Add mqkv and rcache for Gemma3 (#972)

Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
This commit is contained in:
Kawrakow
2025-11-16 19:10:41 +02:00
committed by GitHub
parent a8b3c8ae73
commit 294aec2bc2
2 changed files with 31 additions and 25 deletions

View File

@@ -4952,8 +4952,6 @@ ggml_cgraph * llm_build_context::build_gemma2() {
ggml_cgraph * llm_build_context::build_gemma3() {
struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, llama_model_max_nodes(model), false);
const int64_t n_embd_head_k = hparams.n_embd_head_k;
struct ggml_tensor * cur;
struct ggml_tensor * inpL;
@@ -4977,6 +4975,15 @@ ggml_cgraph * llm_build_context::build_gemma3() {
// 5 layers of local attention followed by 1 layer of global attention
static const int sliding_window_pattern = 6;
ggml_tensor * rope_cache = nullptr;
ggml_tensor * rope_cache_l = nullptr;
if (cparams.rope_cache && (rope_type == LLAMA_ROPE_TYPE_NEOX || rope_type == LLAMA_ROPE_TYPE_NORM)) {
rope_cache = ggml_rope_cache(ctx0, inp_pos, nullptr, n_rot, n_rot, rope_type, n_ctx_orig, freq_base, freq_scale,
ext_factor, attn_factor, beta_fast, beta_slow);
rope_cache_l = ggml_rope_cache(ctx0, inp_pos, nullptr, n_rot, n_rot, rope_type, n_ctx_orig, 10000.0f, 1.0f,
ext_factor, attn_factor, beta_fast, beta_slow);
}
for (int il = 0; il < n_layer; ++il) {
const bool is_sliding = (il + 1) % sliding_window_pattern;
const float freq_base_l = is_sliding ? 10000.0f : freq_base;
@@ -4989,24 +4996,24 @@ ggml_cgraph * llm_build_context::build_gemma3() {
// self-attention
{
auto [Qcur, Kcur, Vcur] = llm_build_mul_mat_qkv(gf, cur, model.layers[il].wq, nullptr,
model.layers[il].wk, nullptr,
model.layers[il].wv, nullptr, 0, il);
auto [Qcur, Kcur, Vcur] = llm_build_mul_mat_qkv(gf, cur,
model.layers[il].wqkv, nullptr,
model.layers[il].wqk, nullptr,
model.layers[il].wq, nullptr, model.layers[il].wk, nullptr, model.layers[il].wv, nullptr,
model.layers[il].attn_q_norm, model.layers[il].attn_k_norm, 0, il);
Qcur = ggml_reshape_3d(ctx0, Qcur, n_embd_head_k, n_head, n_tokens);
Qcur = llm_build_norm(ctx0, Qcur, hparams, model.layers[il].attn_q_norm, NULL, LLM_NORM_RMS, cb, il);
cb(Qcur, "Qcur_normed", il);
if (rope_cache) {
auto rcache = is_sliding ? rope_cache_l : rope_cache;
Qcur = ggml_rope_fast(ctx0, Qcur, rcache);
Kcur = ggml_rope_fast(ctx0, Kcur, rcache);
} else {
Qcur = ggml_rope_ext(ctx0, Qcur, inp_pos, nullptr, n_rot, rope_type, n_ctx_orig, freq_base_l, freq_scale_l,
ext_factor, attn_factor, beta_fast, beta_slow);
Qcur = ggml_rope_ext(ctx0, Qcur, inp_pos, nullptr, n_rot, rope_type, n_ctx_orig, freq_base_l, freq_scale_l,
ext_factor, attn_factor, beta_fast, beta_slow);
Kcur = ggml_rope_ext(ctx0, Kcur, inp_pos, nullptr, n_rot, rope_type, n_ctx_orig, freq_base_l, freq_scale_l,
ext_factor, attn_factor, beta_fast, beta_slow);
}
cb(Qcur, "Qcur", il);
Kcur = ggml_reshape_3d(ctx0, Kcur, n_embd_head_k, n_head_kv, n_tokens);
Kcur = llm_build_norm(ctx0, Kcur, hparams, model.layers[il].attn_k_norm, NULL, LLM_NORM_RMS, cb, il);
cb(Kcur, "Kcur_normed", il);
Kcur = ggml_rope_ext(ctx0, Kcur, inp_pos, nullptr, n_rot, rope_type, n_ctx_orig, freq_base_l, freq_scale_l,
ext_factor, attn_factor, beta_fast, beta_slow);
cb(Kcur, "Kcur", il);
cur = llm_build_kv(ctx0, lctx, kv_self, gf, model.layers[il].wo, NULL,