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May 10, 2024
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llama-bench : add pp+tg test type #7199

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llama-bench : add pp+tg test type
slaren May 10, 2024
e9a3ba6
update llama-bench readme
slaren May 10, 2024
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18 changes: 12 additions & 6 deletions examples/llama-bench/README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -26,27 +26,33 @@ options:
-m, --model <filename> (default: models/7B/ggml-model-q4_0.gguf)
-p, --n-prompt <n> (default: 512)
-n, --n-gen <n> (default: 128)
-b, --batch-size <n> (default: 512)
-ctk <t>, --cache-type-k <t> (default: f16)
-ctv <t>, --cache-type-v <t> (default: f16)
-t, --threads <n> (default: 112)
-pg <pp,tg> (default: 512,128)
-b, --batch-size <n> (default: 2048)
-ub, --ubatch-size <n> (default: 512)
-ctk, --cache-type-k <t> (default: f16)
-ctv, --cache-type-v <t> (default: f16)
-t, --threads <n> (default: 16)
-ngl, --n-gpu-layers <n> (default: 99)
-sm, --split-mode <none|layer|row> (default: layer)
-mg, --main-gpu <i> (default: 0)
-nkvo, --no-kv-offload <0|1> (default: 0)
-fa, --flash-attn <0|1> (default: 0)
-mmp, --mmap <0|1> (default: 1)
-ts, --tensor_split <ts0/ts1/..> (default: 0)
--numa <distribute|isolate|numactl> (default: disabled)
-embd, --embeddings <0|1> (default: 0)
-ts, --tensor-split <ts0/ts1/..> (default: 0)
-r, --repetitions <n> (default: 5)
-o, --output <csv|json|md|sql> (default: md)
-v, --verbose (default: 0)

Multiple values can be given for each parameter by separating them with ',' or by specifying the parameter multiple times.
```

llama-bench can perform two types of tests:
llama-bench can perform three types of tests:

- Prompt processing (pp): processing a prompt in batches (`-p`)
- Text generation (tg): generating a sequence of tokens (`-n`)
- Prompt processing + text generation (pg): processing a prompt followed by generating a sequence of tokens (`-pg`)

With the exception of `-r`, `-o` and `-v`, all options can be specified multiple times to run multiple tests. Each pp and tg test is run with all combinations of the specified options. To specify multiple values for an option, the values can be separated by commas (e.g. `-n 16,32`), or the option can be specified multiple times (e.g. `-n 16 -n 32`).

Expand Down
63 changes: 56 additions & 7 deletions examples/llama-bench/llama-bench.cpp
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Expand Up @@ -161,10 +161,17 @@ static const char * split_mode_str(llama_split_mode mode) {
}
}

static std::string pair_str(const std::pair<int, int> & p) {
static char buf[32];
snprintf(buf, sizeof(buf), "%d,%d", p.first, p.second);
return buf;
}

struct cmd_params {
std::vector<std::string> model;
std::vector<int> n_prompt;
std::vector<int> n_gen;
std::vector<std::pair<int, int>> n_pg;
std::vector<int> n_batch;
std::vector<int> n_ubatch;
std::vector<ggml_type> type_k;
Expand All @@ -188,6 +195,7 @@ static const cmd_params cmd_params_defaults = {
/* model */ {"models/7B/ggml-model-q4_0.gguf"},
/* n_prompt */ {512},
/* n_gen */ {128},
/* n_pg */ {{512, 128}},
/* n_batch */ {2048},
/* n_ubatch */ {512},
/* type_k */ {GGML_TYPE_F16},
Expand Down Expand Up @@ -215,10 +223,11 @@ static void print_usage(int /* argc */, char ** argv) {
printf(" -m, --model <filename> (default: %s)\n", join(cmd_params_defaults.model, ",").c_str());
printf(" -p, --n-prompt <n> (default: %s)\n", join(cmd_params_defaults.n_prompt, ",").c_str());
printf(" -n, --n-gen <n> (default: %s)\n", join(cmd_params_defaults.n_gen, ",").c_str());
printf(" -pg <pp,tg> (default: %s)\n", join(transform_to_str(cmd_params_defaults.n_pg, pair_str), ",").c_str());
printf(" -b, --batch-size <n> (default: %s)\n", join(cmd_params_defaults.n_batch, ",").c_str());
printf(" -ub N, --ubatch-size <n> (default: %s)\n", join(cmd_params_defaults.n_ubatch, ",").c_str());
printf(" -ctk <t>, --cache-type-k <t> (default: %s)\n", join(transform_to_str(cmd_params_defaults.type_k, ggml_type_name), ",").c_str());
printf(" -ctv <t>, --cache-type-v <t> (default: %s)\n", join(transform_to_str(cmd_params_defaults.type_v, ggml_type_name), ",").c_str());
printf(" -ub, --ubatch-size <n> (default: %s)\n", join(cmd_params_defaults.n_ubatch, ",").c_str());
