sampling : refactor init to use llama_sampling_params (#3696)
* sampling : refactor init to use llama_sampling_params * llama : combine repetition, frequency and presence penalties in 1 call * examples : remove embd-input and gptneox-wip * sampling : rename penalty params + reduce size of "prev" vector * sampling : add llama_sampling_print helper * sampling : hide prev behind API and apply #3661 ggml-ci
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30 changed files with 365 additions and 4502 deletions
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@ -4,5 +4,5 @@ install(TARGETS ${TARGET} RUNTIME)
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target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})
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target_compile_features(${TARGET} PRIVATE cxx_std_11)
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if(TARGET BUILD_INFO)
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add_dependencies(${TARGET} BUILD_INFO)
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add_dependencies(${TARGET} BUILD_INFO)
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endif()
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@ -39,8 +39,8 @@ static gpt_params * g_params;
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static std::vector<llama_token> * g_input_tokens;
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static std::ostringstream * g_output_ss;
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static std::vector<llama_token> * g_output_tokens;
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static bool is_interacting = false;
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static bool is_interacting = false;
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static void write_logfile(
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const llama_context * ctx, const gpt_params & params, const llama_model * model,
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@ -104,7 +104,7 @@ static void sigint_handler(int signo) {
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int main(int argc, char ** argv) {
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gpt_params params;
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llama_sampling_params & sparams = params.sampling_params;
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llama_sampling_params & sparams = params.sparams;
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g_params = ¶ms;
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if (!gpt_params_parse(argc, argv, params)) {
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@ -358,36 +358,10 @@ int main(int argc, char ** argv) {
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LOG_TEE("Input suffix: '%s'\n", params.input_suffix.c_str());
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}
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}
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LOG_TEE("sampling: repeat_last_n = %d, repeat_penalty = %f, presence_penalty = %f, frequency_penalty = %f, top_k = %d, tfs_z = %f, top_p = %f, typical_p = %f, temp = %f, mirostat = %d, mirostat_lr = %f, mirostat_ent = %f\n",
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sparams.repeat_last_n, sparams.repeat_penalty, sparams.presence_penalty, sparams.frequency_penalty, sparams.top_k, sparams.tfs_z, sparams.top_p, sparams.typical_p, sparams.temp, sparams.mirostat, sparams.mirostat_eta, sparams.mirostat_tau);
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LOG_TEE("sampling: \n%s\n", llama_sampling_print(sparams).c_str());
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LOG_TEE("generate: n_ctx = %d, n_batch = %d, n_predict = %d, n_keep = %d\n", n_ctx, params.n_batch, params.n_predict, params.n_keep);
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LOG_TEE("\n\n");
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struct llama_grammar * grammar = NULL;
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grammar_parser::parse_state parsed_grammar;
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if (!params.grammar.empty()) {
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parsed_grammar = grammar_parser::parse(params.grammar.c_str());
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// will be empty (default) if there are parse errors
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if (parsed_grammar.rules.empty()) {
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return 1;
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}
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LOG_TEE("%s: grammar:\n", __func__);
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grammar_parser::print_grammar(stderr, parsed_grammar);
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LOG_TEE("\n");
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{
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auto it = sparams.logit_bias.find(llama_token_eos(ctx));
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if (it != sparams.logit_bias.end() && it->second == -INFINITY) {
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LOG_TEE("%s: warning: EOS token is disabled, which will cause most grammars to fail\n", __func__);
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}
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}
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std::vector<const llama_grammar_element *> grammar_rules(parsed_grammar.c_rules());
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grammar = llama_grammar_init(
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grammar_rules.data(), grammar_rules.size(), parsed_grammar.symbol_ids.at("root"));
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}
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LOG_TEE("\n##### Infill mode #####\n\n");
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if (params.infill) {
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printf("\n************\n");
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@ -430,7 +404,7 @@ int main(int argc, char ** argv) {
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std::vector<llama_token> embd;
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std::vector<llama_token> embd_guidance;
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struct llama_sampling_context * ctx_sampling = llama_sampling_init(params);
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struct llama_sampling_context * ctx_sampling = llama_sampling_init(sparams);
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while (n_remain != 0 || params.interactive) {
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// predict
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@ -549,7 +523,7 @@ int main(int argc, char ** argv) {
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const llama_token id = llama_sampling_sample(ctx_sampling, ctx, ctx_guidance);
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llama_sampling_accept(ctx_sampling, ctx, id);
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llama_sampling_accept(ctx_sampling, ctx, id, true);
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LOG("last: %s\n", LOG_TOKENS_TOSTR_PRETTY(ctx, ctx_sampling->prev).c_str());
