ver4a/llama.cpp
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kv-cache : add SWA support (#13194)

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* kv-cache : prepare for SWA

ggml-ci

* kv-cache : initial iSWA implementation

ggml-ci

* kv-cache : rework error recovery logic

ggml-ci

* models : fix Phi-3 SWA parameters

ggml-ci

* model : adjust Granite to rope factor changes

ggml-ci

* server : check if context can do shifts

ggml-ci

* iswa : for now, always enable shifts (experiment)

ggml-ci

* kv-cache : simplify SWA logic

ggml-ci

* kv-cache : apply defrag when we fail to find slots for the batch

ggml-ci

* llama : update docs about llama_decode

ggml-ci

* kv-cache : update warning logs when no space for the batch is available

ggml-ci

* llama : add llama_kv_self_seq_pos_min()

* kv-cache : keep track of partial SWA computes and print warnings

* server : disallow use cases involving partial SWA context

ggml-ci

* llama : add param to control SWA cache size

ggml-ci

* minor : clean-up

ggml-ci
This commit is contained in:
Georgi Gerganov 2025-05-20 08:05:46 +03:00 • committed by GitHub
parent f0adb80bf7
commit e298d2fbd0
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15 changed files with 1426 additions and 650 deletions
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19
src/llama-hparams.h
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@ -14,6 +14,12 @@ enum llama_expert_gating_func_type {
LLAMA_EXPERT_GATING_FUNC_TYPE_SIGMOID = 2,
};
enum llama_swa_type {
LLAMA_SWA_TYPE_NONE = 0,
LLAMA_SWA_TYPE_STANDARD = 1,
LLAMA_SWA_TYPE_CHUNKED = 2,
};
struct llama_hparams_posnet {
uint32_t n_embd;
uint32_t n_layer;
@ -35,8 +41,6 @@ struct llama_hparams {
uint32_t n_embd_features = 0;
uint32_t n_layer;
uint32_t n_rot;
uint32_t n_swa = 0; // sliding window attention (SWA)
uint32_t n_swa_pattern = 1; // by default, all layers use non-sliding-window attention
uint32_t n_embd_head_k; // dimension of keys (d_k). d_q is assumed to be the same, but there are n_head q heads, and only n_head_kv k-v heads
uint32_t n_embd_head_v; // dimension of values (d_v) aka n_embd_head
uint32_t n_expert = 0;
@ -96,6 +100,12 @@ struct llama_hparams {
std::array<int, 4> rope_sections;
// Sliding Window Attention (SWA)
llama_swa_type swa_type = LLAMA_SWA_TYPE_NONE;
uint32_t n_swa = 0; // the size of the sliding window (0 - no SWA)
uint32_t n_swa_pattern = 1; // by default, all layers use non-sliding-window attention
// for State Space Models
uint32_t ssm_d_conv = 0;
uint32_t ssm_d_inner = 0;
@ -116,11 +126,10 @@ struct llama_hparams {
bool causal_attn = true;
bool use_alibi = false;
bool attn_soft_cap = false;
bool use_kq_norm = true;
// llama4
uint32_t n_moe_layer_step = 0;
bool use_kq_norm = true;
uint32_t n_attn_chunk = 0;
// values below seems to be fixed on llama4
uint32_t n_no_rope_layer_step = 4;
uint32_t n_attn_temp_floor_scale = 8192;
float f_attn_temp_scale = 0.1;