ikawrakow/ik_llama.cpp
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Add ser option to llama-bench

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This commit is contained in:
Iwan Kawrakow
2025-03-01 13:25:04 +02:00
parent f5ddc6faa8
commit 8e612d50c1
1 changed files with 63 additions and 2 deletions
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65
examples/llama-bench/llama-bench.cpp
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@@ -215,6 +215,9 @@ static std::string pair_str(const std::pair<int, int> & p) {
return buf;
}
// Ser = Smart Expert Reduction
using Ser = std::pair<int,float>;
struct cmd_params {
std::vector<std::string> model;
std::vector<int> n_prompt;
@@ -234,6 +237,7 @@ struct cmd_params {
std::vector<bool> flash_attn;
std::vector<int> mla_attn;
std::vector<int> attn_max_batch;
std::vector<Ser> ser;
std::vector<std::vector<float>> tensor_split;
std::vector<bool> use_mmap;
std::vector<bool> embeddings;
@@ -267,6 +271,7 @@ static const cmd_params cmd_params_defaults = {
/* flash_attn */ {false},
/* mla_attn */ {0},
/* attn_max_batch */ {0},
/* ser */ {{-1,0.0f}},
/* tensor_split */ {std::vector<float>(llama_max_devices(), 0.0f)},
/* use_mmap */ {true},
/* embeddings */ {false},
@@ -304,6 +309,7 @@ static void print_usage(int /* argc */, char ** argv) {
printf(" -fa, --flash-attn <0|1> (default: %s)\n", join(cmd_params_defaults.flash_attn, ",").c_str());
printf(" -mla, --mla-attn <0|1|2> (default: %s)\n", join(cmd_params_defaults.mla_attn, ",").c_str());
printf(" -amb, --attn-max-batch <i> (default: %s)\n", join(cmd_params_defaults.attn_max_batch, ",").c_str());
printf(" -ser, --smart-expert-reduction <i,f>(default: %s)\n", join(cmd_params_defaults.attn_max_batch, ",").c_str());
printf(" -mmp, --mmap <0|1> (default: %s)\n", join(cmd_params_defaults.use_mmap, ",").c_str());
printf(" --numa <distribute|isolate|numactl> (default: disabled)\n");
printf(" -embd, --embeddings <0|1> (default: %s)\n", join(cmd_params_defaults.embeddings, ",").c_str());
@@ -387,6 +393,28 @@ bool parse_buft_overrides(const std::string& value, std::vector<llama_model_tens
}
return true;
}
template<class T1, class T2>
std::vector<std::pair<T1,T2>> string_split_pairs(const std::string & str, char delim) {
std::vector<std::pair<T1,T2>> values;
std::istringstream str_stream(str);
std::string token;
T1 first_value;
int i = 0;
while (std::getline(str_stream, token, delim)) {
std::istringstream token_stream(token);
if (i%2 == 0) {
token_stream >> first_value;
if (token_stream.fail()) return {};
} else {
T2 value;
token_stream >> value;
if (token_stream.fail()) return {};
values.emplace_back(first_value, value);
}
i++;
}
return values;
}
}
static cmd_params parse_cmd_params(int argc, char ** argv) {
@@ -588,6 +616,13 @@ static cmd_params parse_cmd_params(int argc, char ** argv) {
}
auto p = string_split<int>(argv[i], split_delim);
params.attn_max_batch.insert(params.attn_max_batch.end(), p.begin(), p.end());
} else if (arg == "-ser" || arg == "--smart-expert-reduction") {
if (++i >= argc) {
invalid_param = true;
break;
}
auto p = string_split_pairs<int,float>(argv[i], split_delim);
params.ser.insert(params.ser.end(), p.begin(), p.end());
} else if (arg == "-mmp" || arg == "--mmap") {
if (++i >= argc) {
invalid_param = true;
@@ -701,6 +736,7 @@ static cmd_params parse_cmd_params(int argc, char ** argv) {
if (params.flash_attn.empty()) { params.flash_attn = cmd_params_defaults.flash_attn; }
if (params.mla_attn.empty()) { params.mla_attn = cmd_params_defaults.mla_attn; }
if (params.attn_max_batch.empty()){ params.attn_max_batch = cmd_params_defaults.attn_max_batch; }
if (params.ser.empty()) { params.ser = cmd_params_defaults.ser; }
if (params.tensor_split.empty()) { params.tensor_split = cmd_params_defaults.tensor_split; }
if (params.use_mmap.empty()) { params.use_mmap = cmd_params_defaults.use_mmap; }
if (params.embeddings.empty()) { params.embeddings = cmd_params_defaults.embeddings; }
@@ -739,6 +775,7 @@ struct cmd_params_instance {
bool flash_attn;
int mla_attn;
int attn_max_batch;
Ser ser;
std::vector<float> tensor_split;
bool use_mmap;
bool embeddings;
@@ -787,6 +824,8 @@ struct cmd_params_instance {
cparams.mla_attn = mla_attn;
cparams.attn_max_batch = attn_max_batch;
cparams.fused_moe_up_gate = fmoe;
