sampling.cpp 19 KB

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  1. /**
  2. * llama.cpp - commit 46e3556e01b824e52395fb050b29804b6cff2a7c - do not edit this file
  3. *
  4. * MIT License
  5. *
  6. * Copyright (c) 2023-2024 The ggml authors
  7. *
  8. * Permission is hereby granted, free of charge, to any person obtaining a copy
  9. * of this software and associated documentation files (the "Software"), to deal
  10. * in the Software without restriction, including without limitation the rights
  11. * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
  12. * copies of the Software, and to permit persons to whom the Software is
  13. * furnished to do so, subject to the following conditions:
  14. *
  15. * The above copyright notice and this permission notice shall be included in all
  16. * copies or substantial portions of the Software.
  17. *
  18. * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
  19. * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
  20. * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
  21. * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
  22. * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
  23. * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  24. * SOFTWARE.
  25. */
  26. #include "sampling.h"
  27. #include "common.h"
  28. #include <cmath>
  29. #include <unordered_map>
  30. // the ring buffer works similarly to std::deque, but with a fixed capacity
  31. // TODO: deduplicate with llama-impl.h
  32. template<typename T>
  33. struct ring_buffer {
  34. ring_buffer(size_t cap) : capacity(cap), data(cap) {}
  35. T & front() {
  36. if (sz == 0) {
  37. throw std::runtime_error("ring buffer is empty");
  38. }
  39. return data[first];
  40. }
  41. const T & front() const {
  42. if (sz == 0) {
  43. throw std::runtime_error("ring buffer is empty");
  44. }
  45. return data[first];
  46. }
  47. T & back() {
  48. if (sz == 0) {
  49. throw std::runtime_error("ring buffer is empty");
  50. }
  51. return data[pos];
  52. }
  53. const T & back() const {
  54. if (sz == 0) {
  55. throw std::runtime_error("ring buffer is empty");
  56. }
  57. return data[pos];
  58. }
  59. void push_back(const T & value) {
  60. if (sz == capacity) {
  61. // advance the start when buffer is full
  62. first = (first + 1) % capacity;
  63. } else {
  64. sz++;
  65. }
  66. data[pos] = value;
  67. pos = (pos + 1) % capacity;
  68. }
  69. T pop_front() {
  70. if (sz == 0) {
  71. throw std::runtime_error("ring buffer is empty");
  72. }
  73. T value = data[first];
  74. first = (first + 1) % capacity;
  75. sz--;
  76. return value;
  77. }
  78. const T & rat(size_t i) const {
  79. if (i >= sz) {
  80. throw std::runtime_error("ring buffer: index out of bounds");
  81. }
  82. return data[(first + sz - i - 1) % capacity];
  83. }
  84. std::vector<T> to_vector() const {
  85. std::vector<T> result;
  86. result.reserve(sz);
  87. for (size_t i = 0; i < sz; i++) {
  88. result.push_back(data[(first + i) % capacity]);
  89. }
  90. return result;
  91. }
  92. void clear() {
  93. // here only reset the status of the buffer
  94. sz = 0;
  95. first = 0;
  96. pos = 0;
  97. }
  98. bool empty() const {
  99. return sz == 0;
  100. }
  101. size_t size() const {
  102. return sz;
  103. }
  104. size_t capacity = 0;
  105. size_t sz = 0;
  106. size_t first = 0;
  107. size_t pos = 0;
  108. std::vector<T> data;
  109. };
  110. struct common_sampler {
  111. common_params_sampling params;
  112. struct llama_sampler * grmr;
  113. struct llama_sampler * chain;
  114. ring_buffer<llama_token> prev;
  115. std::vector<llama_token_data> cur;
