/src/llama.cpp/src/llama-batch.cpp
Line | Count | Source |
1 | | #include "llama-batch.h" |
2 | | |
3 | | #include "llama-impl.h" |
4 | | #include "llama-vocab.h" |
5 | | #include "llama-memory.h" |
6 | | |
7 | | #include <cassert> |
8 | | #include <cstring> |
9 | | #include <algorithm> |
10 | | #include <sstream> |
11 | | |
12 | 0 | llama_batch_allocr::llama_batch_allocr(uint32_t n_pos_per_embd) : n_pos_per_embd(n_pos_per_embd) { |
13 | 0 | const char * LLAMA_BATCH_DEBUG = getenv("LLAMA_BATCH_DEBUG"); |
14 | 0 | debug = LLAMA_BATCH_DEBUG ? atoi(LLAMA_BATCH_DEBUG) : 0; |
15 | |
|
16 | 0 | seq_pos.resize(LLAMA_MAX_SEQ); |
17 | 0 | seq_cpl.resize(LLAMA_MAX_SEQ); |
18 | 0 | for (auto & cur : seq_cpl) { |
19 | 0 | cur.resize(LLAMA_MAX_SEQ); |
20 | 0 | } |
21 | |
|
22 | 0 | seq_idx.resize(LLAMA_MAX_SEQ, -1); |
23 | 0 | } |
24 | | |
25 | | bool llama_batch_allocr::init( |
26 | | const llama_batch & batch_inp, |
27 | | const llama_vocab & vocab, |
28 | | const llama_memory_i * memory, |
29 | | uint32_t n_embd, |
30 | | uint32_t n_seq_max, |
31 | 0 | bool output_all) { |
32 | 0 | clear(); |
33 | |
|
34 | 0 | batch = batch_inp; |
35 | |
|
36 | 0 | this->vocab = &vocab; |
37 | |
|
38 | 0 | GGML_ASSERT(batch.n_tokens > 0); |
39 | | |
40 | | // |
41 | | // validate input batch |
42 | | // |
43 | |
|
44 | 0 | if (n_seq_max > LLAMA_MAX_SEQ) { |
45 | 0 | LLAMA_LOG_ERROR("%s: n_seq_max = %d > %d\n", __func__, n_seq_max, LLAMA_MAX_SEQ); |
46 | 0 | return false; |
47 | 0 | } |
48 | | |
49 | 0 | if (batch.token) { |
50 | 0 | for (int32_t i = 0; i < batch.n_tokens; ++i) { |
51 | 0 | if (batch.token[i] < 0 || (uint32_t) batch.token[i] >= vocab.n_tokens()) { |
52 | 0 | LLAMA_LOG_ERROR("%s: invalid token[%d] = %d\n", __func__, i, batch.token[i]); |
53 | 0 | return false; |
54 | 0 | } |
55 | 0 | } |
56 | 0 | } |
57 | | |
58 | 0 | if (batch.seq_id) { |
59 | 0 | for (int32_t i = 0; i < batch.n_tokens; ++i) { |
60 | 0 | for (int32_t s = 0; s < batch.n_seq_id[i]; ++s) { |
61 | 0 | if (batch.seq_id && (batch.seq_id[i][s] < 0 || batch.seq_id[i][s] >= (llama_seq_id) n_seq_max)) { |
62 | 0 | LLAMA_LOG_ERROR("%s: invalid seq_id[%d][%d] = %d >= %d\n", __func__, i, s, batch.seq_id[i][s], (llama_seq_id) n_seq_max); |
63 | 0 | return false; |
64 | 0 | } |
65 | 0 | } |
66 | 0 | } |
67 | 0 | } |
68 | | |
69 | | // |
70 | | // auto-generate missing fields |
71 | | // |
72 | | |
73 | 0 | if (!batch.n_seq_id) { |
74 | 0 | n_seq_id.resize(batch.n_tokens); |
75 | 0 | for (int32_t i = 0; i < batch.n_tokens; i++) { |
76 | 0 | n_seq_id[i] = seq_id_0.size(); |
77 | 0 | } |
78 | 0 | batch.n_seq_id = n_seq_id.data(); |
79 | 0 | } |
80 | |
|
81 | 0 | if (!batch.seq_id) { |