cparams.min_experts = ser.first;
cparams.thresh_experts = ser.second;
cparams.embeddings = embeddings;
return cparams;
@@ -813,6 +852,7 @@ static std::vector<cmd_params_instance> get_cmd_params_instances(const cmd_param
for (const auto & fa : params.flash_attn)
for (const auto & mla : params.mla_attn)
for (const auto & amb : params.attn_max_batch)
for (const auto & ser : params.ser)
for (const auto & nt : params.n_threads) {
for (const auto & n_prompt : params.n_prompt) {
if (n_prompt == 0) {
@@ -836,6 +876,7 @@ static std::vector<cmd_params_instance> get_cmd_params_instances(const cmd_param
/* .flash_attn = */ fa,
/* .mla_attn = */ mla,
/* .attn_max_b = */ amb,
/* .ser = */ ser,
/* .tensor_split = */ ts,
/* .use_mmap = */ mmp,
/* .embeddings = */ embd,
@@ -868,6 +909,7 @@ static std::vector<cmd_params_instance> get_cmd_params_instances(const cmd_param
/* .flash_attn = */ fa,
/* .mla_attn = */ mla,
/* .attn_max_b = */ amb,
/* .ser = */ ser,
/* .tensor_split = */ ts,
/* .use_mmap = */ mmp,
/* .embeddings = */ embd,
@@ -900,6 +942,7 @@ static std::vector<cmd_params_instance> get_cmd_params_instances(const cmd_param
/* .flash_attn = */ fa,
/* .mla_attn = */ mla,
/* .attn_max_b = */ amb,
/* .ser = */ ser,
/* .tensor_split = */ ts,
/* .use_mmap = */ mmp,
/* .embeddings = */ embd,
@@ -932,6 +975,7 @@ static std::vector<cmd_params_instance> get_cmd_params_instances(const cmd_param
/* .flash_attn = */ fa,
/* .mla_attn = */ mla,
/* .attn_max_b = */ amb,
/* .ser = */ ser,
/* .tensor_split = */ ts,
/* .use_mmap = */ mmp,
/* .embeddings = */ embd,
@@ -975,6 +1019,7 @@ struct test {
bool flash_attn;
int mla_attn;
int attn_max_batch;
Ser ser;
std::vector<float> tensor_split;
bool use_mmap;
bool embeddings;
@@ -1007,6 +1052,7 @@ struct test {
flash_attn = inst.flash_attn;
mla_attn = inst.mla_attn;
attn_max_batch = inst.attn_max_batch;
ser = inst.ser;
tensor_split = inst.tensor_split;
use_mmap = inst.use_mmap;
embeddings = inst.embeddings;
@@ -1101,7 +1147,7 @@ struct test {
"n_batch", "n_ubatch",
"n_threads", "type_k", "type_v",
"n_gpu_layers", "split_mode",
"main_gpu", "no_kv_offload", "flash_attn", "mla_attn", "attn_max_batch",
"main_gpu", "no_kv_offload", "flash_attn", "mla_attn", "attn_max_batch", "ser",
"tensor_split", "use_mmap", "embeddings", "repack", "fused_moe",
"n_prompt", "n_gen", "test_time",
"avg_ns", "stddev_ns",
@@ -1149,6 +1195,11 @@ struct test {
tensor_split_str += "/";
}
}
auto ser_to_string = [] (const Ser& ser) {
std::ostringstream str;
str << ser.first << ',' << ser.second;
return str.str();
};
std::vector<std::string> values = {
build_commit, std::to_string(build_number),
std::to_string(cuda), std::to_string(vulkan), std::to_string(vulkan),
@@ -1158,7 +1209,8 @@ struct test {
std::to_string(n_batch), std::to_string(n_ubatch),
std::to_string(n_threads), ggml_type_name(type_k), ggml_type_name(type_v),
std::to_string(n_gpu_layers), split_mode_str(split_mode),
std::to_string(main_gpu), std::to_string(no_kv_offload), std::to_string(flash_attn), std::to_string(mla_attn), std::to_string(attn_max_batch),
std::to_string(main_gpu), std::to_string(no_kv_offload), std::to_string(flash_attn),
std::to_string(mla_attn), std::to_string(attn_max_batch), ser_to_string(ser),
tensor_split_str, std::to_string(use_mmap), std::to_string(embeddings), std::to_string(repack), std::to_string(fmoe),
std::to_string(n_prompt), std::to_string(n_gen), test_time,
std::to_string(avg_ns()), std::to_string(stdev_ns()),
@@ -1328,6 +1380,9 @@ struct markdown_printer : public printer {
if (field == "attn_max_batch") {
return 5;
}
if (field == "ser") {
return 10;
}
if (field == "use_mmap") {
return 4;
}
@@ -1371,6 +1426,9 @@ struct markdown_printer : public printer {
if (field == "attn_max_batch") {
return "amb";
}
if (field == "attn_max_batch") {
return "ser";
}
if (field == "use_mmap") {
return "mmap";
}
@@ -1432,6 +1490,9 @@ struct markdown_printer : public printer {
if (params.attn_max_batch.size() > 1 || params.attn_max_batch != cmd_params_defaults.mla_attn) {
fields.emplace_back("attn_max_batch");
}
if (params.ser.size() > 1 || params.ser != cmd_params_defaults.ser) {
fields.emplace_back("ser");
}
if (params.tensor_split.size() > 1 || params.tensor_split != cmd_params_defaults.tensor_split) {
fields.emplace_back("tensor_split");
}