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@ -567,8 +541,11 @@ int main(int argc, char ** argv) {
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LOG("embd_inp.size(): %d, n_consumed: %d\n", (int) embd_inp.size(), n_consumed);
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while ((int) embd_inp.size() > n_consumed) {
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embd.push_back(embd_inp[n_consumed]);
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ctx_sampling->prev.erase(ctx_sampling->prev.begin());
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ctx_sampling->prev.push_back(embd_inp[n_consumed]);
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// push the prompt in the sampling context in order to apply repetition penalties later
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// for the prompt, we don't apply grammar rules
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llama_sampling_accept(ctx_sampling, ctx, embd_inp[n_consumed], false);
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++n_consumed;
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if ((int) embd.size() >= params.n_batch) {
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break;
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@ -600,7 +577,7 @@ int main(int argc, char ** argv) {
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if ((int) embd_inp.size() <= n_consumed) {
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// deal with eot token in infill mode
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if ((ctx_sampling->prev.back() == llama_token_eot(ctx) || is_interacting) && params.interactive){
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if ((llama_sampling_last(ctx_sampling) == llama_token_eot(ctx) || is_interacting) && params.interactive){
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if(is_interacting && !params.interactive_first) {
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// print an eot token
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printf("%s", llama_token_to_piece(ctx, llama_token_eot(ctx)).c_str());
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@ -617,7 +594,7 @@ int main(int argc, char ** argv) {
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buffer += line;
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} while (another_line);
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// check if we got an empty line, if so we use the old input
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if(!buffer.empty() && !(buffer.length() == 1 && buffer[0] == '\n')) {
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if (!buffer.empty() && !(buffer.length() == 1 && buffer[0] == '\n')) {
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params.input_prefix = buffer;
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}
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buffer.clear();
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@ -627,7 +604,7 @@ int main(int argc, char ** argv) {
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buffer += line;
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} while (another_line);
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// check if we got an empty line
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if(!buffer.empty() && !(buffer.length() == 1 && buffer[0] == '\n')) {
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if (!buffer.empty() && !(buffer.length() == 1 && buffer[0] == '\n')) {
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params.input_suffix = buffer;
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}
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buffer.clear();
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@ -640,7 +617,7 @@ int main(int argc, char ** argv) {
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process_escapes(params.input_suffix);
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}
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suff_rm_leading_spc = params.escape;
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if (suff_rm_leading_spc && params.input_suffix.find_first_of(" ") == 0 && params.input_suffix.size() > 1) {
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if (suff_rm_leading_spc && params.input_suffix.find_first_of(' ') == 0 && params.input_suffix.size() > 1) {
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params.input_suffix.erase(0, 1);
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suff_rm_leading_spc = false;
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}
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@ -667,7 +644,7 @@ int main(int argc, char ** argv) {
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is_interacting = false;
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}
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// deal with end of text token in interactive mode
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else if (ctx_sampling->prev.back() == llama_token_eos(ctx)) {
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else if (llama_sampling_last(ctx_sampling) == llama_token_eos(ctx)) {
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LOG("found EOS token\n");
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if (params.interactive) {
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@ -740,15 +717,7 @@ int main(int argc, char ** argv) {
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if (n_past > 0) {
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if (is_interacting) {
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// reset grammar state if we're restarting generation
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if (grammar != NULL) {
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llama_grammar_free(grammar);
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std::vector<const llama_grammar_element *> grammar_rules(parsed_grammar.c_rules());
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grammar = llama_grammar_init(
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grammar_rules.data(), grammar_rules.size(),
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parsed_grammar.symbol_ids.at("root"));
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}
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llama_sampling_reset(ctx_sampling);
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}
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is_interacting = false;
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}
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@ -778,9 +747,7 @@ int main(int argc, char ** argv) {
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llama_free(ctx);
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llama_free_model(model);
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if (grammar != NULL) {
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llama_grammar_free(grammar);
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}
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llama_sampling_free(ctx_sampling);
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llama_backend_free();
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#ifndef LOG_DISABLE_LOGS
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