82 | 0 | seq_id.resize(batch.n_tokens + 1); |
83 | 0 | seq_id[batch.n_tokens] = NULL; |
84 | 0 | for (int32_t i = 0; i < batch.n_tokens; i++) { |
85 | 0 | seq_id[i] = seq_id_0.data(); |
86 | 0 | } |
87 | 0 | batch.seq_id = seq_id.data(); |
88 | 0 | } |
89 | |
|
90 | 0 | if (!batch.pos) { |
91 | 0 | pos.resize(batch.n_tokens); |
92 | | |
93 | | // initialize the starting position for each sequence based on the positions in the memory |
94 | 0 | llama_pos p0[LLAMA_MAX_SEQ]; |
95 | 0 | for (uint32_t s = 0; s < n_seq_max; ++s) { |
96 | 0 | if (!memory) { |
97 | | // if no memory -> start from 0 |
98 | 0 | p0[s] = 0; |
99 | 0 | } else { |
100 | 0 | p0[s] = memory->seq_pos_max(s) + 1; |
101 | 0 | } |
102 | 0 | } |
103 | |
|
104 | 0 | for (int32_t i = 0; i < batch.n_tokens; i++) { |
105 | 0 | const llama_seq_id seq_id = batch.seq_id[i][0]; |
106 | |
|
107 | 0 | pos[i] = p0[seq_id]; |
108 | | |
109 | | // update the starting position for all sequences that are assigned to the this token |
110 | 0 | for (int32_t s = 0; s < batch.n_seq_id[i]; ++s) { |
111 | 0 | const llama_seq_id seq_id = batch.seq_id[i][s]; |
112 | |
|
113 | 0 | p0[seq_id] = pos[i] + 1; |
114 | 0 | } |
115 | 0 | } |
116 | |
|
117 | 0 | batch.pos = pos.data(); |
118 | 0 | } |
119 | |
|
120 | 0 | if (!batch.logits) { |
121 | 0 | if (output_all) { |
122 | | // return the output for all tokens |
123 | 0 | output.resize(batch.n_tokens, true); |
124 | 0 | } else { |
125 | | // return the output only for the last token |
126 | 0 | output.resize(batch.n_tokens, false); |
127 | 0 | output[output.size() - 1] = true; |
128 | 0 | } |
129 | |
|
130 | 0 | batch.logits = output.data(); |
131 | 0 | } else if (output_all) { |
132 | 0 | bool warn = false; |
133 | |
|
134 | 0 | for (int32_t i = 0; i < batch.n_tokens; ++i) { |
135 | 0 | if (batch.logits[i] == 0) { |
136 | 0 | warn = true; |
137 | 0 | } |
138 | 0 | } |
139 | |
|
140 | 0 | if (warn) { |
141 | 0 | LLAMA_LOG_WARN("%s: embeddings required but some input tokens were not marked as outputs -> overriding\n", __func__); |
142 | |
|
143 | 0 | output.resize(batch.n_tokens, true); |
144 | 0 | batch.logits = output.data(); |
145 | 0 | } |
146 | 0 | } |
147 | | |
148 | | // |
149 | | // compute stats |
150 | | // |
151 | |
|
152 | 0 | this->n_embd = n_embd; |
153 | 0 | this->n_seq_max = n_seq_max; |
154 | | |
155 | | // count the outputs in this batch |
156 | 0 | for (int32_t i = 0; i < batch.n_tokens; ++i) { |
157 | 0 | n_outputs += batch.logits[i] != 0; |
158 | 0 | } |
159 | |
|
160 | 0 | has_cpl = false; |
161 | | |
162 | | // determine coupled sequences |
163 | | // these are pairs of sequences that have at least one token in the input batch that is assigned to both of them |