  116. llama_token_data_array cur_p;
  117. void set_logits(struct llama_context * ctx, int idx) {
  118. const auto * logits = llama_get_logits_ith(ctx, idx);
  119. const int n_vocab = llama_n_vocab(llama_get_model(ctx));
  120. cur.resize(n_vocab);
  121. for (llama_token token_id = 0; token_id < n_vocab; token_id++) {
  122. cur[token_id] = llama_token_data{token_id, logits[token_id], 0.0f};
  123. }
  124. cur_p = { cur.data(), cur.size(), -1, false };
  125. }
  126. };
  127. std::string common_params_sampling::print() const {
  128. char result[1024];
  129. snprintf(result, sizeof(result),
  130. "\trepeat_last_n = %d, repeat_penalty = %.3f, frequency_penalty = %.3f, presence_penalty = %.3f\n"
  131. "\tdry_multiplier = %.3f, dry_base = %.3f, dry_allowed_length = %d, dry_penalty_last_n = %d\n"
  132. "\ttop_k = %d, top_p = %.3f, min_p = %.3f, xtc_probability = %.3f, xtc_threshold = %.3f, typical_p = %.3f, temp = %.3f\n"
  133. "\tmirostat = %d, mirostat_lr = %.3f, mirostat_ent = %.3f",
  134. penalty_last_n, penalty_repeat, penalty_freq, penalty_present,
  135. dry_multiplier, dry_base, dry_allowed_length, dry_penalty_last_n,
  136. top_k, top_p, min_p, xtc_probability, xtc_threshold, typ_p, temp,
  137. mirostat, mirostat_eta, mirostat_tau);
  138. return std::string(result);
  139. }
  140. struct common_sampler * common_sampler_init(const struct llama_model * model, const struct common_params_sampling & params) {
  141. llama_sampler_chain_params lparams = llama_sampler_chain_default_params();
  142. lparams.no_perf = params.no_perf;
  143. auto * result = new common_sampler {
  144. /* .params = */ params,
  145. /* .grmr = */ llama_sampler_init_grammar(model, params.grammar.c_str(), "root"),
  146. /* .chain = */ llama_sampler_chain_init(lparams),
  147. /* .prev = */ ring_buffer<llama_token>(std::max(32, params.n_prev)),
  148. /* .cur = */ {},
  149. /* .cur_p = */ {},
  150. };
  151. llama_sampler_chain_add(result->chain,
  152. llama_sampler_init_logit_bias(
  153. llama_n_vocab(model),
  154. params.logit_bias.size(),
  155. params.logit_bias.data()));
  156. if (params.mirostat == 0) {
  157. for (const auto & cnstr : params.samplers) {
  158. switch (cnstr) {
  159. case COMMON_SAMPLER_TYPE_DRY:
  160. {
  161. std::vector<const char *> c_breakers;
  162. c_breakers.reserve(params.dry_sequence_breakers.size());
  163. for (const auto & str : params.dry_sequence_breakers) {
  164. c_breakers.push_back(str.c_str());
  165. }
  166. 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()));
  167. }
  168. break;
  169. case COMMON_SAMPLER_TYPE_TOP_K:
  170. llama_sampler_chain_add(result->chain, llama_sampler_init_top_k (params.top_k));
  171. break;
  172. case COMMON_SAMPLER_TYPE_TOP_P:
  173. llama_sampler_chain_add(result->chain, llama_sampler_init_top_p (params.top_p, params.min_keep));
  174. break;
  175. case COMMON_SAMPLER_TYPE_MIN_P:
  176. llama_sampler_chain_add(result->chain, llama_sampler_init_min_p (params.min_p, params.min_keep));
  177. break;
  178. case COMMON_SAMPLER_TYPE_XTC:
  179. llama_sampler_chain_add(result->chain, llama_sampler_init_xtc (params.xtc_probability, params.xtc_threshold, params.min_keep, params.seed));
  180. break;
  181. case COMMON_SAMPLER_TYPE_TYPICAL_P:
  182. llama_sampler_chain_add(result->chain, llama_sampler_init_typical (params.typ_p, params.min_keep));
  183. break;
  184. case COMMON_SAMPLER_TYPE_TEMPERATURE:
  185. llama_sampler_chain_add(result->chain, llama_sampler_init_temp_ext (params.temp, params.dynatemp_range, params.dynatemp_exponent));
  186. break;
  187. case COMMON_SAMPLER_TYPE_INFILL:
