talk-llama : sync llama.cpp

This commit is contained in:
Georgi Gerganov
2026-01-30 15:56:40 +02:00
parent b529c0610f
commit 953e503fd9
38 changed files with 2299 additions and 730 deletions
+14 -14
View File
@@ -2,14 +2,11 @@
llm_build_deepseek2::llm_build_deepseek2(const llama_model & model, const llm_graph_params & params) :
llm_graph_context(params) {
// lite variants include DeepSeek-V2-Lite, GigaChat3-10B-A1.8B
bool is_lite = (hparams.n_layer == 27 || hparams.n_layer == 26);
const bool is_mla = (hparams.n_embd_head_k_mla != 0 && hparams.n_embd_head_v_mla != 0);
const bool is_mla = hparams.is_mla();
// note: these are the actual head sizes you get when treating as MHA or after "decompression" using wv_b for MLA
const int64_t n_embd_head_k = is_mla ? hparams.n_embd_head_k_mla : hparams.n_embd_head_k;
const int64_t n_embd_head_v = is_mla ? hparams.n_embd_head_v_mla : hparams.n_embd_head_v;
const int64_t n_embd_head_k = hparams.n_embd_head_k_mla();
const int64_t n_embd_head_v = hparams.n_embd_head_v_mla();
const int64_t n_embd_head_qk_rope = hparams.n_rot;
const int64_t n_embd_head_qk_nope = n_embd_head_k - n_embd_head_qk_rope;
@@ -43,7 +40,8 @@ llm_build_deepseek2::llm_build_deepseek2(const llama_model & model, const llm_gr
// inp_pos - contains the positions
ggml_tensor * inp_pos = build_inp_pos();
auto * inp_attn = build_attn_inp_kv();
auto * inp_attn_kv = !is_mla ? build_attn_inp_kv() : nullptr;
auto * inp_attn_k = is_mla ? build_attn_inp_k() : nullptr;
ggml_tensor * inp_out_ids = build_inp_out_ids();
@@ -57,6 +55,9 @@ llm_build_deepseek2::llm_build_deepseek2(const llama_model & model, const llm_gr
// self_attention
{
ggml_tensor * q = NULL;
const bool is_lite = model.layers[il].wq;
if (!is_lite) {
q = ggml_mul_mat(ctx0, model.layers[il].wq_a, cur);
cb(q, "q", il);
@@ -124,14 +125,14 @@ llm_build_deepseek2::llm_build_deepseek2(const llama_model & model, const llm_gr
// {n_embd_head_qk_rope + kv_lora_rank, n_head, n_tokens}
// note: rope must go first for in-place context shifting in build_rope_shift()
ggml_tensor * Qcur = ggml_concat(ctx0, q_pe, q_nope_absorbed, 0);
ggml_tensor * Qcur = ggml_concat(ctx0, q_nope_absorbed, q_pe, 0);
cb(Qcur, "Qcur", il);
kv_cmpr = ggml_reshape_3d(ctx0, kv_cmpr, kv_lora_rank, 1, n_tokens);
cb(kv_cmpr, "kv_cmpr_reshape", il);
// {n_embd_head_qk_rope + kv_lora_rank, 1, n_tokens}
ggml_tensor * Kcur = ggml_concat(ctx0, k_pe, kv_cmpr, 0);
ggml_tensor * Kcur = ggml_concat(ctx0, kv_cmpr, k_pe, 0);
cb(Kcur, "Kcur", il);
// {kv_lora_rank, 1, n_tokens}
@@ -145,7 +146,7 @@ llm_build_deepseek2::llm_build_deepseek2(const llama_model & model, const llm_gr
}
// note: MLA with the absorption optimzation converts into MQA (ie: GQA with 1 group)
cur = build_attn(inp_attn,
cur = build_attn(inp_attn_k,
model.layers[il].wo, NULL,
Qcur, Kcur, Vcur, nullptr, nullptr, model.layers[il].wv_b, kq_scale, il);
} else {
@@ -169,11 +170,10 @@ llm_build_deepseek2::llm_build_deepseek2(const llama_model & model, const llm_gr
Vcur = ggml_cont(ctx0, Vcur);
cb(Vcur, "Vcur_cont", il);
// note: rope must go first for in-place context shifting in build_rope_shift()
ggml_tensor * Qcur = ggml_concat(ctx0, q_pe, q_nope, 0);
ggml_tensor * Qcur = ggml_concat(ctx0, q_nope, q_pe, 0);
cb(Qcur, "Qcur", il);
ggml_tensor * Kcur = ggml_concat(ctx0, ggml_repeat(ctx0, k_pe, q_pe), k_nope, 0);
ggml_tensor * Kcur = ggml_concat(ctx0, k_nope, ggml_repeat(ctx0, k_pe, q_pe), 0);
cb(Kcur, "Kcur", il);
if (inp_attn_scale) {
@@ -183,7 +183,7 @@ llm_build_deepseek2::llm_build_deepseek2(const llama_model & model, const llm_gr
}
// note: MLA without the absorption optimization converts into MHA (ie: GQA with full n_head groups)
cur = build_attn(inp_attn,
cur = build_attn(inp_attn_kv,
model.layers[il].wo, NULL,
Qcur, Kcur, Vcur, nullptr, nullptr, nullptr, kq_scale, il);
}