164 | 0 | for (int32_t i = 0; i < batch.n_tokens; ++i) { |
165 | 0 | const llama_seq_id s0 = batch.seq_id[i][0]; |
166 | |
|
167 | 0 | for (int32_t s = 0; s < batch.n_seq_id[i]; ++s) { |
168 | 0 | const llama_seq_id s1 = batch.seq_id[i][s]; |
169 | |
|
170 | 0 | seq_pos[s1].insert(batch.pos[i]); |
171 | |
|
172 | 0 | if (s > 0) { |
173 | | // mark that sequence s1 is coupled to s0 |
174 | 0 | seq_cpl[s1][s0] = true; |
175 | | |
176 | | // note: tracking the other way around is not necessary for now |
177 | | //seq_cpl[s0][s1] = true; |
178 | |
|
179 | 0 | has_cpl = true; |
180 | 0 | } |
181 | 0 | } |
182 | 0 | } |
183 | | |
184 | | // precompute the sequence sets for each token and determine the unique sequence ids that participate in the batch |
185 | 0 | { |
186 | 0 | seq_set_t seq_set_unq; |
187 | |
|
188 | 0 | for (int32_t i = 0; i < batch.n_tokens; ++i) { |
189 | 0 | seq_set_t cur; |
190 | 0 | for (int32_t s = 0; s < batch.n_seq_id[i]; ++s) { |
191 | 0 | const llama_seq_id seq_id = batch.seq_id[i][s]; |
192 | |
|
193 | 0 | cur .set(seq_id); |
194 | 0 | seq_set_unq.set(seq_id); |
195 | 0 | } |
196 | |
|
197 | 0 | seq_set.push_back(cur); |
198 | 0 | seq_set_map[cur].push_back(i); |
199 | 0 | } |
200 | |
|
201 | 0 | for (uint32_t s = 0; s < n_seq_max; ++s) { |
202 | 0 | if (seq_set_unq.test(s)) { |
203 | 0 | seq_idx[s] = seq_id_unq.size(); |
204 | 0 | seq_id_unq.push_back(s); |
205 | 0 | } |
206 | 0 | } |
207 | 0 | } |
208 | |
|
209 | 0 | if (debug > 0) { |
210 | 0 | LLAMA_LOG_DEBUG("%s: input batch info:\n", __func__); |
211 | |
|
212 | 0 | llama_ubatch ubatch { |
213 | 0 | /*.b_equal_seqs =*/ false, |
214 | 0 | /*.n_tokens =*/ (uint32_t) batch.n_tokens, |
215 | 0 | /*.n_seq_tokens =*/ (uint32_t) 1, |
216 | 0 | /*.n_seqs =*/ (uint32_t) batch.n_tokens, |
217 | 0 | /*.n_seqs_unq =*/ (uint32_t) this->seq_id_unq.size(), |
218 | 0 | /*.n_pos =*/ n_pos_per_embd, |
219 | 0 | /*.token =*/ batch.token, |
220 | 0 | /*.embd =*/ batch.embd, |
221 | 0 | /*.pos =*/ batch.pos, |
222 | 0 | /*.n_seq_id =*/ batch.n_seq_id, |
223 | 0 | /*.seq_id =*/ batch.seq_id, |
224 | 0 | /*.seq_id_unq =*/ this->seq_id_unq.data(), |
225 | 0 | /*.seq_idx =*/ this->seq_idx.data(), |
226 | 0 | /*.output =*/ batch.logits, |
227 | 0 | /*.data =*/ {}, |
228 | 0 | }; |
229 | |
|
230 | 0 | ubatch_print(ubatch, debug); |
231 | |
|
232 | 0 | LLAMA_LOG_DEBUG("%s: seq = [\n", __func__); |
233 | 0 | for (int s0 = 0; s0 < (int) seq_pos.size(); ++s0) { |
234 | 0 | if (seq_pos[s0].empty()) { |
235 | 0 | continue; |
236 | 0 | } |
237 | | |
238 | 0 | std::stringstream ss; |
239 | 0 | for (int s1 = 0; s1 < (int) seq_cpl[s0].size(); ++s1) { |
240 | 0 | if (seq_cpl[s0][s1]) { |
