sampling.cpp 21.1 KB
Newer Older
1
2
#include "sampling.h"

3
#include "common.h"
4
#include "log.h"
5

6
7
#include <cmath>
#include <unordered_map>
8
#include <algorithm>
9

10
11
12
13
14
// 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) {}
15

16
17
18
    T & front() {
        if (sz == 0) {
            throw std::runtime_error("ring buffer is empty");
19
        }
20
21
        return data[first];
    }
22

23
24
25
    const T & front() const {
        if (sz == 0) {
            throw std::runtime_error("ring buffer is empty");
26
        }
27
28
        return data[first];
    }
29

30
31
32
    T & back() {
        if (sz == 0) {
            throw std::runtime_error("ring buffer is empty");
33
        }
34
        return data[pos];
35
36
    }

37
38
39
40
41
    const T & back() const {
        if (sz == 0) {
            throw std::runtime_error("ring buffer is empty");
        }
        return data[pos];
42
43
    }

44
45
46
47
48
49
50
51
52
    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;
53
54
    }

55
56
57
58
59
60
61
62
63
    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;
    }
64

65
66
67
    const T & rat(size_t i) const {
        if (i >= sz) {
            throw std::runtime_error("ring buffer: index out of bounds");
68
        }
69
        return data[(first + sz - i - 1) % capacity];
70
71
    }

72
73
74
75
76
77
78
79
    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;
    }
80

81
82
83
84
85
    void clear() {
        // here only reset the status of the buffer
        sz = 0;
        first = 0;
        pos = 0;
86
87
    }

88
89
    bool empty() const {
        return sz == 0;
90
91
    }

92
93
    size_t size() const {
        return sz;
94
95
    }

96
97
98
99
100
101
    size_t capacity = 0;
    size_t sz = 0;
    size_t first = 0;
    size_t pos = 0;
    std::vector<T> data;
};
102

103
104
struct common_sampler {
    common_params_sampling params;
105

106
107
    struct llama_sampler * grmr;
    struct llama_sampler * chain;
108

109
    ring_buffer<llama_token> prev;
110

111
    std::vector<llama_token_data> cur;
112

113
    llama_token_data_array cur_p;
114

115
116
    void set_logits(struct llama_context * ctx, int idx) {
        const auto * logits = llama_get_logits_ith(ctx, idx);
117

118
119
120
121
        const llama_model * model = llama_get_model(ctx);
        const llama_vocab * vocab = llama_model_get_vocab(model);

        const int n_vocab = llama_vocab_n_tokens(vocab);
122
123
124
125
126
127
128
129
130
131
132

        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 };
    }
};

133
std::string common_params_sampling::print() const {
134
135
136
137
    char result[1024];

    snprintf(result, sizeof(result),
            "\trepeat_last_n = %d, repeat_penalty = %.3f, frequency_penalty = %.3f, presence_penalty = %.3f\n"
138
            "\tdry_multiplier = %.3f, dry_base = %.3f, dry_allowed_length = %d, dry_penalty_last_n = %d\n"
139
            "\ttop_k = %d, top_p = %.3f, min_p = %.3f, xtc_probability = %.3f, xtc_threshold = %.3f, typical_p = %.3f, top_n_sigma = %.3f, temp = %.3f\n"
140
            "\tmirostat = %d, mirostat_lr = %.3f, mirostat_ent = %.3f",
141
            penalty_last_n, penalty_repeat, penalty_freq, penalty_present,
142
            dry_multiplier, dry_base, dry_allowed_length, dry_penalty_last_n,
143
            top_k, top_p, min_p, xtc_probability, xtc_threshold, typ_p, top_n_sigma, temp,
144
            mirostat, mirostat_eta, mirostat_tau);
145
146
147
148

    return std::string(result);
}

149
struct common_sampler * common_sampler_init(const struct llama_model * model, const struct common_params_sampling & params) {
150
151
    const llama_vocab * vocab = llama_model_get_vocab(model);

152
153
154
155
    llama_sampler_chain_params lparams = llama_sampler_chain_default_params();

    lparams.no_perf = params.no_perf;

156
157
158
159
160
161
162
163
    struct llama_sampler * grmr;
    if (params.grammar.compare(0, 11, "%llguidance") == 0) {
#ifdef LLAMA_USE_LLGUIDANCE
        grmr = llama_sampler_init_llg(vocab, "lark", params.grammar.c_str());
#else
        GGML_ABORT("llguidance (cmake -DLLAMA_LLGUIDANCE=ON) is not enabled");
#endif // LLAMA_USE_LLGUIDANCE
    } else {
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
        std::vector<std::string> patterns_at_start;
        std::vector<std::string> patterns_anywhere;
        std::vector<llama_token> trigger_tokens;
        for (const auto & trigger : params.grammar_triggers) {
            switch (trigger.type) {
                case COMMON_GRAMMAR_TRIGGER_TYPE_WORD:
                {
                    const auto & word = trigger.value;
                    patterns_anywhere.push_back(regex_escape(word));
                    break;
                }
                case COMMON_GRAMMAR_TRIGGER_TYPE_PATTERN:
                case COMMON_GRAMMAR_TRIGGER_TYPE_PATTERN_START:
                {
                    const auto & pattern = trigger.value;
                    (trigger.type == COMMON_GRAMMAR_TRIGGER_TYPE_PATTERN_START ? patterns_at_start : patterns_anywhere).push_back(pattern);
                    break;
                }
                case COMMON_GRAMMAR_TRIGGER_TYPE_TOKEN:
                {
                    const auto token = trigger.token;
                    trigger_tokens.push_back(token);
                    break;
                }
                default:
                    GGML_ASSERT(false && "unknown trigger type");
            }
        }

