mirror of https://github.com/ollama/ollama.git
226 lines
5.3 KiB
C++
226 lines
5.3 KiB
C++
#include "llama-hparams.h"
|
|
|
|
#include "ggml.h"
|
|
#include <cassert>
|
|
|
|
void llama_hparams::set_swa_pattern(uint32_t n_pattern, bool dense_first) {
|
|
if (dense_first) {
|
|
for (uint32_t il = 0; il < n_layer; ++il) {
|
|
swa_layers[il] = n_pattern == 0 || (il % n_pattern != 0);
|
|
}
|
|
} else {
|
|
for (uint32_t il = 0; il < n_layer; ++il) {
|
|
swa_layers[il] = n_pattern == 0 || (il % n_pattern < (n_pattern - 1));
|
|
}
|
|
}
|
|
}
|
|
|
|
bool llama_hparams::is_swa_any() const {
|
|
for (uint32_t il = 0; il < n_layer; ++il) {
|
|
if (swa_layers[il]) {
|
|
return true;
|
|
}
|
|
}
|
|
|
|
return false;
|
|
}
|
|
|
|
uint32_t llama_hparams::n_head(uint32_t il) const {
|
|
if (il < n_layer) {
|
|
return n_head_arr[il];
|
|
}
|
|
|
|
GGML_ABORT("fatal error");
|
|
}
|
|
|
|
uint32_t llama_hparams::n_head_kv(uint32_t il) const {
|
|
if (il < n_layer) {
|
|
return n_head_kv_arr[il];
|
|
}
|
|
|
|
GGML_ABORT("fatal error");
|
|
}
|
|
|
|
uint32_t llama_hparams::n_ff(uint32_t il) const {
|
|
if (il < n_layer) {
|
|
return n_ff_arr[il];
|
|
}
|
|
|
|
GGML_ABORT("fatal error");
|
|
}
|
|
|
|
uint32_t llama_hparams::n_gqa(uint32_t il) const {
|
|
const uint32_t n_head = this->n_head(il);
|
|
const uint32_t n_head_kv = this->n_head_kv(il);
|
|
|
|
if (n_head_kv == 0) {
|
|
return 0;
|
|
}
|
|
|
|
return n_head/n_head_kv;
|
|
}
|
|
|
|
uint32_t llama_hparams::n_embd_k_gqa(uint32_t il) const {
|
|
const uint32_t n_head_kv = this->n_head_kv(il);
|
|
|
|
return n_embd_head_k * n_head_kv;
|
|
}
|
|
|
|
uint32_t llama_hparams::n_embd_v_gqa(uint32_t il) const {
|
|
const uint32_t n_head_kv = this->n_head_kv(il);
|
|
|
|
return n_embd_head_v * n_head_kv;
|
|
}
|
|
|
|
bool llama_hparams::is_n_embd_k_gqa_variable() const {
|
|
const uint32_t val = n_embd_k_gqa();
|
|
for (uint32_t il = 0; il < n_layer; ++il) {
|
|
if (val != n_embd_k_gqa(il)) {
|
|
return true;
|
|
}
|
|
}
|
|
|
|
return false;
|
|
}
|
|
|
|
bool llama_hparams::is_n_embd_v_gqa_variable() const {
|
|
const uint32_t val = n_embd_v_gqa();
|
|
for (uint32_t il = 0; il < n_layer; ++il) {
|
|
if (val != n_embd_v_gqa(il)) {
|
|
return true;
|
|
}
|
|
}
|
|
|
|
return false;
|
|
}
|
|
|
|
uint32_t llama_hparams::n_embd_k_gqa_max() const {
|
|
uint32_t val = n_embd_k_gqa();
|
|
for (uint32_t il = 0; il < n_layer; ++il) {
|
|
val = std::max(val, n_embd_k_gqa(il));
|
|
}
|
|
|
|
return val;
|
|
}
|
|
|
|
uint32_t llama_hparams::n_embd_v_gqa_max() const {
|
|
uint32_t val = n_embd_v_gqa();
|
|
for (uint32_t il = 0; il < n_layer; ++il) {
|
|
val = std::max(val, n_embd_v_gqa(il));
|
|
}
|
|
|
|