241 | 0 | ss << s1 << " "; |
242 | 0 | } |
243 | 0 | } |
244 | |
|
245 | 0 | LLAMA_LOG_DEBUG("%s: %4d: pos = [%4d, %4d], cpl = %s\n", |
246 | 0 | __func__, s0, seq_pos_min(s0), seq_pos_max(s0), ss.str().empty() ? "-" : ss.str().c_str()); |
247 | 0 | } |
248 | 0 | LLAMA_LOG_DEBUG("%s: ]\n", __func__); |
249 | 0 | } |
250 | | |
251 | | // |
252 | | // consistency checks |
253 | | // |
254 | |
|
255 | 0 | if (n_pos_per_embd > 1) { |
256 | | // M-RoPE case: allow position to "jump" forward only (non-continuous positions are allowed) |
257 | 0 | for (uint32_t s = 0; s < n_seq_max; ++s) { |
258 | 0 | if (seq_pos[s].empty()) { |
259 | 0 | continue; |
260 | 0 | } |
261 | | |
262 | 0 | const llama_pos p0 = memory ? memory->seq_pos_max(s) : -1; |
263 | |
|
264 | 0 | if (batch.token) { |
265 | 0 | if (p0 >= 0 && p0 >= seq_pos_min(s)) { |
266 | 0 | LLAMA_LOG_ERROR( |
267 | 0 | "%s: the tokens of sequence %d in the input batch have inconsistent sequence positions:\n" |
268 | 0 | " - the last position stored in the memory module of the context (i.e. the KV cache) for sequence %d is X = %d\n" |
269 | 0 | " - the tokens for sequence %d in the input batch have a starting position of Y = %d\n" |
270 | 0 | " for M-RoPE, it is required that the position satisfies: X < Y\n", |
271 | 0 | __func__, s, s, p0, s, seq_pos_min(s)); |
272 | |
|
273 | 0 | return false; |
274 | 0 | } |
275 | 0 | } else { |
276 | | // embedding inputs can have overlapping positions |
277 | 0 | if (p0 >= 0 && p0 > seq_pos_min(s)) { |
278 | 0 | LLAMA_LOG_ERROR( |
279 | 0 | "%s: the tokens of sequence %d in the input batch have inconsistent sequence positions:\n" |
280 | 0 | " - the last position stored in the memory module of the context (i.e. the KV cache) for sequence %d is X = %d\n" |
281 | 0 | " - the tokens for sequence %d in the input batch have a starting position of Y = %d\n" |
282 | 0 | " for M-RoPE, it is required that the position satisfies: X <= Y\n", |
283 | 0 | __func__, s, s, p0, s, seq_pos_min(s)); |
284 | |
|
285 | 0 | return false; |
286 | 0 | } |
287 | 0 | } |
288 | 0 | } |
289 | 0 | } else { |
290 | 0 | for (uint32_t s = 0; s < n_seq_max; ++s) { |
291 | 0 | if (seq_pos[s].empty()) { |
292 | 0 | continue; |
293 | 0 | } |
294 | | |
295 | 0 | const llama_pos p0 = memory ? memory->seq_pos_max(s) : -1; |
296 | |
|
297 | 0 | if (p0 >= 0) { |
298 | 0 | bool ok = true; |
299 | |
|
300 | 0 | if (seq_pos_min(s) != p0 + 1) { |
301 | 0 | ok = false; |
302 | 0 | } |
303 | |
|
304 | 0 | if (!ok) { |
305 | 0 | LLAMA_LOG_ERROR( |
306 | 0 | "%s: the tokens of sequence %d in the input batch have inconsistent sequence positions:\n" |
307 | 0 | " - the last position stored in the memory module of the context (i.e. the KV cache) for sequence %d is X = %d\n" |
