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#include "sampling.h"
#include "common.h"
#include <cmath>
#include <unordered_map>
// the ring buffer works similarly to std::deque, but with a fixed capacity
// TODO: deduplicate with llama-impl.h
template<typename T>
struct ring_buffer {
ring_buffer(size_t cap) : capacity(cap), data(cap) {}
T & front() {
if (sz == 0) {
throw std::runtime_error("ring buffer is empty");
}
return data[first];
}
const T & front() const {
if (sz == 0) {
throw std::runtime_error("ring buffer is empty");
}
return data[first];
}
T & back() {
if (sz == 0) {
throw std::runtime_error("ring buffer is empty");
}
return data[pos];
}
const T & back() const {
if (sz == 0) {
throw std::runtime_error("ring buffer is empty");
}
return data[pos];
}
void push_back(const T & value) {
if (sz == capacity) {
// advance the start when buffer is full
first = (first + 1) % capacity;
} else {
sz++;
}
data[pos] = value;
pos = (pos + 1) % capacity;
}
T pop_front() {
if (sz == 0) {
throw std::runtime_error("ring buffer is empty");
}
T value = data[first];
first = (first + 1) % capacity;
sz--;
return value;
}
const T & rat(size_t i) const {
if (i >= sz) {
throw std::runtime_error("ring buffer: index out of bounds");
}
return data[(first + sz - i - 1) % capacity];
}
std::vector<T> to_vector() const {
std::vector<T> result;
result.reserve(sz);
for (size_t i = 0; i < sz; i++) {
result.push_back(data[(first + i) % capacity]);
}
return result;
}
void clear() {
// here only reset the status of the buffer
sz = 0;
first = 0;
pos = 0;
}
bool empty() const {
return sz == 0;
}
size_t size() const {
return sz;
}
size_t capacity = 0;
size_t sz = 0;
size_t first = 0;
size_t pos = 0;
std::vector<T> data;
};
struct common_sampler {
common_params_sampling params;
struct llama_sampler * grmr;
struct llama_sampler * chain;
ring_buffer<llama_token> prev;
std::vector<llama_token_data> cur;
llama_token_data_array cur_p;
void set_logits(struct llama_context * ctx, int idx) {
const auto * logits = llama_get_logits_ith(ctx, idx);
const int n_vocab = llama_n_vocab(llama_get_model(ctx));
cur.resize(n_vocab);
for (llama_token token_id = 0; token_id < n_vocab; token_id++) {
cur[token_id] = llama_token_data{token_id, logits[token_id], 0.0f};
}
cur_p = { cur.data(), cur.size(), -1, false };
}
};
std::string common_params_sampling::print() const {
char result[1024];
snprintf(result, sizeof(result),
"\trepeat_last_n = %d, repeat_penalty = %.3f, frequency_penalty = %.3f, presence_penalty = %.3f\n"
"\tdry_multiplier = %.3f, dry_base = %.3f, dry_allowed_length = %d, dry_penalty_last_n = %d\n"
"\ttop_k = %d, top_p = %.3f, min_p = %.3f, xtc_probability = %.3f, xtc_threshold = %.3f, typical_p = %.3f, temp = %.3f\n"
"\tmirostat = %d, mirostat_lr = %.3f, mirostat_ent = %.3f",
penalty_last_n, penalty_repeat, penalty_freq, penalty_present,
dry_multiplier, dry_base, dry_allowed_length, dry_penalty_last_n,
top_k, top_p, min_p, xtc_probability, xtc_threshold, typ_p, temp,
mirostat, mirostat_eta, mirostat_tau);
return std::string(result);
}
struct common_sampler * common_sampler_init(const struct llama_model * model, const struct common_params_sampling & params) {
llama_sampler_chain_params lparams = llama_sampler_chain_default_params();
lparams.no_perf = params.no_perf;
auto * result = new common_sampler {
/* .params = */ params,
/* .grmr = */ llama_sampler_init_grammar(model, params.grammar.c_str(), "root"),
/* .chain = */ llama_sampler_chain_init(lparams),
/* .prev = */ ring_buffer<llama_token>(std::max(32, params.n_prev)),
/* .cur = */ {},
/* .cur_p = */ {},
};
llama_sampler_chain_add(result->chain,