return val;
|
|
}
|
|
|
|
uint32_t llama_hparams::n_embd_r() const {
|
|
if (wkv_head_size != 0) {
|
|
// for RWKV models
|
|
return token_shift_count * n_embd;
|
|
}
|
|
|
|
if (n_shortconv_l_cache != 0) {
|
|
// for LFM2 models
|
|
return n_embd * (n_shortconv_l_cache - 1);
|
|
}
|
|
|
|
// TODO: maybe support other convolution strides than 1
|
|
// NOTE: since the first column of the conv_state is shifted out each time, it's not actually needed
|
|
// Corresponds to Mamba's conv_states size
|
|
return (ssm_d_conv > 0 ? ssm_d_conv - 1 : 0) * (ssm_d_inner + 2*ssm_n_group*ssm_d_state);
|
|
}
|
|
|
|
uint32_t llama_hparams::n_embd_s() const {
|
|
if (wkv_head_size != 0) {
|
|
// corresponds to RWKV's wkv_states size
|
|
return n_embd * wkv_head_size;
|
|
}
|
|
|
|
// corresponds to Mamba's ssm_states size
|
|
return ssm_d_state * ssm_d_inner;
|
|
}
|
|
|
|
bool llama_hparams::is_recurrent(uint32_t il) const {
|
|
return recurrent_layer_arr[il];
|
|
}
|
|
|
|
uint32_t llama_hparams::n_pos_per_embd() const {
|
|
return rope_type == LLAMA_ROPE_TYPE_MROPE ? 4 : 1;
|
|
}
|
|
|
|
bool llama_hparams::n_bskcn(uint32_t n, uint32_t il) const {
|
|
if (il < n_layer) {
|
|
return n_bskcn_arr[n][il] > 0;
|
|
}
|
|
|
|
GGML_ABORT("fatal error");
|
|
}
|
|
|
|
bool llama_hparams::is_swa(uint32_t il) const {
|
|
if (il < n_layer) {
|
|
return swa_layers[il];
|
|
}
|
|
|
|
GGML_ABORT("fatal error");
|
|
}
|
|
|
|
bool llama_hparams::has_kv(uint32_t il) const {
|
|
if (n_layer_kv_from_start >= 0) {
|
|
if (il < (uint32_t) n_layer_kv_from_start) {
|
|
return true;
|
|
}
|
|
|
|
return false;
|
|
}
|
|
|
|
// by default, all layers have kv
|
|
return true;
|
|
}
|
|
|
|
uint32_t llama_hparams::n_layer_kv() const {
|
|
uint32_t res = 0;
|
|
|
|
for (uint32_t il = 0; il < n_layer; ++il) {
|
|
if (has_kv(il)) {
|
|
res++;
|
|
}
|
|
}
|
|
|
|
return res;
|
|
}
|
|
|
|
bool llama_hparams::is_masked_swa(uint32_t n_swa, llama_swa_type swa_type, llama_pos p0, llama_pos p1) {
|
|
assert(p0 >= 0 && p1 >= 0);
|
|
|
|
switch (swa_type) {
|
|
case LLAMA_SWA_TYPE_NONE:
|
|
{
|
|
} break;
|
|
case LLAMA_SWA_TYPE_STANDARD:
|
|
{
|
|
if (p1 - p0 >= (int32_t) n_swa) {
|
|
return true;
|
|
}
|
|
} break;
|
|
case LLAMA_SWA_TYPE_CHUNKED:
|
|
{
|
|
const llama_pos pos_chunk_start = (p1 / n_swa) * n_swa;
|
|
|
|
if (p0 < pos_chunk_start) {
|
|
return true;
|
|
}
|
|
} break;
|
|
case LLAMA_SWA_TYPE_SYMMETRIC:
|
|
{
|
|
const int32_t half_n_swa = (int32_t) n_swa / 2;
|
|
const int32_t pos_diff = p1 - p0;
|
|
|
|
// Mask if outside the symmetric window
|
|
if (pos_diff < -half_n_swa || pos_diff > half_n_swa) {
|
|
return true;
|
|
}
|
|
} break;
|
|
}
|
|
|
|
return false;
|
|
}
|