llama-hparams.cpp 2.5 KB

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  1. #include "llama-hparams.h"
  2. #include "ggml.h"
  3. void llama_hparams::set_swa_pattern(uint32_t n_pattern) {
  4. for (uint32_t il = 0; il < n_layer; ++il) {
  5. swa_layers[il] = n_pattern == 0 || (il % n_pattern < (n_pattern - 1));
  6. }
  7. }
  8. bool llama_hparams::is_swa_any() const {
  9. for (uint32_t il = 0; il < n_layer; ++il) {
  10. if (swa_layers[il]) {
  11. return true;
  12. }
  13. }
  14. return false;
  15. }
  16. uint32_t llama_hparams::n_head(uint32_t il) const {
  17. if (il < n_layer) {
  18. return n_head_arr[il];
  19. }
  20. GGML_ABORT("fatal error");
  21. }
  22. uint32_t llama_hparams::n_head_kv(uint32_t il) const {
  23. if (il < n_layer) {
  24. return n_head_kv_arr[il];
  25. }
  26. GGML_ABORT("fatal error");
  27. }
  28. uint32_t llama_hparams::n_ff(uint32_t il) const {
  29. if (il < n_layer) {
  30. return n_ff_arr[il];
  31. }
  32. GGML_ABORT("fatal error");
  33. }
  34. uint32_t llama_hparams::n_gqa(uint32_t il) const {
  35. const uint32_t n_head = this->n_head(il);
  36. const uint32_t n_head_kv = this->n_head_kv(il);
  37. if (n_head_kv == 0) {
  38. return 0;
  39. }
  40. return n_head/n_head_kv;
  41. }
  42. uint32_t llama_hparams::n_embd_k_gqa(uint32_t il) const {
  43. const uint32_t n_head_kv = this->n_head_kv(il);
  44. return n_embd_head_k * n_head_kv;
  45. }
  46. uint32_t llama_hparams::n_embd_v_gqa(uint32_t il) const {
  47. const uint32_t n_head_kv = this->n_head_kv(il);
  48. return n_embd_head_v * n_head_kv;
  49. }
  50. uint32_t llama_hparams::n_embd_r() const {
  51. if (wkv_head_size != 0) {
  52. // for RWKV models
  53. return token_shift_count * n_embd;
  54. }
  55. if (n_shortconv_l_cache != 0) {
  56. // for LFM2 models
  57. return n_embd * (n_shortconv_l_cache - 1);
  58. }
  59. // TODO: maybe support other convolution strides than 1
  60. // NOTE: since the first column of the conv_state is shifted out each time, it's not actually needed
  61. // Corresponds to Mamba's conv_states size
  62. return (ssm_d_conv > 0 ? ssm_d_conv - 1 : 0) * (ssm_d_inner + 2*ssm_n_group*ssm_d_state);
  63. }
  64. uint32_t llama_hparams::n_embd_s() const {
  65. if (wkv_head_size != 0) {
  66. // corresponds to RWKV's wkv_states size
  67. return n_embd * wkv_head_size;
  68. }
  69. // corresponds to Mamba's ssm_states size
  70. return ssm_d_state * ssm_d_inner;
  71. }
  72. bool llama_hparams::is_recurrent(uint32_t il) const {
  73. return recurrent_layer_arr[il];
  74. }
  75. uint32_t llama_hparams::n_pos_per_embd() const {
  76. return rope_type == LLAMA_ROPE_TYPE_MROPE ? 4 : 1;
  77. }
  78. bool llama_hparams::is_swa(uint32_t il) const {
  79. if (il < n_layer) {
  80. return swa_layers[il];
  81. }
  82. GGML_ABORT("fatal error");
  83. }