| 36 | |
| 37 | // self-attention |
| 38 | { |
| 39 | cur = attn_norm; |
| 40 | |
| 41 | cur = build_lora_mm(model.layers[il].wqkv, cur); |
| 42 | cb(cur, "wqkv", il); |
| 43 | |
| 44 | if (model.layers[il].bqkv) { |
| 45 | cur = ggml_add(ctx0, cur, model.layers[il].bqkv); |
| 46 | cb(cur, "bqkv", il); |
| 47 | } |
| 48 | |
| 49 | if (hparams.f_clamp_kqv > 0.0f) { |
| 50 | cur = ggml_clamp(ctx0, cur, -hparams.f_clamp_kqv, hparams.f_clamp_kqv); |
| 51 | cb(cur, "wqkv_clamped", il); |
| 52 | } |
| 53 | |
| 54 | ggml_tensor * Qcur = ggml_view_3d(ctx0, cur, n_embd_head, n_head, n_tokens, n_embd_head * sizeof(float), |
| 55 | cur->nb[1], 0 * sizeof(float) * (n_embd)); |
| 56 | ggml_tensor * Kcur = ggml_view_3d(ctx0, cur, n_embd_head, n_head_kv, n_tokens, n_embd_head * sizeof(float), |
| 57 | cur->nb[1], 1 * sizeof(float) * (n_embd)); |
| 58 | ggml_tensor * Vcur = ggml_view_3d(ctx0, cur, n_embd_head, n_head_kv, n_tokens, n_embd_head * sizeof(float), |
| 59 | cur->nb[1], 1 * sizeof(float) * (n_embd + n_embd_gqa)); |
| 60 | |
| 61 | // Q/K Layernorm |
| 62 | if (model.layers[il].attn_q_norm) { |
nothing calls this directly
no test coverage detected