Lumpiasty/llama.cpp
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

hparams : refactor hparams.n_layer (#24060)

Browse Source 
* hparams : refactor hparams.n_layer

* cont : remove `n_layer_kv()`, use n_layer_all instead

* cont : type consistency

* pi : update SYSTEM.md

* models : fix Step3.5 MTP

* cont : remove duplicate switch cases

* cont : explicitly set `false` to extra layers for `is_swa` and `is_recr`

* cont : fix nextn layer count handling

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

---------

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
This commit is contained in:
Georgi Gerganov
2026-06-05 11:09:36 +03:00
committed by GitHub
co-authored by Sigbjørn Skjæret
parent 3ecfb150a4
commit 7acb4e8cd2
129 changed files with 412 additions and 431 deletions
Download Patch File Download Diff File Expand all files Collapse all files
src/llama-kv-cache.cpp
+4 -4
View File
@@ -97,7 +97,7 @@ llama_kv_cache::llama_kv_cache(
GGML_ASSERT(kv_size % n_pad == 0);
const uint32_t n_layer_kv = hparams.n_layer_kv();
const uint32_t n_layer = hparams.n_layer_all;
// define a comparator for the buft -> ctx map to ensure that the order is well-defined:
struct ggml_backend_buft_comparator {
@@ -112,7 +112,7 @@ llama_kv_cache::llama_kv_cache(
auto it = ctx_map.find(buft);
if (it == ctx_map.end()) {
ggml_init_params params = {
/*.mem_size =*/ size_t(2u*(1 + n_stream)*n_layer_kv*ggml_tensor_overhead()),
/*.mem_size =*/ size_t(2u*(1 + n_stream)*n_layer*ggml_tensor_overhead()),
/*.mem_buffer =*/ NULL,
/*.no_alloc =*/ true,
};
@@ -160,7 +160,7 @@ llama_kv_cache::llama_kv_cache(
const bool is_mla = hparams.is_mla();
for (uint32_t il = 0; il < hparams.n_layer; il++) {
for (uint32_t il = 0; il < n_layer; il++) {
if (!hparams.has_kv(il)) {
LLAMA_LOG_DEBUG("%s: layer %3d: does not have KV cache\n", __func__, il);
continue;
@@ -230,7 +230,7 @@ llama_kv_cache::llama_kv_cache(
if (reuse) {
LLAMA_LOG_DEBUG("%s: reusing layers:\n", __func__);
for (uint32_t il = 0; il < hparams.n_layer; il++) {
for (uint32_t il = 0; il < n_layer; il++) {
const int32_t il_reuse = reuse(il);
if (il_reuse < 0) {