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batched-bench : add "separate text gen" mode (#17103)
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@@ -2253,6 +2253,13 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
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params.is_pp_shared = true;
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}
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).set_examples({LLAMA_EXAMPLE_BENCH, LLAMA_EXAMPLE_PARALLEL}));
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add_opt(common_arg(
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{"-tgs"},
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string_format("is the text generation separated across the different sequences (default: %s)", params.is_tg_separate ? "true" : "false"),
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[](common_params & params) {
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params.is_tg_separate = true;
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}
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).set_examples({LLAMA_EXAMPLE_BENCH, LLAMA_EXAMPLE_PARALLEL}));
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add_opt(common_arg(
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{"-npp"}, "n0,n1,...",
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"number of prompt tokens",
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@@ -460,7 +460,8 @@ struct common_params {
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float slot_prompt_similarity = 0.1f;
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// batched-bench params
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bool is_pp_shared = false;
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bool is_pp_shared = false;
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bool is_tg_separate = false;
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std::vector<int32_t> n_pp;
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std::vector<int32_t> n_tg;
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@@ -23,7 +23,8 @@ int main(int argc, char ** argv) {
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common_init();
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int is_pp_shared = params.is_pp_shared;
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int is_pp_shared = params.is_pp_shared;
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int is_tg_separate = params.is_tg_separate;
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std::vector<int> n_pp = params.n_pp;
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std::vector<int> n_tg = params.n_tg;
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@@ -72,8 +73,8 @@ int main(int argc, char ** argv) {
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// decode in batches of ctx_params.n_batch tokens
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auto decode_helper = [](llama_context * ctx, llama_batch & batch, int32_t n_batch, bool synchronize) {
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for (int32_t i = 0; i < (int32_t) batch.n_tokens; i += n_batch) {
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const int32_t n_tokens = std::min(n_batch, (int32_t) (batch.n_tokens - i));
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for (int32_t i = 0; i < batch.n_tokens; i += n_batch) {
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const int32_t n_tokens = std::min(n_batch, batch.n_tokens - i);
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llama_batch batch_view = {
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n_tokens,
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@@ -113,7 +114,7 @@ int main(int argc, char ** argv) {
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if (!params.batched_bench_output_jsonl) {
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LOG("\n");
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LOG("%s: n_kv_max = %d, n_batch = %d, n_ubatch = %d, flash_attn = %d, is_pp_shared = %d, n_gpu_layers = %d, n_threads = %u, n_threads_batch = %u\n", __func__, n_kv_max, params.n_batch, params.n_ubatch, int(params.flash_attn_type), params.is_pp_shared, params.n_gpu_layers, ctx_params.n_threads, ctx_params.n_threads_batch);
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LOG("%s: n_kv_max = %d, n_batch = %d, n_ubatch = %d, flash_attn = %d, is_pp_shared = %d, is_tg_separate = %d, n_gpu_layers = %d, n_threads = %u, n_threads_batch = %u\n", __func__, n_kv_max, params.n_batch, params.n_ubatch, int(params.flash_attn_type), is_pp_shared, is_tg_separate, params.n_gpu_layers, ctx_params.n_threads, ctx_params.n_threads_batch);
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LOG("\n");
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LOG("|%6s | %6s | %4s | %6s | %8s | %8s | %8s | %8s | %8s | %8s |\n", "PP", "TG", "B", "N_KV", "T_PP s", "S_PP t/s", "T_TG s", "S_TG t/s", "T s", "S t/s");
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LOG("|%6s-|-%6s-|-%4s-|-%6s-|-%8s-|-%8s-|-%8s-|-%8s-|-%8s-|-%8s-|\n", "------", "------", "----", "------", "--------", "--------", "--------", "--------", "--------", "--------");
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@@ -172,16 +173,35 @@ int main(int argc, char ** argv) {
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const auto t_tg_start = ggml_time_us();
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for (int i = 0; i < tg; ++i) {
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common_batch_clear(batch);
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if (is_tg_separate) {
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// decode pattern:
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// 0 0 0 ... 1 1 1 ... 2 2 2 ... 3 3 3 ...
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for (int j = 0; j < pl; ++j) {
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common_batch_add(batch, get_token_rand(), pp + i, { j }, true);
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}
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for (int i = 0; i < tg; ++i) {
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common_batch_clear(batch);
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if (!decode_helper(ctx, batch, ctx_params.n_batch, true)) {
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LOG_ERR("%s: llama_decode() failed\n", __func__);
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return 1;
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common_batch_add(batch, get_token_rand(), pp + i, { j }, true);
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if (!decode_helper(ctx, batch, ctx_params.n_batch, true)) {
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LOG_ERR("%s: llama_decode() failed\n", __func__);
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return 1;
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}
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}
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}
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} else {
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// decode pattern:
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// 0123 0123 0123 ...
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for (int i = 0; i < tg; ++i) {
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common_batch_clear(batch);
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for (int j = 0; j < pl; ++j) {
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common_batch_add(batch, get_token_rand(), pp + i, { j }, true);
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}
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if (!decode_helper(ctx, batch, ctx_params.n_batch, true)) {
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LOG_ERR("%s: llama_decode() failed\n", __func__);
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return 1;
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}
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}
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}
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