llama_sampler_init_logit_bias(
llama_n_vocab(model),
params.logit_bias.size(),
params.logit_bias.data()));
llama_sampler_chain_add(result->chain,
llama_sampler_init_penalties(
llama_n_vocab (model),
llama_token_eos(model),
llama_token_nl (model),
params.penalty_last_n,
params.penalty_repeat,
params.penalty_freq,
params.penalty_present,
params.penalize_nl,
params.ignore_eos));
if (params.mirostat == 0) {
for (const auto & cnstr : params.samplers) {
switch (cnstr) {
case COMMON_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());
}
llama_sampler_chain_add(result->chain, llama_sampler_init_dry (model, params.dry_multiplier, params.dry_base, params.dry_allowed_length, params.dry_penalty_last_n, c_breakers.data(), c_breakers.size()));
}
break;
case COMMON_SAMPLER_TYPE_TOP_K:
llama_sampler_chain_add(result->chain, llama_sampler_init_top_k (params.top_k));
break;
case COMMON_SAMPLER_TYPE_TOP_P:
llama_sampler_chain_add(result->chain, llama_sampler_init_top_p (params.top_p, params.min_keep));
break;
case COMMON_SAMPLER_TYPE_MIN_P:
llama_sampler_chain_add(result->chain, llama_sampler_init_min_p (params.min_p, params.min_keep));
break;
case COMMON_SAMPLER_TYPE_XTC:
llama_sampler_chain_add(result->chain, llama_sampler_init_xtc (params.xtc_probability, params.xtc_threshold, params.min_keep, params.seed));
break;
case COMMON_SAMPLER_TYPE_TYPICAL_P:
llama_sampler_chain_add(result->chain, llama_sampler_init_typical (params.typ_p, params.min_keep));
break;
case COMMON_SAMPLER_TYPE_TEMPERATURE:
llama_sampler_chain_add(result->chain, llama_sampler_init_temp_ext (params.temp, params.dynatemp_range, params.dynatemp_exponent));
break;
case COMMON_SAMPLER_TYPE_INFILL:
llama_sampler_chain_add(result->chain, llama_sampler_init_infill (model));
break;
default:
GGML_ASSERT(false && "unknown sampler type");
}
}
llama_sampler_chain_add(result->chain, llama_sampler_init_dist(params.seed));
} else if (params.mirostat == 1) {
llama_sampler_chain_add(result->chain, llama_sampler_init_temp(params.temp));
llama_sampler_chain_add(result->chain, llama_sampler_init_mirostat(llama_n_vocab(model), params.seed, params.mirostat_tau, params.mirostat_eta, 100));
} else if (params.mirostat == 2) {
llama_sampler_chain_add(result->chain, llama_sampler_init_temp(params.temp));
llama_sampler_chain_add(result->chain, llama_sampler_init_mirostat_v2(params.seed, params.mirostat_tau, params.mirostat_eta));
} else {
GGML_ASSERT(false && "unknown mirostat version");
}
return result;
}
void common_sampler_free(struct common_sampler * gsmpl) {
if (gsmpl) {
llama_sampler_free(gsmpl->grmr);
llama_sampler_free(gsmpl->chain);
delete gsmpl;
}
}
void common_sampler_accept(struct common_sampler * gsmpl, llama_token token, bool accept_grammar) {
if (accept_grammar) {
llama_sampler_accept(gsmpl->grmr, token);
}
llama_sampler_accept(gsmpl->chain, token);
gsmpl->prev.push_back(token);
}
void common_sampler_reset(struct common_sampler * gsmpl) {
llama_sampler_reset(gsmpl->grmr);
llama_sampler_reset(gsmpl->chain);
}
struct common_sampler * common_sampler_clone(common_sampler * gsmpl) {
return new common_sampler {
/* .params = */ gsmpl->params,
/* .grmr = */ llama_sampler_clone(gsmpl->grmr),
/* .chain = */ llama_sampler_clone(gsmpl->chain),
/* .prev = */ gsmpl->prev,
/* .cur = */ gsmpl->cur,
/* .cur_p = */ gsmpl->cur_p,
};
}
void common_perf_print(const struct llama_context * ctx, const struct common_sampler * gsmpl) {
// TODO: measure grammar performance
if (gsmpl) {
llama_perf_sampler_print(gsmpl->chain);
}
if (ctx) {
llama_perf_context_print(ctx);
}
}