308 | 0 | " - the tokens for sequence %d in the input batch have a starting position of Y = %d\n" |
309 | 0 | " it is required that the sequence positions remain consecutive: Y = X + 1\n", |
310 | 0 | __func__, s, s, p0, s, seq_pos_min(s)); |
311 | |
|
312 | 0 | return false; |
313 | 0 | } |
314 | 0 | } |
315 | | |
316 | 0 | if (seq_pos_max(s) - seq_pos_min(s) + 1 > (int) seq_pos[s].size()) { |
317 | 0 | LLAMA_LOG_ERROR("%s: sequence %d positions are not continuous\n", __func__, s); |
318 | 0 | return false; |
319 | 0 | } |
320 | 0 | } |
321 | 0 | } |
322 | | |
323 | 0 | if (memory) { |
324 | 0 | for (uint32_t s0 = 0; s0 < n_seq_max; ++s0) { |
325 | 0 | for (uint32_t s1 = 0; s1 < n_seq_max; ++s1) { |
326 | 0 | if (seq_cpl[s0][s1]) { |
327 | 0 | if (memory->seq_pos_min(s0) != memory->seq_pos_min(s1) || |
328 | 0 | memory->seq_pos_max(s0) != memory->seq_pos_max(s1)) { |
329 | 0 | LLAMA_LOG_ERROR("%s: sequence %d is coupled to %d in the input batch, but have divereged\n", __func__, s0, s1); |
330 | 0 | return false; |
331 | 0 | } |
332 | 0 | } |
333 | 0 | } |
334 | 0 | } |
335 | 0 | } |
336 | | |
337 | | // disallow partial sequence sub-sets: |
338 | | // |
339 | | // invalid: x |
340 | | // i: 0 1 2 ... |
341 | | // --------------------------------------- |
342 | | // seq_id[i][0]: 0 0 1 |
343 | | // seq_id[i][1]: 1 1 2 |
344 | | // seq_id[i][2]: 2 |
345 | | // |
346 | | // disallow decreasing sequence positions: |
347 | | // |
348 | | // invalid: x |
349 | | // i: 0 1 2 3 4 5 6 ... |
350 | | // --------------------------------------- |
351 | | // pos[i]: 4 5 0 1 6 2 3 |
352 | | // seq_id[i][0]: 0 0 1 1 0 1 0 |
353 | | // |
354 | 0 | { |
355 | 0 | seq_set_t cur_seq_set[LLAMA_MAX_SEQ]; |
356 | 0 | for (uint32_t s = 0; s < n_seq_max; ++s) { |
357 | 0 | cur_seq_set[s].set(); |
358 | 0 | } |
359 | |
|
360 | 0 | llama_pos cur_seq_pos[LLAMA_MAX_SEQ]; |
361 | 0 | for (uint32_t s = 0; s < n_seq_max; ++s) { |
362 | 0 | cur_seq_pos[s] = -1; |
363 | 0 | } |
364 | |
|
365 | 0 | for (int32_t i = 0; i < batch.n_tokens; ++i) { |
366 | 0 | const llama_pos pos = batch.pos[i]; |
367 | |
|
368 | 0 | for (int32_t s = 0; s < batch.n_seq_id[i]; ++s) { |
369 | 0 | const llama_seq_id seq_id = batch.seq_id[i][s]; |
370 | |
|
371 | 0 | cur_seq_set[seq_id] &= seq_set[i]; |
372 | |
|
373 | 0 | if (cur_seq_set[seq_id].none()) { |
374 | 0 | LLAMA_LOG_ERROR("%s: sequence %d belongs to incompatible sequence sets (not allowed)\n", __func__, seq_id); |
375 | 0 | return false; |
376 | 0 | } |
377 | | |
378 | 0 | if (pos < cur_seq_pos[seq_id]) { |
379 | 0 | LLAMA_LOG_ERROR("%s: sequence %d positions are decreasing (not allowed)\n", __func__, seq_id); |
