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synced 2024-12-28 12:24:35 +00:00
parallel : rename hot-plug to continuous-batching
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@ -372,8 +372,8 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
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params.multiline_input = true;
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} else if (arg == "--simple-io") {
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params.simple_io = true;
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} else if (arg == "--hot-plug") {
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params.hot_plug = true;
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} else if (arg == "-cb" || arg == "--cont-batching") {
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params.cont_batching = true;
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} else if (arg == "--color") {
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params.use_color = true;
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} else if (arg == "--mlock") {
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@ -675,7 +675,7 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
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printf(" --chunks N max number of chunks to process (default: %d, -1 = all)\n", params.n_chunks);
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printf(" -np N, --parallel N number of parallel sequences to decode (default: %d)\n", params.n_parallel);
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printf(" -ns N, --sequences N number of sequences to decode (default: %d)\n", params.n_sequences);
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printf(" --hot-plug enable hot-plugging of new sequences for decoding (default: disabled)\n");
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printf(" -cb, --cont-batching enable continuous batching (a.k.a dynamic batching) (default: disabled)\n");
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if (llama_mlock_supported()) {
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printf(" --mlock force system to keep model in RAM rather than swapping or compressing\n");
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}
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@ -1270,7 +1270,7 @@ void dump_non_result_info_yaml(FILE * stream, const gpt_params & params, const l
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fprintf(stream, "rope_freq_scale: %f # default: 1.0\n", params.rope_freq_scale);
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fprintf(stream, "seed: %d # default: -1 (random seed)\n", params.seed);
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fprintf(stream, "simple_io: %s # default: false\n", params.simple_io ? "true" : "false");
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fprintf(stream, "hot_plug: %s # default: false\n", params.hot_plug ? "true" : "false");
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fprintf(stream, "cont_batching: %s # default: false\n", params.cont_batching ? "true" : "false");
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fprintf(stream, "temp: %f # default: 0.8\n", params.temp);
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const std::vector<float> tensor_split_vector(params.tensor_split, params.tensor_split + LLAMA_MAX_DEVICES);
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@ -110,7 +110,7 @@ struct gpt_params {
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bool interactive_first = false; // wait for user input immediately
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bool multiline_input = false; // reverse the usage of `\`
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bool simple_io = false; // improves compatibility with subprocesses and limited consoles
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bool hot_plug = false; // hot-plug new sequences for decoding
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bool cont_batching = false; // insert new sequences for decoding on-the-fly
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bool input_prefix_bos = false; // prefix BOS to user inputs, preceding input_prefix
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bool ignore_eos = false; // ignore generated EOS tokens
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@ -86,7 +86,7 @@ int main(int argc, char ** argv) {
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const int32_t n_seq = params.n_sequences;
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// insert new requests as soon as the previous one is done
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const bool hot_plug = params.hot_plug;
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const bool cont_batching = params.cont_batching;
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#ifndef LOG_DISABLE_LOGS
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log_set_target(log_filename_generator("parallel", "log"));
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@ -140,7 +140,7 @@ int main(int argc, char ** argv) {
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const auto t_main_start = ggml_time_us();
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LOG_TEE("%s: Simulating parallel requests from clients:\n", __func__);
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LOG_TEE("%s: n_parallel = %d, n_sequences = %d, hot_plug = %d, system tokens = %d\n", __func__, n_clients, n_seq, hot_plug, n_tokens_system);
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LOG_TEE("%s: n_parallel = %d, n_sequences = %d, cont_batching = %d, system tokens = %d\n", __func__, n_clients, n_seq, cont_batching, n_tokens_system);
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LOG_TEE("\n");
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{
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@ -208,7 +208,7 @@ int main(int argc, char ** argv) {
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}
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}
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if (hot_plug || batch_token.empty()) {
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if (cont_batching || batch_token.empty()) {
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for (auto & client : clients) {
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if (client.seq_id == -1 && g_seq_id < n_seq) {
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client.seq_id = g_seq_id;
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@ -237,9 +237,9 @@ int main(int argc, char ** argv) {
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client.i_batch = batch_token.size() - 1;
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g_seq_id += 1;
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if (hot_plug) {
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//break;
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}
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//if (cont_batching) {
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// break;
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//}
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}
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}
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}
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