llama_token common_sampler_sample(struct common_sampler * gsmpl, struct llama_context * ctx, int idx, bool grammar_first) {
gsmpl->set_logits(ctx, idx);
auto & grmr = gsmpl->grmr;
auto & chain = gsmpl->chain;
auto & cur_p = gsmpl->cur_p; // initialized by set_logits
if (grammar_first) {
llama_sampler_apply(grmr, &cur_p);
}
llama_sampler_apply(chain, &cur_p);
GGML_ASSERT(cur_p.selected != -1 && "no selected token during sampling - check your sampling configuration");
const llama_token id = cur_p.data[cur_p.selected].id;
if (grammar_first) {
return id;
}
// check if it the sampled token fits the grammar
{
llama_token_data single_token_data = { id, 1.0f, 0.0f };
llama_token_data_array single_token_data_array = { &single_token_data, 1, -1, false };
llama_sampler_apply(grmr, &single_token_data_array);
const bool is_valid = single_token_data_array.data[0].logit != -INFINITY;
if (is_valid) {
return id;
}
}
// resampling:
// if the token is not valid, sample again, but first apply the grammar sampler and then the sampling chain
gsmpl->set_logits(ctx, idx);
llama_sampler_apply(grmr, &cur_p);
llama_sampler_apply(chain, &cur_p);
GGML_ASSERT(cur_p.selected != -1 && "no selected token during re-sampling - check your sampling configuration");
return cur_p.data[cur_p.selected].id;
}
std::vector<llama_token> common_sampler_sample_and_accept_n(struct common_sampler * gsmpl, struct llama_context * ctx, const std::vector<int> & idxs, const llama_tokens & draft, bool grammar_first) {
GGML_ASSERT(idxs.size() == draft.size() + 1 && "idxs.size() must be draft.size() + 1");
std::vector<llama_token> result;
result.reserve(idxs.size());
size_t i = 0;
for (; i < draft.size(); i++) {
const llama_token id = common_sampler_sample(gsmpl, ctx, idxs[i], grammar_first);
common_sampler_accept(gsmpl, id, true);
result.push_back(id);
if (draft[i] != id) {
break;
}
}
if (i == draft.size()) {
const llama_token id = common_sampler_sample(gsmpl, ctx, idxs[i], grammar_first);
common_sampler_accept(gsmpl, id, true);
result.push_back(id);
}
return result;
}
std::vector<llama_token> common_sampler_sample_and_accept_n(struct common_sampler * gsmpl, struct llama_context * ctx, const llama_tokens & draft, bool grammar_first) {
std::vector<int> idxs(draft.size() + 1);
for (size_t i = 0; i < idxs.size(); ++i) {
idxs[i] = i;
}
return common_sampler_sample_and_accept_n(gsmpl, ctx, idxs, draft, grammar_first);
}
uint32_t common_sampler_get_seed(const struct common_sampler * gsmpl) {
return llama_sampler_get_seed(gsmpl->chain);
}
// helpers
llama_token_data_array * common_sampler_get_candidates(struct common_sampler * gsmpl) {
return &gsmpl->cur_p;
}
llama_token common_sampler_last(const struct common_sampler * gsmpl) {
return gsmpl->prev.rat(0);
}
std::string common_sampler_print(const struct common_sampler * gsmpl) {
std::string result = "logits ";
for (int i = 0; i < llama_sampler_chain_n(gsmpl->chain); i++) {
const auto * smpl = llama_sampler_chain_get(gsmpl->chain, i);
result += std::string("-> ") + llama_sampler_name(smpl) + " ";
}
return result;
}
std::string common_sampler_prev_str(common_sampler * gsmpl, llama_context * ctx_main, int n) {
n = std::min(n, (int) gsmpl->prev.size());
if (n <= 0) {
return "";
}
std::string result;
result.reserve(8*n); // 8 is the average length of a token [citation needed], TODO: compute this from the vocab
for (int i = n - 1; i >= 0; i--) {
const llama_token id = gsmpl->prev.rat(i);
GGML_ASSERT(id != LLAMA_TOKEN_NULL && "null token in the sampling history - should not happen");
result += common_token_to_piece(ctx_main, id);
}
return result;
}
char common_sampler_type_to_chr(enum common_sampler_type cnstr) {
switch (cnstr) {
