diff options
Diffstat (limited to 'common')
| -rw-r--r-- | common/common.cpp | 50 | ||||
| -rw-r--r-- | common/sampling.cpp | 69 | ||||
| -rw-r--r-- | common/sampling.h | 17 |
3 files changed, 114 insertions, 22 deletions
diff --git a/common/common.cpp b/common/common.cpp index 20e583fc..208d4511 100644 --- a/common/common.cpp +++ b/common/common.cpp @@ -666,6 +666,47 @@ bool gpt_params_find_arg(int argc, char ** argv, const std::string & arg, gpt_pa sparams.top_n_sigma = std::stof(argv[i]); return true; } + + if (arg == "--dry-multiplier") { + CHECK_ARG + sparams.dry_multiplier = std::stof(argv[i]); + return true; + } + if (arg == "--dry-base") { + CHECK_ARG + sparams.dry_base = std::stof(argv[i]); + return true; + } + if (arg == "--dry-allowed-length") { + CHECK_ARG + sparams.dry_allowed_length = std::stof(argv[i]); + return true; + } + if (arg == "--dry-penalty-last-n") { + CHECK_ARG + sparams.dry_penalty_last_n = std::stof(argv[i]); + return true; + } + if (arg == "--dry-sequence-breaker") { + CHECK_ARG + static bool defaults_cleared = false; + + if (!defaults_cleared) { + params.sparams.dry_sequence_breakers.clear(); + defaults_cleared = true; + } + std::string value= std::string(argv[i]); + if (value == "none") { + params.sparams.dry_sequence_breakers.clear(); + } + else { + for (size_t i; i < value.size(); i++) + { + params.sparams.dry_sequence_breakers.emplace_back(""+value[i]); + } + } + return true; + } if (arg == "--cfg-negative-prompt") { CHECK_ARG sparams.cfg_negative_prompt = argv[i]; @@ -2326,6 +2367,11 @@ struct llama_init_result llama_init_from_gpt_params(gpt_params & params) { params.sparams.logit_bias[llama_token_eos(model)] = -INFINITY; } + if (params.sparams.dry_penalty_last_n == -1) { + LOG("%s: setting dry_penalty_last_n to ctx_size = %d\n", __func__, llama_n_ctx(lctx)); + params.sparams.dry_penalty_last_n = llama_n_ctx(lctx); + } + if (params.warmup) { LOG("warming up the model with an empty run\n"); @@ -3389,6 +3435,10 @@ void yaml_dump_non_result_info(FILE * stream, const gpt_params & params, const l fprintf(stream, "chunks: %d # default: -1 (unlimited)\n", params.n_chunks); fprintf(stream, "color: %s # default: false\n", params.use_color ? "true" : "false"); fprintf(stream, "ctx_size: %d # default: 512\n", params.n_ctx); + fprintf(stream, "dry_allowed_length: %d # default: 2\n", sparams.dry_allowed_length); + fprintf(stream, "dry_base: %.2f # default: 1.75\n", sparams.dry_base); + fprintf(stream, "dry_multiplier: %.1f # default: 0.0\n", sparams.dry_multiplier); + fprintf(stream, "dry_penalty_last_n: %d # default: -1 (0 = disable, -1 = context size)\n", sparams.dry_penalty_last_n); fprintf(stream, "escape: %s # default: false\n", params.escape ? "true" : "false"); fprintf(stream, "file: # never logged, see prompt instead. Can still be specified for input.\n"); fprintf(stream, "frequency_penalty: %f # default: 0.0 \n", sparams.penalty_freq); diff --git a/common/sampling.cpp b/common/sampling.cpp index 4db12ee1..4b983e5f 100644 --- a/common/sampling.cpp +++ b/common/sampling.cpp @@ -1,8 +1,9 @@ #define LLAMA_API_INTERNAL #include "sampling.h" +#include "llama-vocab.h" #include <random> -struct llama_sampling_context * llama_sampling_init(const struct llama_sampling_params & params) { +struct llama_sampling_context * llama_sampling_init(const struct llama_vocab* vocab, const struct llama_sampling_params & params) { struct llama_sampling_context * result = new llama_sampling_context(); result->params = params; @@ -36,13 +37,32 @@ struct llama_sampling_context * llama_sampling_init(const struct llama_sampling_ } result->grammar = grammar; } - result->prev.resize(params.n_prev); result->n_valid = 0; + // init DRY + for (const auto& cnstr : params.samplers_sequence) + { + switch (cnstr) + { + case llama_sampler_type::DRY: + { + std::vector<const char*> c_breakers; + c_breakers.reserve(params.dry_sequence_breakers.size()); + for (const auto& str : params.dry_sequence_breakers) + { + c_breakers.push_back(str.c_str()); + } + result->smpl=llama_sampler_init_dry(vocab, params.dry_multiplier, params.dry_base, params.dry_allowed_length, params.dry_penalty_last_n, c_breakers.data(), c_breakers.size()); + + break; + } + default: + break; + } + } llama_sampling_set_rng_seed(result, params.seed); - return result; } @@ -50,7 +70,8 @@ void llama_sampling_free(struct llama_sampling_context * ctx) { if (ctx->grammar != NULL) { llama_grammar_free(ctx->grammar); } - + if (ctx->smpl !