printf(" -ctk, --cache-type-k <t> (default: %s)\n", join(transform_to_str(cmd_params_defaults.type_k, ggml_type_name), ",").c_str());
printf(" -ctv, --cache-type-v <t> (default: %s)\n", join(transform_to_str(cmd_params_defaults.type_v, ggml_type_name), ",").c_str());
printf(" -t, --threads <n> (default: %s)\n", join(cmd_params_defaults.n_threads, ",").c_str());
printf(" -ngl, --n-gpu-layers <n> (default: %s)\n", join(cmd_params_defaults.n_gpu_layers, ",").c_str());
printf(" -sm, --split-mode <none|layer|row> (default: %s)\n", join(transform_to_str(cmd_params_defaults.split_mode, split_mode_str), ",").c_str());
Expand Down Expand Up @@ -304,6 +313,17 @@ static cmd_params parse_cmd_params(int argc, char ** argv) {
}
auto p = split<int>(argv[i], split_delim);
params.n_gen.insert(params.n_gen.end(), p.begin(), p.end());
} else if (arg == "-pg") {
if (++i >= argc) {
invalid_param = true;
break;
}
auto p = split<std::string>(argv[i], ',');
if (p.size() != 2) {
invalid_param = true;
break;
}
params.n_pg.push_back({std::stoi(p[0]), std::stoi(p[1])});
} else if (arg == "-b" || arg == "--batch-size") {
if (++i >= argc) {
invalid_param = true;
Expand Down Expand Up @@ -493,6 +513,7 @@ static cmd_params parse_cmd_params(int argc, char ** argv) {
if (params.model.empty()) { params.model = cmd_params_defaults.model; }
if (params.n_prompt.empty()) { params.n_prompt = cmd_params_defaults.n_prompt; }
if (params.n_gen.empty()) { params.n_gen = cmd_params_defaults.n_gen; }
if (params.n_pg.empty()) { params.n_pg = cmd_params_defaults.n_pg; }
if (params.n_batch.empty()) { params.n_batch = cmd_params_defaults.n_batch; }
if (params.n_ubatch.empty()) { params.n_ubatch = cmd_params_defaults.n_ubatch; }
if (params.type_k.empty()) { params.type_k = cmd_params_defaults.type_k; }
Expand Down Expand Up @@ -632,6 +653,31 @@ static std::vector<cmd_params_instance> get_cmd_params_instances(const cmd_param
};
instances.push_back(instance);
}

for (const auto & n_pg : params.n_pg) {
if (n_pg.first == 0 && n_pg.second == 0) {
continue;
}
cmd_params_instance instance = {
/* .model = */ m,
/* .n_prompt = */ n_pg.first,
/* .n_gen = */ n_pg.second,
/* .n_batch = */ nb,
/* .n_ubatch = */ nub,
/* .type_k = */ tk,
/* .type_v = */ tv,
/* .n_threads = */ nt,
/* .n_gpu_layers = */ nl,
/* .split_mode = */ sm,
/* .main_gpu = */ mg,
/* .no_kv_offload= */ nkvo,
/* .flash_attn = */ fa,
/* .tensor_split = */ ts,
/* .use_mmap = */ mmp,
/* .embeddings = */ embd,
};
instances.push_back(instance);
}
}

return instances;
Expand Down Expand Up @@ -965,6 +1011,9 @@ struct markdown_printer : public printer {
if (field == "n_gpu_layers") {
return 3;
}
if (field == "test") {
return 13;
}

int width = std::max((int)field.length(), 10);

Expand Down Expand Up @@ -1091,12 +1140,11 @@ struct markdown_printer : public printer {
value = test::get_backend();
} else if (field == "test") {
if (t.n_prompt > 0 && t.n_gen == 0) {
snprintf(buf, sizeof(buf), "pp %d", t.n_prompt);
snprintf(buf, sizeof(buf), "pp%d", t.n_prompt);
} else if (t.n_gen > 0 && t.n_prompt == 0) {
snprintf(buf, sizeof(buf), "tg %d", t.n_gen);
snprintf(buf, sizeof(buf), "tg%d", t.n_gen);
} else {
assert(false);
exit(1);
snprintf(buf, sizeof(buf), "pp%d+tg%d", t.n_prompt, t.n_gen);
}
value = buf;
} else if (field == "t/s") {
Expand Down Expand Up @@ -1297,6 +1345,7 @@ int main(int argc, char ** argv) {
llama_kv_cache_clear(ctx);

uint64_t t_start = get_time_ns();

if (t.n_prompt > 0) {
test_prompt(ctx, t.n_prompt, 0, t.n_batch, t.n_threads);
}
Expand Down
8 changes: 6 additions & 2 deletions scripts/compare-llama-bench.py
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Expand Up @@ -325,8 +325,12 @@ def get_rows(properties):
for row in rows_show:
n_prompt = int(row[-4])
n_gen = int(row[-3])
assert n_prompt == 0 or n_gen == 0
test_name = f"tg{n_gen}" if n_prompt == 0 else f"pp{n_prompt}"
if n_prompt != 0 and n_gen == 0:
test_name = f"pp{n_prompt}"
elif n_prompt == 0 and n_gen != 0:
test_name = f"tg{n_gen}"
else:
test_name = f"pp{n_prompt}+tg{n_gen}"
# Regular columns test name avg t/s values Speedup
# VVVVVVVVVVVVV VVVVVVVVV VVVVVVVVVVVVVV VVVVVVV
table.append(list(row[:-4]) + [test_name] + list(row[-2:]) + [float(row[-1]) / float(row[-2])])
Expand Down
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