case COMMON_SAMPLER_TYPE_DRY: return 'd';
case COMMON_SAMPLER_TYPE_TOP_K: return 'k';
case COMMON_SAMPLER_TYPE_TYPICAL_P: return 'y';
case COMMON_SAMPLER_TYPE_TOP_P: return 'p';
case COMMON_SAMPLER_TYPE_MIN_P: return 'm';
case COMMON_SAMPLER_TYPE_TEMPERATURE: return 't';
case COMMON_SAMPLER_TYPE_XTC: return 'x';
case COMMON_SAMPLER_TYPE_INFILL: return 'i';
default : return '?';
}
}
std::string common_sampler_type_to_str(enum common_sampler_type cnstr) {
switch (cnstr) {
case COMMON_SAMPLER_TYPE_DRY: return "dry";
case COMMON_SAMPLER_TYPE_TOP_K: return "top_k";
case COMMON_SAMPLER_TYPE_TYPICAL_P: return "typ_p";
case COMMON_SAMPLER_TYPE_TOP_P: return "top_p";
case COMMON_SAMPLER_TYPE_MIN_P: return "min_p";
case COMMON_SAMPLER_TYPE_TEMPERATURE: return "temperature";
case COMMON_SAMPLER_TYPE_XTC: return "xtc";
case COMMON_SAMPLER_TYPE_INFILL: return "infill";
default : return "";
}
}
std::vector<common_sampler_type> common_sampler_types_from_names(const std::vector<std::string> & names, bool allow_alt_names) {
std::unordered_map<std::string, common_sampler_type> sampler_canonical_name_map {
{ "dry", COMMON_SAMPLER_TYPE_DRY },
{ "top_k", COMMON_SAMPLER_TYPE_TOP_K },
{ "top_p", COMMON_SAMPLER_TYPE_TOP_P },
{ "typ_p", COMMON_SAMPLER_TYPE_TYPICAL_P },
{ "min_p", COMMON_SAMPLER_TYPE_MIN_P },
{ "temperature", COMMON_SAMPLER_TYPE_TEMPERATURE },
{ "xtc", COMMON_SAMPLER_TYPE_XTC },
{ "infill", COMMON_SAMPLER_TYPE_INFILL },
};
// since samplers names are written multiple ways
// make it ready for both system names and input names
std::unordered_map<std::string, common_sampler_type> sampler_alt_name_map {
{ "top-k", COMMON_SAMPLER_TYPE_TOP_K },
{ "top-p", COMMON_SAMPLER_TYPE_TOP_P },
{ "nucleus", COMMON_SAMPLER_TYPE_TOP_P },
{ "typical-p", COMMON_SAMPLER_TYPE_TYPICAL_P },
{ "typical", COMMON_SAMPLER_TYPE_TYPICAL_P },
{ "typ-p", COMMON_SAMPLER_TYPE_TYPICAL_P },
{ "typ", COMMON_SAMPLER_TYPE_TYPICAL_P },
{ "min-p", COMMON_SAMPLER_TYPE_MIN_P },
{ "temp", COMMON_SAMPLER_TYPE_TEMPERATURE },
};
std::vector<common_sampler_type> samplers;
samplers.reserve(names.size());
for (const auto & name : names) {
auto sampler = sampler_canonical_name_map.find(name);
if (sampler != sampler_canonical_name_map.end()) {
samplers.push_back(sampler->second);
} else {
if (allow_alt_names) {
sampler = sampler_alt_name_map.find(name);
if (sampler != sampler_alt_name_map.end()) {
samplers.push_back(sampler->second);
}
}
}
}
return samplers;
}
std::vector<common_sampler_type> common_sampler_types_from_chars(const std::string & chars) {
std::unordered_map<char, common_sampler_type> sampler_name_map = {
{ common_sampler_type_to_chr(COMMON_SAMPLER_TYPE_DRY), COMMON_SAMPLER_TYPE_DRY },
{ common_sampler_type_to_chr(COMMON_SAMPLER_TYPE_TOP_K), COMMON_SAMPLER_TYPE_TOP_K },
{ common_sampler_type_to_chr(COMMON_SAMPLER_TYPE_TYPICAL_P), COMMON_SAMPLER_TYPE_TYPICAL_P },
{ common_sampler_type_to_chr(COMMON_SAMPLER_TYPE_TOP_P), COMMON_SAMPLER_TYPE_TOP_P },
{ common_sampler_type_to_chr(COMMON_SAMPLER_TYPE_MIN_P), COMMON_SAMPLER_TYPE_MIN_P },
{ common_sampler_type_to_chr(COMMON_SAMPLER_TYPE_TEMPERATURE), COMMON_SAMPLER_TYPE_TEMPERATURE },
{ common_sampler_type_to_chr(COMMON_SAMPLER_TYPE_XTC), COMMON_SAMPLER_TYPE_XTC },
{ common_sampler_type_to_chr(COMMON_SAMPLER_TYPE_INFILL), COMMON_SAMPLER_TYPE_INFILL },
};
std::vector<common_sampler_type> samplers;
samplers.reserve(chars.size());
for (const auto & c : chars) {
const auto sampler = sampler_name_map.find(c);
if (sampler != sampler_name_map.end()) {
samplers.push_back(sampler->second);
}
}
return samplers;
}
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