=NULL) + llama_sampler_dry_free(ctx->smpl); delete ctx; } @@ -75,6 +96,7 @@ void llama_sampling_reset(llama_sampling_context * ctx) { std::fill(ctx->prev.begin(), ctx->prev.end(), 0); ctx->cur.clear(); ctx->n_valid = 0; + llama_sampler_dry_reset(ctx->smpl); } void llama_sampling_set_rng_seed(struct llama_sampling_context * ctx, uint32_t seed) { @@ -95,6 +117,7 @@ void llama_sampling_cp(llama_sampling_context * src, llama_sampling_context * ds } dst->prev = src->prev; + dst->smpl = llama_sampler_dry_clone(src->smpl); } llama_token llama_sampling_last(llama_sampling_context * ctx) { @@ -149,6 +172,7 @@ std::string llama_sampling_order_print(const llama_sampling_params & params) { std::string llama_sampling_type_to_str(llama_sampler_type sampler_type) { switch (sampler_type) { + case llama_sampler_type::DRY: return "dry"; case llama_sampler_type::TOP_K: return "top_k"; case llama_sampler_type::TFS_Z: return "tfs_z"; case llama_sampler_type::TYPICAL_P: return "typical_p"; @@ -163,6 +187,7 @@ std::string llama_sampling_type_to_str(llama_sampler_type sampler_type) { std::vector<llama_sampler_type> llama_sampling_types_from_names(const std::vector<std::string> & names, bool allow_alt_names) { std::unordered_map<std::string, llama_sampler_type> sampler_canonical_name_map { + {"dry", llama_sampler_type::DRY}, {"top_k", llama_sampler_type::TOP_K}, {"top_p", llama_sampler_type::TOP_P}, {"typical_p", llama_sampler_type::TYPICAL_P}, @@ -176,6 +201,7 @@ std::vector<llama_sampler_type> llama_sampling_types_from_names(const std::vecto // since samplers names are written multiple ways // make it ready for both system names and input names std::unordered_map<std::string, llama_sampler_type> sampler_alt_name_map { + {"dry", llama_sampler_type::DRY}, {"top-k", llama_sampler_type::TOP_K}, {"top-p", llama_sampler_type::TOP_P}, {"nucleus", llama_sampler_type::TOP_P}, @@ -215,6 +241,7 @@ std::vector<llama_sampler_type> llama_sampling_types_from_names(const std::vecto std::vector<llama_sampler_type> llama_sampling_types_from_chars(const std::string & names_string) { std::unordered_map<char, llama_sampler_type> sampler_name_map { + {'d', llama_sampler_type::DRY}, {'k', llama_sampler_type::TOP_K}, {'p', llama_sampler_type::TOP_P}, {'y', llama_sampler_type::TYPICAL_P}, @@ -238,25 +265,28 @@ std::vector<llama_sampler_type> llama_sampling_types_from_chars(const std::strin // no reasons to expose this function in header static void sampler_queue( - struct llama_context * ctx_main, - const llama_sampling_params & params, - llama_token_data_array & cur_p, - size_t min_keep) { - const float temp = params.temp; - const float dynatemp_range = params.dynatemp_range; + struct llama_context* ctx_main, + const llama_sampling_params& params, + llama_sampling_context * ctx_sampling, + llama_token_data_array& cur_p, + size_t min_keep) { + const float temp = params.temp; + const float dynatemp_range = params.dynatemp_range; const float dynatemp_exponent = params.dynatemp_exponent; - const int32_t top_k = params.top_k; - const float top_p = params.top_p; - const float min_p = params.min_p; - const float tfs_z = params.tfs_z; - const float typical_p = params.typical_p; - const float xtc_probability = params.xtc_probability; - const float xtc_threshold = params.xtc_threshold; - const float top_n_sigma = params.top_n_sigma; + const int32_t top_k = params.top_k; + const float top_p = params.top_p; + const float min_p = params.min_p; + const float tfs_z = params.tfs_z; + const float typical_p = params.typical_p; + const float xtc_probability = params.xtc_probability; + const float xtc_threshold = params.xtc_threshold; + const float top_n_sigma = params.top_n_sigma; + const std::vector<llama_sampler_type> & samplers_sequence = params.samplers_sequence; for (auto sampler_type : samplers_sequence) { switch (sampler_type) { + case llama_sampler_type::DRY : llama_sample_dry (ctx_main, ctx_sampling->smpl, &cur_p); break; case llama_sampler_type::TOP_K : llama_sample_top_k (ctx_main, &cur_p, top_k, min_keep); break; case llama_sampler_type::TFS_Z : llama_sample_tail_free(ctx_main, &cur_p, tfs_z, min_keep); break; case llama_sampler_type::TYPICAL_P : llama_sample_typical (ctx_main, &cur_p, typical_p, min_keep); break; @@ -317,7 +347,7 @@ static llama_token llama_sampling_sample_impl( // temperature sampling size_t min_keep = std::max(1, params.min_keep); - sampler_queue(ctx_main, params, cur_p, min_keep); + sampler_queue(ctx_main, params,ctx_sampling, cur_p, min_keep); id = llama_sample_token_with_rng(ctx_main, &cur_p, ctx_sampling->rng); @@ -472,4 +502,5 @@ void llama_sampling_accept( if (ctx_sampling->grammar != NULL && apply_grammar) { llama_grammar_accept_token(ctx_sampling->grammar, ctx_main, id); } + llama_sampler_dry_accept(ctx_sampling->smpl, id); } diff --git a/common/sampling.h b/common/sampling.h index 4fc86595..1d5bf0b9 100644 --- a/common/sampling.h +++ b/common/sampling.h @@ -35,11 +35,16 @@ typedef struct llama_sampling_params { float temp = 0.80f; // <= 0.0 to sample greedily, 0.0 to not output probabilities float dynatemp_range = 0.00f; // 0.0 = disabled float dynatemp_exponent = 1.00f; // controls how entropy maps to temperature in dynamic temperature sampler - int32_t penalty_last_n = 64; // last n tokens to penalize (0 = disable penalty, -1 = context size) + int32_t penalty_last_n = 64; // last n tokens to penalize (0 = disable penalty, -1 = context size) float penalty_repeat = 1.00f; // 1.0 = disabled float penalty_freq = 0.00f; // 0.0 = disabled float penalty_present = 0.00f; // 0.0 = disabled - int32_t mirostat = 0; // 0 = disabled, 1 = mirostat, 2 = mirostat 2.0 + float dry_multiplier = 0.0f; // 0.0 = disabled; DRY repetition penalty for tokens extending repetition: + float dry_base = 1.75f; // 0.0 = disabled; multiplier * base ^ (length of sequence before token - allowed length) + int32_t dry_allowed_length = 2; // tokens extending repetitions beyond this receive penalty + int32_t dry_penalty_last_n = -1; // how many tokens to scan for repetitions (0 = disable penalty, -1 = context size) + int32_t total_context_size = 16840; + int32_t mirostat = 0; // 0 = disabled, 1 = mirostat, 2 = mirostat 2.0 float mirostat_tau = 5.00f; // target entropy float mirostat_eta = 0.10f; // learning rate float xtc_probability = 0.0f; // xtc probability @@ -48,12 +53,16 @@ typedef struct llama_sampling_params { bool penalize_nl = false; // consider newlines as a repeatable token uint32_t seed = LLAMA_DEFAULT_SEED; // the seed used to initialize llama_sampling_context + std::vector<std::string> dry_sequence_breakers = { "\n", ":", "\"", "*" }; // default sequence breakers for DRY + std::vector<llama_sampler_type> samplers_sequence = { + llama_sampler_type::DRY, llama_sampler_type::TOP_K, llama_sampler_type::TFS_Z, llama_sampler_type::TYPICAL_P, llama_sampler_type::TOP_P, llama_sampler_type::MIN_P, + llama_sampler_type::XTC, llama_sampler_type::TOP_N_SIGMA, llama_sampler_type::TEMPERATURE }; @@ -88,6 +97,8 @@ struct llama_sampling_context { // TODO: replace with ring-buffer std::vector<llama_token> prev; std::vector<llama_token_data> cur; + llama_sampler_dry* smpl; + size_t n_valid; // Number of correct top tokens with correct probabilities. std::mt19937 rng; @@ -96,7 +107,7 @@ struct llama_sampling_context { #include "common.h" // Create a new sampling context instance. -struct llama_sampling_context * llama_sampling_init(const struct llama_sampling_params & params); +struct llama_sampling_context * llama_sampling_init(const struct llama_vocab* vocab, const struct llama_sampling_params & params); void llama_sampling_free(struct llama_sampling_context * ctx); |