  188. llama_sampler_chain_add(result->chain, llama_sampler_init_infill (model));
  189. break;
  190. case COMMON_SAMPLER_TYPE_PENALTIES:
  191. llama_sampler_chain_add(result->chain, llama_sampler_init_penalties(params.penalty_last_n, params.penalty_repeat, params.penalty_freq, params.penalty_present));
  192. break;
  193. default:
  194. GGML_ASSERT(false && "unknown sampler type");
  195. }
  196. }
  197. llama_sampler_chain_add(result->chain, llama_sampler_init_dist(params.seed));
  198. } else if (params.mirostat == 1) {
  199. llama_sampler_chain_add(result->chain, llama_sampler_init_temp(params.temp));
  200. llama_sampler_chain_add(result->chain, llama_sampler_init_mirostat(llama_n_vocab(model), params.seed, params.mirostat_tau, params.mirostat_eta, 100));
  201. } else if (params.mirostat == 2) {
  202. llama_sampler_chain_add(result->chain, llama_sampler_init_temp(params.temp));
  203. llama_sampler_chain_add(result->chain, llama_sampler_init_mirostat_v2(params.seed, params.mirostat_tau, params.mirostat_eta));
  204. } else {
  205. GGML_ASSERT(false && "unknown mirostat version");
  206. }
  207. return result;
  208. }
  209. void common_sampler_free(struct common_sampler * gsmpl) {
  210. if (gsmpl) {
  211. llama_sampler_free(gsmpl->grmr);
  212. llama_sampler_free(gsmpl->chain);
  213. delete gsmpl;
  214. }
  215. }
  216. void common_sampler_accept(struct common_sampler * gsmpl, llama_token token, bool accept_grammar) {
  217. if (accept_grammar) {
  218. llama_sampler_accept(gsmpl->grmr, token);
  219. }
  220. llama_sampler_accept(gsmpl->chain, token);
  221. gsmpl->prev.push_back(token);
  222. }
  223. void common_sampler_reset(struct common_sampler * gsmpl) {
  224. llama_sampler_reset(gsmpl->grmr);
  225. llama_sampler_reset(gsmpl->chain);
  226. }
  227. struct common_sampler * common_sampler_clone(common_sampler * gsmpl) {
  228. return new common_sampler {
  229. /* .params = */ gsmpl->params,
  230. /* .grmr = */ llama_sampler_clone(gsmpl->grmr),
  231. /* .chain = */ llama_sampler_clone(gsmpl->chain),
  232. /* .prev = */ gsmpl->prev,
  233. /* .cur = */ gsmpl->cur,
  234. /* .cur_p = */ gsmpl->cur_p,
  235. };
  236. }
  237. void common_perf_print(const struct llama_context * ctx, const struct common_sampler * gsmpl) {
  238. // TODO: measure grammar performance
  239. if (gsmpl) {
  240. llama_perf_sampler_print(gsmpl->chain);
  241. }
  242. if (ctx) {
  243. llama_perf_context_print(ctx);
  244. }
  245. }
  246. llama_token common_sampler_sample(struct common_sampler * gsmpl, struct llama_context * ctx, int idx, bool grammar_first) {
  247. gsmpl->set_logits(ctx, idx);
  248. auto & grmr = gsmpl->grmr;
  249. auto & chain = gsmpl->chain;
  250. auto & cur_p = gsmpl->cur_p; // initialized by set_logits
  251. if (grammar_first) {
  252. llama_sampler_apply(grmr, &cur_p);
  253. }
  254. llama_sampler_apply(chain, &cur_p);
  255. GGML_ASSERT(cur_p.selected != -1 && "no selected token during sampling - check your sampling configuration");
  256. const llama_token id = cur_p.data[cur_p.selected].id;
  257. if (grammar_first) {
  258. return id;
  259. }
  260. // check if it the sampled token fits the grammar
  261. {
  262. llama_token_data single_token_data = { id, 1.0f, 0.0f };
  263. llama_token_data_array single_token_data_array = { &single_token_data, 1, -1, false };
  264. llama_sampler_apply(grmr, &single_token_data_array);
  265. const bool is_valid = single_token_data_array.data[0].logit != -INFINITY;
  266. if (is_valid) {
  267. return id;
  268. }
  269. }
  270. // resampling:
  271. // if the token is not valid, sample again, but first apply the grammar sampler and then the sampling chain
