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Revert "Update vendored llama.cpp to b7847" (#14061)

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This commit is contained in:
Jeffrey Morgan
2026-02-03 18:39:36 -08:00
committed by GitHub
parent a6355329bf
commit b1fccabb34
240 changed files with 5050 additions and 21247 deletions
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66
llama/llama.cpp/src/llama-hparams.h vendored
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@@ -3,7 +3,6 @@
#include "llama.h"
#include <array>
#include <cassert>
// bump if necessary
#define LLAMA_MAX_LAYERS 512
@@ -53,8 +52,8 @@ struct llama_hparams {
uint32_t n_rel_attn_bkts = 0;
// note: deepseek2 using MLA converts into MQA with larger heads, then decompresses to MHA
uint32_t n_embd_head_k_mla_impl = 0;
uint32_t n_embd_head_v_mla_impl = 0;
uint32_t n_embd_head_k_mla = 0;
uint32_t n_embd_head_v_mla = 0;
// for WavTokenizer
struct llama_hparams_posnet posnet;
@@ -108,9 +107,9 @@ struct llama_hparams {
float rope_attn_factor = 1.0f;
float rope_freq_base_train;
float rope_freq_base_train_swa = 10000.0f;
float rope_freq_base_train_swa;
float rope_freq_scale_train;
float rope_freq_scale_train_swa = 1.0f;
float rope_freq_scale_train_swa;
uint32_t n_ctx_orig_yarn;
float rope_yarn_log_mul = 0.0f;
@@ -126,11 +125,10 @@ struct llama_hparams {
llama_swa_type swa_type = LLAMA_SWA_TYPE_NONE;
// the size of the sliding window (0 - no SWA)
uint32_t n_swa = 0;
// if swa_layers[il] == 1, then layer il is SWA
// if swa_layers[il] == 0, then layer il is dense (i.e. non-SWA)
// if swa_layers[il] == true, then layer il is SWA
// if swa_layers[il] == false, then layer il is dense (i.e. non-SWA)
// by default, all layers are dense
// note: using uint32_t type for compatibility reason
std::array<uint32_t, LLAMA_MAX_LAYERS> swa_layers;
std::array<bool, LLAMA_MAX_LAYERS> swa_layers;
// for State Space Models
uint32_t ssm_d_conv = 0;
@@ -165,9 +163,6 @@ struct llama_hparams {
// for Classifiers
uint32_t n_cls_out = 1;
// output embedding dimension (0 = use n_embd)
uint32_t n_embd_out_impl = 0;
// llama4 smallthinker
uint32_t n_moe_layer_step = 0;
uint32_t n_no_rope_layer_step = 4;
@@ -240,9 +235,6 @@ struct llama_hparams {
// dimension of main + auxiliary input embeddings
uint32_t n_embd_inp() const;
// dimension of output embeddings
uint32_t n_embd_out() const;
// dimension of key embeddings across all k-v heads
uint32_t n_embd_k_gqa(uint32_t il = 0) const;
@@ -274,57 +266,15 @@ struct llama_hparams {
bool is_swa(uint32_t il) const;
// note: currently only support if either all or none of the layers are MLA
bool is_mla() const;
uint32_t n_embd_head_k_mla() const;
uint32_t n_embd_head_v_mla() const;
bool has_kv(uint32_t il) const;
// number of layers for which has_kv() returns true
uint32_t n_layer_kv() const;
// note that this function uses different SWA parameters from those in the hparams
// note: inlined on purpose for performance reasons
// TODO: think of a better place for this function
// TODO: pack the SWA params in a struct?
static bool 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;
}
static bool is_masked_swa(uint32_t n_swa, llama_swa_type swa_type, llama_pos p0, llama_pos p1);
bool use_mrope() const;
};