From d1031cf49c3b958b915fd558e23453471c29ac33 Mon Sep 17 00:00:00 2001 From: Georgi Gerganov Date: Fri, 20 Oct 2023 21:07:23 +0300 Subject: 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 --- common/sampling.cpp | 73 +++++++++++++++++++++++++++++++++++++---------------- 1 file changed, 51 insertions(+), 22 deletions(-) (limited to 'common/sampling.cpp') diff --git a/common/sampling.cpp b/common/sampling.cpp index 0b246658..6f0af3c4 100644 --- a/common/sampling.cpp +++ b/common/sampling.cpp @@ -1,9 +1,9 @@ #include "sampling.h" -struct llama_sampling_context * llama_sampling_init(const struct gpt_params & params) { +struct llama_sampling_context * llama_sampling_init(const struct llama_sampling_params & params) { struct llama_sampling_context * result = new llama_sampling_context(); - result->params = params.sampling_params; + result->params = params; result->grammar = nullptr; // if there is a grammar, parse it @@ -23,7 +23,7 @@ struct llama_sampling_context * llama_sampling_init(const struct gpt_params & pa grammar_rules.size(), result->parsed_grammar.symbol_ids.at("root")); } - result->prev.resize(params.n_ctx); + result->prev.resize(params.n_prev); return result; } @@ -66,25 +66,56 @@ void llama_sampling_cp(llama_sampling_context * src, llama_sampling_context * ds dst->prev = src->prev; } +llama_token llama_sampling_last(llama_sampling_context * ctx) { + return ctx->prev.back(); +} + +std::string llama_sampling_prev_str(llama_sampling_context * ctx_sampling, llama_context * ctx_main, int n) { + const int size = ctx_sampling->prev.size(); + + n = std::min(n, size); + + std::string result; + + for (int i = size - n; i < size; i++) { + result += llama_token_to_piece(ctx_main, ctx_sampling->prev[i]); + } + + return result; +} + +std::string llama_sampling_print(const llama_sampling_params & params) { + char result[1024]; + + snprintf(result, sizeof(result), + "\trepeat_last_n = %d, repeat_penalty = %.3f, frequency_penalty = %.3f, presence_penalty = %.3f\n" + "\ttop_k = %d, tfs_z = %.3f, top_p = %.3f, typical_p = %.3f, temp = %.3f\n" + "\tmirostat = %d, mirostat_lr = %.3f, mirostat_ent = %.3f", + params.penalty_last_n, params.penalty_repeat, params.penalty_freq, params.penalty_present, + params.top_k, params.tfs_z, params.top_p, params.typical_p, params.temp, + params.mirostat, params.mirostat_eta, params.mirostat_tau); + + return std::string(result); +} + llama_token llama_sampling_sample( struct llama_sampling_context * ctx_sampling, struct llama_context * ctx_main, struct llama_context * ctx_cfg, const int idx) { - const int n_ctx = llama_n_ctx(ctx_main); - const int n_vocab = llama_n_vocab(llama_get_model(ctx_main)); - const llama_sampling_params & params = ctx_sampling->params; + const int n_vocab = llama_n_vocab(llama_get_model(ctx_main)); + const float temp = params.temp; const int32_t top_k = params.top_k <= 0 ? n_vocab : params.top_k; const float top_p = params.top_p; const float tfs_z = params.tfs_z; const float typical_p = params.typical_p; - const int32_t repeat_last_n = params.repeat_last_n < 0 ? n_ctx : params.repeat_last_n; - const float repeat_penalty = params.repeat_penalty; - const float alpha_presence = params.presence_penalty; - const float alpha_frequency = params.frequency_penalty; + const int32_t penalty_last_n = params.penalty_last_n < 0 ? params.n_prev : params.penalty_last_n; + const float penalty_repeat = params.penalty_repeat; + const float penalty_freq = params.penalty_freq; + const float penalty_present = params.penalty_present; const int mirostat = params.mirostat; const float mirostat_tau = params.mirostat_tau; const float mirostat_eta = params.mirostat_eta; @@ -97,7 +128,7 @@ llama_token llama_sampling_sample( float * logits = llama_get_logits_ith(ctx_main, idx); - // Apply params.logit_bias map + // apply params.logit_bias map for (auto it = params.logit_bias.begin(); it != params.logit_bias.end(); it++) { logits[it->first] += it->second; } @@ -117,14 +148,10 @@ llama_token llama_sampling_sample( // apply penalties if (!prev.empty()) { const float nl_logit = logits[llama_token_nl(ctx_main)]; - const int last_n_repeat = std::min(std::min((int)prev.size(), repeat_last_n), n_ctx); - llama_sample_repetition_penalty(ctx_main, &cur_p, - prev.data() + prev.size() - last_n_repeat, - last_n_repeat, repeat_penalty); - llama_sample_frequency_and_presence_penalties(ctx_main, &cur_p, - prev.data() + prev.size() - last_n_repeat, - last_n_repeat, alpha_frequency, alpha_presence); + llama_sample_repetition_penalties(ctx_main, &cur_p, + prev.data() + prev.size() - penalty_last_n, + penalty_last_n, penalty_repeat, penalty_freq, penalty_present); if (!penalize_nl) { for (size_t idx = 0; idx < cur_p.size; idx++) { @@ -141,7 +168,7 @@ llama_token llama_sampling_sample( } if (temp <= 0) { - // Greedy sampling + // greedy sampling id = llama_sample_token_greedy(ctx_main, &cur_p); } else { if (mirostat == 1) { @@ -152,8 +179,9 @@ llama_token llama_sampling_sample( llama_sample_temp(ctx_main, &cur_p, temp); id = llama_sample_token_mirostat_v2(ctx_main, &cur_p, mirostat_tau, mirostat_eta, &ctx_sampling->mirostat_mu); } else { - // Temperature sampling + // temperature sampling size_t min_keep = std::max(1, params.n_probs); + llama_sample_top_k (ctx_main, &cur_p, top_k, min_keep); llama_sample_tail_free(ctx_main, &cur_p, tfs_z, min_keep); llama_sample_typical (ctx_main, &cur_p, typical_p, min_keep); @@ -183,11 +211,12 @@ llama_token llama_sampling_sample( void llama_sampling_accept( struct llama_sampling_context * ctx_sampling, struct llama_context * ctx_main, - llama_token id) { + llama_token id, + bool apply_grammar) { ctx_sampling->prev.erase(ctx_sampling->prev.begin()); ctx_sampling->prev.push_back(id); - if (ctx_sampling->grammar != NULL) { + if (ctx_sampling->grammar != NULL && apply_grammar) { llama_grammar_accept_token(ctx_main, ctx_sampling->grammar, id); } } -- cgit v1.2.3