jais.cpp 3.0 KB

1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950515253545556575859606162636465666768697071727374757677787980818283848586
  1. #include "models.h"
  2. llm_build_jais::llm_build_jais(const llama_model & model, const llm_graph_params & params) : llm_graph_context(params) {
  3. const int64_t n_embd_head = hparams.n_embd_head_v;
  4. const int64_t n_embd_gqa = hparams.n_embd_v_gqa();
  5. GGML_ASSERT(n_embd_head == hparams.n_embd_head_k);
  6. ggml_tensor * cur;
  7. ggml_tensor * inpL;
  8. inpL = build_inp_embd(model.tok_embd);
  9. auto * inp_attn = build_attn_inp_kv();
  10. ggml_tensor * inp_out_ids = build_inp_out_ids();
  11. for (int il = 0; il < n_layer; ++il) {
  12. cur = build_norm(inpL,
  13. model.layers[il].attn_norm,
  14. model.layers[il].attn_norm_b,
  15. LLM_NORM, il);
  16. cb(cur, "attn_norm", il);
  17. // self-attention
  18. {
  19. cur = build_lora_mm(model.layers[il].wqkv, cur);
  20. cb(cur, "wqkv", il);
  21. cur = ggml_add(ctx0, cur, model.layers[il].bqkv);
  22. cb(cur, "bqkv", il);
  23. ggml_tensor * Qcur = ggml_view_3d(ctx0, cur, n_embd_head, n_head, n_tokens, n_embd_head*sizeof(float), cur->nb[1], 0*cur->nb[0]*(n_embd));
  24. ggml_tensor * Kcur = ggml_view_3d(ctx0, cur, n_embd_head, n_head_kv, n_tokens, n_embd_head*sizeof(float), cur->nb[1], 1*cur->nb[0]*(n_embd));
  25. ggml_tensor * Vcur = ggml_view_3d(ctx0, cur, n_embd_head, n_head_kv, n_tokens, n_embd_head*sizeof(float), cur->nb[1], 1*cur->nb[0]*(n_embd + n_embd_gqa));
  26. cb(Qcur, "Qcur", il);
  27. cb(Kcur, "Kcur", il);
  28. cb(Vcur, "Vcur", il);
  29. cur = build_attn(inp_attn,
  30. model.layers[il].wo, model.layers[il].bo,
  31. Qcur, Kcur, Vcur, nullptr, nullptr, nullptr, 1.0f/float(n_embd_head), il);
  32. }
  33. if (il == n_layer - 1 && inp_out_ids) {
  34. cur = ggml_get_rows(ctx0, cur, inp_out_ids);
  35. inpL = ggml_get_rows(ctx0, inpL, inp_out_ids);
  36. }
  37. // add the input
  38. ggml_tensor * ffn_inp = ggml_add(ctx0, cur, inpL);
  39. cb(ffn_inp, "ffn_inp", il);
  40. // FF
  41. {
  42. cur = build_norm(ffn_inp,
  43. model.layers[il].ffn_norm,
  44. model.layers[il].ffn_norm_b,
  45. LLM_NORM, il);
  46. cb(cur, "ffn_norm", il);
  47. cur = build_ffn(cur,
  48. model.layers[il].ffn_up, model.layers[il].ffn_up_b, NULL,
  49. model.layers[il].ffn_gate, model.layers[il].ffn_gate_b, NULL,
  50. model.layers[il].ffn_down, model.layers[il].ffn_down_b, NULL,
  51. NULL,
  52. LLM_FFN_SILU, LLM_FFN_PAR, il);
  53. cb(cur, "ffn_out", il);
  54. }
  55. inpL = ggml_add(ctx0, cur, ffn_inp);
  56. cb(inpL, "l_out", il);
  57. }
  58. cur = build_norm(inpL,
  59. model.output_norm,
  60. model.output_norm_b,
  61. LLM_NORM, -1);
  62. cb(cur, "result_norm", -1);
  63. res->t_embd = cur;
  64. cur = build_lora_mm(model.output, cur);
  65. cb(cur, "result_output", -1);
  66. res->t_logits = cur;
  67. ggml_build_forward_expand(gf, cur);
  68. }