  272. gsmpl->set_logits(ctx, idx);
  273. llama_sampler_apply(grmr, &cur_p);
  274. llama_sampler_apply(chain, &cur_p);
  275. GGML_ASSERT(cur_p.selected != -1 && "no selected token during re-sampling - check your sampling configuration");
  276. return cur_p.data[cur_p.selected].id;
  277. }
  278. 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) {
  279. GGML_ASSERT(idxs.size() == draft.size() + 1 && "idxs.size() must be draft.size() + 1");
  280. std::vector<llama_token> result;
  281. result.reserve(idxs.size());
  282. size_t i = 0;
  283. for (; i < draft.size(); i++) {
  284. const llama_token id = common_sampler_sample(gsmpl, ctx, idxs[i], grammar_first);
  285. common_sampler_accept(gsmpl, id, true);
  286. result.push_back(id);
  287. if (draft[i] != id) {
  288. break;
  289. }
  290. }
  291. if (i == draft.size()) {
  292. const llama_token id = common_sampler_sample(gsmpl, ctx, idxs[i], grammar_first);
  293. common_sampler_accept(gsmpl, id, true);
  294. result.push_back(id);
  295. }
  296. return result;
  297. }
  298. 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) {
  299. std::vector<int> idxs(draft.size() + 1);
  300. for (size_t i = 0; i < idxs.size(); ++i) {
  301. idxs[i] = i;
  302. }
  303. return common_sampler_sample_and_accept_n(gsmpl, ctx, idxs, draft, grammar_first);
  304. }
  305. uint32_t common_sampler_get_seed(const struct common_sampler * gsmpl) {
  306. return llama_sampler_get_seed(gsmpl->chain);
  307. }
  308. // helpers
  309. llama_token_data_array * common_sampler_get_candidates(struct common_sampler * gsmpl) {
  310. return &gsmpl->cur_p;
  311. }
  312. llama_token common_sampler_last(const struct common_sampler * gsmpl) {
  313. return gsmpl->prev.rat(0);
  314. }
  315. std::string common_sampler_print(const struct common_sampler * gsmpl) {
  316. std::string result = "logits ";
  317. for (int i = 0; i < llama_sampler_chain_n(gsmpl->chain); i++) {
  318. const auto * smpl = llama_sampler_chain_get(gsmpl->chain, i);
  319. result += std::string("-> ") + llama_sampler_name(smpl) + " ";
  320. }
  321. return result;
  322. }
  323. std::string common_sampler_prev_str(common_sampler * gsmpl, llama_context * ctx_main, int n) {
  324. n = std::min(n, (int) gsmpl->prev.size());
  325. if (n <= 0) {
  326. return "";
  327. }
  328. std::string result;
  329. result.reserve(8*n); // 8 is the average length of a token [citation needed], TODO: compute this from the vocab
  330. for (int i = n - 1; i >= 0; i--) {
  331. const llama_token id = gsmpl->prev.rat(i);
  332. GGML_ASSERT(id != LLAMA_TOKEN_NULL && "null token in the sampling history - should not happen");
  333. result += common_token_to_piece(ctx_main, id);
  334. }
  335. return result;
  336. }
  337. char common_sampler_type_to_chr(enum common_sampler_type cnstr) {
  338. switch (cnstr) {
  339. case COMMON_SAMPLER_TYPE_DRY: return 'd';
  340. case COMMON_SAMPLER_TYPE_TOP_K: return 'k';
  341. case COMMON_SAMPLER_TYPE_TYPICAL_P: return 'y';
  342. case COMMON_SAMPLER_TYPE_TOP_P: return 'p';
  343. case COMMON_SAMPLER_TYPE_MIN_P: return 'm';
  344. case COMMON_SAMPLER_TYPE_TEMPERATURE: return 't';
  345. case COMMON_SAMPLER_TYPE_XTC: return 'x';
  346. case COMMON_SAMPLER_TYPE_INFILL: return 'i';
  347. case COMMON_SAMPLER_TYPE_PENALTIES: return 'e';
  348. default : return '?';
  349. }
  350. }
  351. std::string common_sampler_type_to_str(enum common_sampler_type cnstr) {
  352. switch (cnstr) {
  353. case COMMON_SAMPLER_TYPE_DRY: return "dry";
  354. case COMMON_SAMPLER_TYPE_TOP_K: return "top_k";
  355. case COMMON_SAMPLER_TYPE_TYPICAL_P: return "typ_p";
