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llama.cpp
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Merge branch 'master' into HEAD

This commit is contained in:
Georgi Gerganov 2025-12-14 16:44:30 +02:00
parent 22c7f85b9c 9e6649ecf2
commit 0086c246ee
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GPG Key ID: 449E073F9DC10735
5 changed files with 21 additions and 14 deletions
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20
ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_iq1_s.comp
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@ -10,44 +10,44 @@ FLOAT_TYPE temp[NUM_COLS][NUM_ROWS];
void calc_superblock(const uint a_offset, const uint b_offset, const uint ib32, const uint i,
const uint num_blocks_per_row, const uint first_row, const uint num_rows) {
const uint y_idx_base = i * QUANT_K + 32 * ib32;
[[unroll]] for (uint j = 0; j < NUM_COLS; ++j) {
[[unroll]] for (uint j = 0; j < NUM_COLS; ++j) {
const uint base_b_idx = (j * p.batch_stride_b + b_offset + y_idx_base) / 4;
[[unroll]] for (uint l = 0; l < 4; ++l) {
[[unroll]] for (uint l = 0; l < 4; ++l) {
const vec4 b_val_0 = vec4(data_b_v4[base_b_idx + 2 * l]);
const vec4 b_val_1 = vec4(data_b_v4[base_b_idx + 2 * l + 1]);
// index for data_a
uint ibi = a_offset / QUANT_K + first_row * num_blocks_per_row + i;
[[unroll]] for (uint n = 0; n < num_rows; ++n) {
[[unroll]] for (uint n = 0; n < num_rows; ++n) {
const float d = float(data_a[ibi].d);
const uint qh = data_a[ibi].qh[ib32];
const float dl = d * float(2 * bitfieldExtract(qh, 12, 3) + 1);
const uint qs = data_a[ibi].qs[4 * ib32 + l];
const uint idxhi = bitfieldExtract(qh, 3 * int(l), 3);
const uint idxhi = bitfieldExtract(qh, 3 * int(l), 3);
const uint16_t grid = uint16_t(iq1s_grid[qs | (idxhi << 8)]);
const float delta_val = ((qh & 0x8000) != 0) ? -IQ1S_DELTA : IQ1S_DELTA;
const vec4 delta_v = vec4(delta_val);
const vec4 delta_v = vec4(delta_val);
const vec4 fbits0 = vec4(
float(bitfieldExtract(grid, 0, 2)),
float(bitfieldExtract(grid, 2, 2)),
float(bitfieldExtract(grid, 4, 2)),
float(bitfieldExtract(grid, 6, 2))
);
);
const vec4 fbits1 = vec4(
float(bitfieldExtract(grid, 8, 2)),
float(bitfieldExtract(grid, 10, 2)),
float(bitfieldExtract(grid, 12, 2)),
float(bitfieldExtract(grid, 14, 2))
);
vec4 sum_v = fma(b_val_0, fbits0 + delta_v, vec4(0.0));
sum_v = fma(b_val_1, fbits1 + delta_v, sum_v);
FLOAT_TYPE sum = dot(sum_v, vec4(1.0));
temp[j][n] = fma(dl, sum, temp[j][n]);
FLOAT_TYPE sum = dot(sum_v, vec4(1.0));
temp[j][n] = fma(dl, sum, temp[j][n]);
ibi += num_blocks_per_row;
}
}

4
src/llama-graph.cpp
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@ -79,7 +79,7 @@ void llm_graph_input_attn_temp::set_input(const llama_ubatch * ubatch) {
for (int i = 0; i < n_tokens; ++i) {
const float pos = ubatch->pos[i];
attn_scale_data[i] = std::log(
std::floor((pos + 1.0f) / n_attn_temp_floor_scale) + 1.0
std::floor((pos + f_attn_temp_offset) / n_attn_temp_floor_scale) + 1.0
) * f_attn_temp_scale + 1.0;
}
@ -1278,7 +1278,7 @@ ggml_tensor * llm_graph_context::build_inp_pos() const {
}
ggml_tensor * llm_graph_context::build_inp_attn_scale() const {
auto inp = std::make_unique<llm_graph_input_attn_temp>(hparams.n_attn_temp_floor_scale, hparams.f_attn_temp_scale);
auto inp = std::make_unique<llm_graph_input_attn_temp>(hparams.n_attn_temp_floor_scale, hparams.f_attn_temp_scale, hparams.f_attn_temp_offset);
auto & cur = inp->attn_scale;

5
src/llama-graph.h
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@ -133,8 +133,8 @@ public:
// temperature tuning, used by llama4
class llm_graph_input_attn_temp : public llm_graph_input_i {
public:
llm_graph_input_attn_temp(uint32_t n_attn_temp_floor_scale, float f_attn_temp_scale)
: n_attn_temp_floor_scale(n_attn_temp_floor_scale), f_attn_temp_scale(f_attn_temp_scale) {}
llm_graph_input_attn_temp(uint32_t n_attn_temp_floor_scale, float f_attn_temp_scale, float f_attn_temp_offset)
: n_attn_temp_floor_scale(n_attn_temp_floor_scale), f_attn_temp_scale(f_attn_temp_scale), f_attn_temp_offset(f_attn_temp_offset) {}
virtual ~llm_graph_input_attn_temp() = default;
void set_input(const llama_ubatch * ubatch) override;
@ -143,6 +143,7 @@ public:
const uint32_t n_attn_temp_floor_scale;
const float f_attn_temp_scale;
const float f_attn_temp_offset;
};
class llm_graph_input_pos_bucket : public llm_graph_input_i {

1
src/llama-hparams.h
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@ -165,6 +165,7 @@ struct llama_hparams {
uint32_t n_no_rope_layer_step = 4;
uint32_t n_attn_temp_floor_scale = 0;
float f_attn_temp_scale = 0.0f;
float f_attn_temp_offset = 0.0f; // offset position index
// gemma3n altup
uint32_t n_altup = 4; // altup_num_inputs

5
src/llama-model.cpp
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@ -668,6 +668,7 @@ void llama_model::load_hparams(llama_model_loader & ml) {
hparams.n_swa = 8192;
hparams.n_attn_temp_floor_scale = 8192;
hparams.f_attn_temp_scale = 0.1f;
hparams.f_attn_temp_offset = 1.0f;
hparams.set_swa_pattern(4); // pattern: 3 chunked - 1 full
}
@ -1646,6 +1647,8 @@ void llama_model::load_hparams(llama_model_loader & ml) {
ml.get_key(LLM_KV_ATTENTION_TEMPERATURE_SCALE, hparams.f_attn_temp_scale, false);
ml.get_key(LLM_KV_ATTENTION_TEMPERATURE_LENGTH, hparams.n_attn_temp_floor_scale, false);
hparams.f_attn_temp_offset = 0.0f;
switch (hparams.n_layer) {
case 27: type = LLM_TYPE_16B; break;
case 60: type = LLM_TYPE_236B; break;
@ -2276,6 +2279,8 @@ void llama_model::load_hparams(llama_model_loader & ml) {
ml.get_key(LLM_KV_ROPE_SCALING_YARN_BETA_SLOW, hparams.yarn_beta_slow, false);
ml.get_key(LLM_KV_ROPE_SCALING_YARN_LOG_MUL, hparams.rope_yarn_log_mul, 0.0f);
hparams.f_attn_temp_offset = 0.0f;
// TODO: maybe add n_attn_temp_floor_scale as a separate KV?
if (hparams.f_attn_temp_scale != 0.0f) {
hparams.n_attn_temp_floor_scale = hparams.n_ctx_orig_yarn;