        std::vector<std::string> trigger_patterns;
        if (!patterns_at_start.empty()) {
            trigger_patterns.push_back("^(" + string_join(patterns_at_start, "|") + ")[\\s\\S]*");
        }
        if (!patterns_anywhere.empty()) {
            trigger_patterns.push_back("^[\\s\\S]*?(" + string_join(patterns_anywhere, "|") + ")[\\s\\S]*");
        }

        std::vector<const char *> trigger_patterns_c;
        trigger_patterns_c.reserve(trigger_patterns.size());
        for (const auto & regex : trigger_patterns) {
            trigger_patterns_c.push_back(regex.c_str());
205
206
207
        }

        grmr = params.grammar_lazy
208
209
210
             ? llama_sampler_init_grammar_lazy_patterns(vocab, params.grammar.c_str(), "root",
                                                        trigger_patterns_c.data(), trigger_patterns_c.size(),
                                                        trigger_tokens.data(), trigger_tokens.size())
211
             :      llama_sampler_init_grammar(vocab, params.grammar.c_str(), "root");
212
213
214
        if (!grmr) {
            return nullptr;
        }
215
216
    }

217
    auto * result = new common_sampler {
218
        /* .params = */ params,
219
        /* .grmr   = */ grmr,
220
221
222
223
224
225
226
227
        /* .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(
228
                llama_vocab_n_tokens(vocab),
229
230
231
                params.logit_bias.size(),
                params.logit_bias.data()));

232
    if (params.mirostat == 0) {
233
234
235
236
237
238
239
240
        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());
241
                        }
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274

                        llama_sampler_chain_add(result->chain, llama_sampler_init_dry      (vocab, llama_model_n_ctx_train(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_TOP_N_SIGMA:
                    llama_sampler_chain_add(result->chain, llama_sampler_init_top_n_sigma (params.top_n_sigma));
                    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      (vocab));
                    break;
                case COMMON_SAMPLER_TYPE_PENALTIES:
                    llama_sampler_chain_add(result->chain, llama_sampler_init_penalties   (params.penalty_last_n, params.penalty_repeat, params.penalty_freq, params.penalty_present));
                    break;
                default:
                    GGML_ASSERT(false && "unknown sampler type");
275
276
            }
        }
277
278
279
        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));
280
        llama_sampler_chain_add(result->chain, llama_sampler_init_mirostat(llama_vocab_n_tokens(vocab), params.seed, params.mirostat_tau, params.mirostat_eta, 100));
281
282
283
    } 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));
284
    } else {
285
        GGML_ASSERT(false && "unknown mirostat version");
286
287
288
289
290
    }

    return result;
}

291
void common_sampler_free(struct common_sampler * gsmpl) {
292
293
294
295
296
297
    if (gsmpl) {
        llama_sampler_free(gsmpl->grmr);

        llama_sampler_free(gsmpl->chain);

        delete gsmpl;
298
299
300
    }
}

301
void common_sampler_accept(struct common_sampler * gsmpl, llama_token token, bool accept_grammar) {
302
303
304
    if (accept_grammar) {
        llama_sampler_accept(gsmpl->grmr, token);
    }
305

306
    llama_sampler_accept(gsmpl->chain, token);
307

308
    gsmpl->prev.push_back(token);
309
310
}

311
void common_sampler_reset(struct common_sampler * gsmpl) {
312
    llama_sampler_reset(gsmpl->grmr);
313

314
    llama_sampler_reset(gsmpl->chain);
315
316
}

317
318
struct common_sampler * common_sampler_clone(common_sampler * gsmpl) {
    return new common_sampler {
319
320
321
322
323
324
325
        /* .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,
    };
326
327
}

328
void common_perf_print(const struct llama_context * ctx, const struct common_sampler * gsmpl) {
329
    // TODO: measure grammar performance
330

331
332
333
334
335
336
337
    if (gsmpl) {
        llama_perf_sampler_print(gsmpl->chain);
    }
    if (ctx) {
        llama_perf_context_print(ctx);
    }
}
338

339
llama_token common_sampler_sample(struct common_sampler * gsmpl, struct llama_context * ctx, int idx, bool grammar_first) {
340
    gsmpl->set_logits(ctx, idx);
341

342
343
344
    auto & grmr  = gsmpl->grmr;
    auto & chain = gsmpl->chain;
    auto & cur_p = gsmpl->cur_p; // initialized by set_logits
345