  356. case COMMON_SAMPLER_TYPE_TOP_P: return "top_p";
  357. case COMMON_SAMPLER_TYPE_MIN_P: return "min_p";
  358. case COMMON_SAMPLER_TYPE_TEMPERATURE: return "temperature";
  359. case COMMON_SAMPLER_TYPE_XTC: return "xtc";
  360. case COMMON_SAMPLER_TYPE_INFILL: return "infill";
  361. case COMMON_SAMPLER_TYPE_PENALTIES: return "penalties";
  362. default : return "";
  363. }
  364. }
  365. std::vector<common_sampler_type> common_sampler_types_from_names(const std::vector<std::string> & names, bool allow_alt_names) {
  366. std::unordered_map<std::string, common_sampler_type> sampler_canonical_name_map {
  367. { "dry", COMMON_SAMPLER_TYPE_DRY },
  368. { "top_k", COMMON_SAMPLER_TYPE_TOP_K },
  369. { "top_p", COMMON_SAMPLER_TYPE_TOP_P },
  370. { "typ_p", COMMON_SAMPLER_TYPE_TYPICAL_P },
  371. { "min_p", COMMON_SAMPLER_TYPE_MIN_P },
  372. { "temperature", COMMON_SAMPLER_TYPE_TEMPERATURE },
  373. { "xtc", COMMON_SAMPLER_TYPE_XTC },
  374. { "infill", COMMON_SAMPLER_TYPE_INFILL },
  375. { "penalties", COMMON_SAMPLER_TYPE_PENALTIES },
  376. };
  377. // since samplers names are written multiple ways
  378. // make it ready for both system names and input names
  379. std::unordered_map<std::string, common_sampler_type> sampler_alt_name_map {
  380. { "top-k", COMMON_SAMPLER_TYPE_TOP_K },
  381. { "top-p", COMMON_SAMPLER_TYPE_TOP_P },
  382. { "nucleus", COMMON_SAMPLER_TYPE_TOP_P },
  383. { "typical-p", COMMON_SAMPLER_TYPE_TYPICAL_P },
  384. { "typical", COMMON_SAMPLER_TYPE_TYPICAL_P },
  385. { "typ-p", COMMON_SAMPLER_TYPE_TYPICAL_P },
  386. { "typ", COMMON_SAMPLER_TYPE_TYPICAL_P },
  387. { "min-p", COMMON_SAMPLER_TYPE_MIN_P },
  388. { "temp", COMMON_SAMPLER_TYPE_TEMPERATURE },
  389. };
  390. std::vector<common_sampler_type> samplers;
  391. samplers.reserve(names.size());
  392. for (const auto & name : names) {
  393. auto sampler = sampler_canonical_name_map.find(name);
  394. if (sampler != sampler_canonical_name_map.end()) {
  395. samplers.push_back(sampler->second);
  396. } else {
  397. if (allow_alt_names) {
  398. sampler = sampler_alt_name_map.find(name);
  399. if (sampler != sampler_alt_name_map.end()) {
  400. samplers.push_back(sampler->second);
  401. }
  402. }
  403. }
  404. }
  405. return samplers;
  406. }
  407. std::vector<common_sampler_type> common_sampler_types_from_chars(const std::string & chars) {
  408. std::unordered_map<char, common_sampler_type> sampler_name_map = {
  409. { common_sampler_type_to_chr(COMMON_SAMPLER_TYPE_DRY), COMMON_SAMPLER_TYPE_DRY },
  410. { common_sampler_type_to_chr(COMMON_SAMPLER_TYPE_TOP_K), COMMON_SAMPLER_TYPE_TOP_K },
  411. { common_sampler_type_to_chr(COMMON_SAMPLER_TYPE_TYPICAL_P), COMMON_SAMPLER_TYPE_TYPICAL_P },
  412. { common_sampler_type_to_chr(COMMON_SAMPLER_TYPE_TOP_P), COMMON_SAMPLER_TYPE_TOP_P },
  413. { common_sampler_type_to_chr(COMMON_SAMPLER_TYPE_MIN_P), COMMON_SAMPLER_TYPE_MIN_P },
  414. { common_sampler_type_to_chr(COMMON_SAMPLER_TYPE_TEMPERATURE), COMMON_SAMPLER_TYPE_TEMPERATURE },
  415. { common_sampler_type_to_chr(COMMON_SAMPLER_TYPE_XTC), COMMON_SAMPLER_TYPE_XTC },
  416. { common_sampler_type_to_chr(COMMON_SAMPLER_TYPE_INFILL), COMMON_SAMPLER_TYPE_INFILL },
  417. { common_sampler_type_to_chr(COMMON_SAMPLER_TYPE_PENALTIES), COMMON_SAMPLER_TYPE_PENALTIES },
  418. };
  419. std::vector<common_sampler_type> samplers;
  420. samplers.reserve(chars.size());
  421. for (const auto & c : chars) {
  422. const auto sampler = sampler_name_map.find(c);
  423. if (sampler != sampler_name_map.end()) {
  424. samplers.push_back(sampler->second);
  425. }
  426. }
  427. return samplers;
  428. }