llama-bench : add pp+tg test type (#7199)

diff --git a/examples/llama-bench/README.md b/examples/llama-bench/README.md
index 10f37b4418897e16673490f6a6febcc8d04d68df..8578405646af7f78bf368c6f4baed935614c2ab1 100644 (file)
--- a/examples/llama-bench/README.md
+++ b/examples/llama-bench/README.md
@@ -26,16 +26,21 @@ 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)
@@ -43,10 +48,11 @@ options:
 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`).
 

diff --git a/examples/llama-bench/llama-bench.cpp b/examples/llama-bench/llama-bench.cpp
index 40128ec444334797a119b6ea27e35e1ba3302c16..8b965e1990ba5d8486a7db716b91bd2431bcc7fd 100644 (file)
--- a/examples/llama-bench/llama-bench.cpp
+++ b/examples/llama-bench/llama-bench.cpp
@@ -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;
@@ -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},
@@ -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());
@@ -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;
@@ -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; }
@@ -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;
@@ -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);
 
@@ -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") {
@@ -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);
             }

diff --git a/scripts/compare-llama-bench.py b/scripts/compare-llama-bench.py
index fed3c1ee3d298349047dd2a072ec232778f2aa03..0ede9e67c2f150f83ad07342f50dcf73aa1313c9 100755 (executable)
--- a/scripts/compare-llama-bench.py
+++ b/scripts/compare-llama-bench.py
@@ -325,8 +325,12 @@ table = []
 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])])