346
347
    if (grammar_first) {
        llama_sampler_apply(grmr, &cur_p);
348
349
    }

350
    llama_sampler_apply(chain, &cur_p);
351

352
    GGML_ASSERT(cur_p.selected != -1 && "no selected token during sampling - check your sampling configuration");
353

354
    const llama_token id = cur_p.data[cur_p.selected].id;
355

356
357
358
    if (grammar_first) {
        return id;
    }
359

360
361
362
363
    // 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 };
364

365
        llama_sampler_apply(grmr, &single_token_data_array);
366

367
368
369
        const bool is_valid = single_token_data_array.data[0].logit != -INFINITY;
        if (is_valid) {
            return id;
370
371
372
        }
    }

373
374
375
    // 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);
376

377
378
    llama_sampler_apply(grmr,  &cur_p);
    llama_sampler_apply(chain, &cur_p);
379

380
    GGML_ASSERT(cur_p.selected != -1 && "no selected token during re-sampling - check your sampling configuration");
381

382
383
    return cur_p.data[cur_p.selected].id;
}
384

385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
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) {
425
426
427
428
    return llama_sampler_get_seed(gsmpl->chain);
}

// helpers
429

430
llama_token_data_array * common_sampler_get_candidates(struct common_sampler * gsmpl) {
431
432
    return &gsmpl->cur_p;
}
433

434
llama_token common_sampler_last(const struct common_sampler * gsmpl) {
435
436
    return gsmpl->prev.rat(0);
}
437

438
std::string common_sampler_print(const struct common_sampler * gsmpl) {
439
    std::string result = "logits ";
440

441
442
443
    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) + " ";
444
445
    }

446
447
448
    return result;
}

449
std::string common_sampler_prev_str(common_sampler * gsmpl, llama_context * ctx_main, int n) {
450
451
452
453
    n = std::min(n, (int) gsmpl->prev.size());

    if (n <= 0) {
        return "";
454
455
    }

456
457
458
459
460
461
462
463
    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");

464
        result += common_token_to_piece(ctx_main, id);
465
466
    }

467
468
469
    return result;
}

470
char common_sampler_type_to_chr(enum common_sampler_type cnstr) {
471
    switch (cnstr) {
472
473
474
475
        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';
476
        case COMMON_SAMPLER_TYPE_TOP_N_SIGMA: return 's';
477
478
479
480
        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';
481
        case COMMON_SAMPLER_TYPE_PENALTIES:   return 'e';
482
483
484
        default : return '?';
    }
}
485

486
std::string common_sampler_type_to_str(enum common_sampler_type cnstr) {
487
    switch (cnstr) {
488
489
490
491
        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";
492
        case COMMON_SAMPLER_TYPE_TOP_N_SIGMA: return "top_n_sigma";
493
494
495
496
        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";
497
        case COMMON_SAMPLER_TYPE_PENALTIES:   return "penalties";
498
        default : return "";
499
    }
500
}
501

502
503
504
505
506
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 },
507
        { "top_n_sigma", COMMON_SAMPLER_TYPE_TOP_N_SIGMA },
508
509
510
511
512
        { "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 },
513
        { "penalties",   COMMON_SAMPLER_TYPE_PENALTIES },
514
    };
515

516
517
    // since samplers names are written multiple ways
    // make it ready for both system names and input names
518
519
520
    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 },
521
        { "top-n-sigma", COMMON_SAMPLER_TYPE_TOP_N_SIGMA },
522
523
524
525
526
527
528
        { "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 },
529
    };
530

531
    std::vector<common_sampler_type> samplers;
532
    samplers.reserve(names.size());
533

534
535
536
537
    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);
538
539
540
541
542
543
544
            continue;
        }
        if (allow_alt_names) {
            sampler = sampler_alt_name_map.find(name);
            if (sampler != sampler_alt_name_map.end()) {
                samplers.push_back(sampler->second);
                continue;
545
546
            }
        }
547
        LOG_WRN("%s: unable to match sampler by name '%s'\n", __func__, name.c_str());
548
549
    }

550
    return samplers;
551
552
}

553
554
555
556
557
558
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 },
559
        { common_sampler_type_to_chr(COMMON_SAMPLER_TYPE_TOP_N_SIGMA), COMMON_SAMPLER_TYPE_TOP_N_SIGMA },
560
561
562
563
        { 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 },
564
        { common_sampler_type_to_chr(COMMON_SAMPLER_TYPE_PENALTIES),   COMMON_SAMPLER_TYPE_PENALTIES },
565
    };
566

567
    std::vector<common_sampler_type> samplers;
568
    samplers.reserve(chars.size());
569

570
571
572
573
    for (const auto & c : chars) {
        const auto sampler = sampler_name_map.find(c);
        if (sampler != sampler_name_map.end()) {
            samplers.push_back(sampler->second);
574
575
        } else {
            LOG_WRN("%s: unable to match sampler by char '%c'\n", __func__, c);
576
        }
577
    }
578
579

    return samplers;
580
}