ggml : add GGML_OP_LIGHTNING_INDEXER that implements DeepSeek V3.2/V4 lightning indexer (#24231)

* ggml : add GGML_OP_LIGHTNING_INDEXER that implements DeepSeek V3.2/V4 lightning indexer

* ggml : remove scale parameters from lightning indexer OP, add f16 mask parameter

* tests : add GGML_OP_LIGHTNING_INDEXER tests

* ggml : bump RPC version

* chore : check if lightning indexer input tensors are not transposed

* tests : count flops instead of bandwidth in lightning indexer test

* chore : add missing const

* chore : whitespace

* ggml : renamed variables in CPU lightning indexer implementation

* ggml : fix lightning indexer mask broadcasting

* tests : tests for lightning indexer mask broadcasting

* chore : whitespace

* llama : use GGML_OP_LIGHTNING_INDEXER in DeepSeek V3.2 and DeepSeek V4 models

---------

Co-authored-by: Stanisław Szymczyk <sszymczy@gmail.com>
This commit is contained in:
fairydreaming
2026-07-11 11:39:07 +02:00
committed by GitHub
parent 76f2798059
commit 00f5442cc4
13 changed files with 324 additions and 52 deletions

View File

@@ -7097,6 +7097,67 @@ struct test_diag : public test_case {
}
};
// GGML_OP_LIGHTNING_INDEXER
struct test_lightning_indexer : public test_case {
const int64_t hsk; // indexer K head size
const int64_t nh; // num indexer heads
const int64_t kv; // kv size
const int64_t nb; // batch size
const int64_t ns; // num streams
const int64_t nm; // ne[3] of mask
const ggml_type type_K;
std::string vars() override {
return VARS_TO_STR7(hsk, nh, kv, nb, ns, nm, type_K);
}
double max_nmse_err() override {
return 1e-6;
}
uint64_t op_flops(ggml_tensor * t) override {
GGML_UNUSED(t);
return ((2 * hsk + 2) * nh + 1) * kv * nb * ns;
}
test_lightning_indexer(int64_t hsk = 128, int64_t nh = 64, int64_t kv = 256, int64_t nb = 128, int64_t ns = 1, int64_t nm = 1, ggml_type type_K = GGML_TYPE_F16)
: hsk(hsk), nh(nh), kv(kv), nb(nb), ns(ns), nm(nm), type_K(type_K) {}
ggml_tensor * build_graph(ggml_context * ctx) override {
ggml_tensor * q = ggml_new_tensor_4d(ctx, GGML_TYPE_F32, hsk, nh, nb, ns);
ggml_set_param(q);
ggml_set_name(q, "q");
ggml_tensor * k = ggml_new_tensor_4d(ctx, type_K, hsk, 1, kv, ns);
ggml_set_param(k);
ggml_set_name(k, "k");
ggml_tensor * w = ggml_new_tensor_4d(ctx, GGML_TYPE_F32, nh, nb, 1, ns);
ggml_set_param(w);
ggml_set_name(w, "w");
ggml_tensor * m = ggml_new_tensor_4d(ctx, GGML_TYPE_F16, kv, nb, 1, nm);
ggml_set_param(m);
ggml_set_name(m, "m");
ggml_tensor * out = ggml_lightning_indexer(ctx, q, k, w, m);
ggml_set_name(out, "out");
return out;
}
void initialize_tensors(ggml_context * ctx) override {
for (ggml_tensor * t = ggml_get_first_tensor(ctx); t != NULL; t = ggml_get_next_tensor(ctx, t)) {
if (strcmp(t->name, "m") == 0) {
init_tensor_kq_mask(t);
} else {
init_tensor_uniform(t);
}
}
}
};
// Deserializable generic test case
struct input_tensor {
ggml_type type;
@@ -9393,6 +9454,19 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
test_cases.emplace_back(new test_falcon(2));
#endif
// lightning_indexer
for (int kv : { 256 }) {
for (int bs : { 1, 512 }) {
for (int nh : { 32, 64 }) {
for (auto [ns, nm] : { std::pair{1, 1}, std::pair{4, 4}, std::pair{4, 1} }) {
for (ggml_type type_K : {GGML_TYPE_F32, GGML_TYPE_F16, GGML_TYPE_BF16, GGML_TYPE_Q8_0, GGML_TYPE_Q5_1, GGML_TYPE_Q5_0, GGML_TYPE_Q4_1, GGML_TYPE_Q4_0, GGML_TYPE_IQ4_NL}) {
test_cases.emplace_back(new test_lightning_indexer(128, nh, kv, bs, ns, nm, type_K));
}
}
}
}
}
return test_cases;
}
#ifdef _MSC_VER
@@ -9722,6 +9796,19 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_perf() {
test_cases.emplace_back(new test_gated_delta_net(GGML_TYPE_F32, 4, 128, 1024, 1)); // 4h PP-1024
test_cases.emplace_back(new test_gated_delta_net(GGML_TYPE_F32, 32, 128, 64, 1, 1, false, true)); // KDA PP-64
// lightning_indexer
for (int kv : { 256, 4096, 65536 }) {
for (int bs : { 1, 512, 2048 }) {
for (int nh : { 32, 64 }) {
for (int ns : { 1, 4 }) {
for (ggml_type type_K : {GGML_TYPE_F32, GGML_TYPE_F16, GGML_TYPE_BF16, GGML_TYPE_Q8_0, GGML_TYPE_Q5_1, GGML_TYPE_Q5_0, GGML_TYPE_Q4_1, GGML_TYPE_Q4_0, GGML_TYPE_IQ4_NL}) {
test_cases.emplace_back(new test_lightning_indexer(128, nh, kv, bs, ns, ns, type_K));
}
}
}
}
}
return test_cases;
}