380 | 0 | return false; |
381 | 0 | } |
382 | 0 | } |
383 | 0 | } |
384 | 0 | } |
385 | | |
386 | 0 | split_reset(); |
387 | |
|
388 | 0 | return true; |
389 | 0 | } |
390 | | |
391 | 0 | llama_ubatch llama_batch_allocr::ubatch_reserve(uint32_t n_seq_tokens, uint32_t n_seqs) { |
392 | 0 | const uint32_t n_tokens = n_seq_tokens*n_seqs; |
393 | |
|
394 | 0 | clear(); |
395 | 0 | split_reset(); |
396 | |
|
397 | 0 | auto udata = std::make_shared<llama_ubatch::data_t>(); |
398 | |
|
399 | 0 | udata->token .resize(n_tokens); |
400 | 0 | udata->embd .clear(); |
401 | 0 | udata->pos .resize(n_tokens); |
402 | 0 | udata->n_seq_id .resize(n_tokens); |
403 | 0 | udata->seq_id .resize(n_tokens); |
404 | 0 | udata->seq_id_unq.resize(0); |
405 | 0 | udata->seq_idx .resize(LLAMA_MAX_SEQ, -1); |
406 | 0 | udata->output .resize(n_tokens); |
407 | |
|
408 | 0 | for (uint32_t s = 0; s < n_seqs; ++s) { |
409 | 0 | udata->seq_idx[s] = s; |
410 | 0 | udata->seq_id_unq.push_back(s); |
411 | 0 | } |
412 | |
|
413 | 0 | llama_ubatch res { |
414 | 0 | /*.b_equal_seqs =*/ true, |
415 | 0 | /*.n_tokens =*/ n_tokens, |
416 | 0 | /*.n_seq_tokens =*/ n_seq_tokens, |
417 | 0 | /*.n_seqs =*/ n_seqs, |
418 | 0 | /*.n_seqs_unq =*/ n_seqs, |
419 | 0 | /*.n_pos =*/ n_pos_per_embd, |
420 | | |
421 | | /*.token =*/ udata->token.data(), |
422 | 0 | /*.embd =*/ nullptr, |
423 | 0 | /*.pos =*/ udata->pos.data(), |
424 | 0 | /*.n_seq_id =*/ udata->n_seq_id.data(), |
425 | 0 | /*.seq_id =*/ udata->seq_id.data(), |
426 | 0 | /*.seq_id_unq =*/ udata->seq_id_unq.data(), |
427 | 0 | /*.seq_idx =*/ udata->seq_idx.data(), |
428 | 0 | /*.output =*/ udata->output.data(), |
429 | 0 | /*.data =*/ std::move(udata), |
430 | 0 | }; |
431 | |
|
432 | 0 | return res; |
433 | 0 | } |
434 | | |
435 | 0 | const llama_batch & llama_batch_allocr::get_batch() const { |
436 | 0 | return batch; |
437 | 0 | } |
438 | | |
439 | 0 | uint32_t llama_batch_allocr::get_n_tokens() const { |
440 | 0 | return batch.n_tokens; |
441 | 0 | } |
442 | | |
443 | 0 | uint32_t llama_batch_allocr::get_n_outputs() const { |
444 | 0 | return n_outputs; |
445 | 0 | } |
446 | | |
447 | 0 | uint32_t llama_batch_allocr::get_n_used() const { |
448 | 0 | return n_used; |
449 | 0 | } |
450 | | |
451 | 0 | std::vector<int32_t> & llama_batch_allocr::get_out_ids() { |
452 | 0 | return out_ids; |
453 | 0 | } |
454 | | |
455 | 0 | llama_pos llama_batch_allocr::seq_pos_min(llama_seq_id seq_id) const { |
456 | 0 | return seq_pos[seq_id].empty() ? -1 : *seq_pos[seq_id].begin(); |
457 | 0 | } |
458 | | |
459 | 0 | llama_pos llama_batch_allocr::seq_pos_max(llama_seq_id seq_id) const { |
460 | 0 | return seq_pos[seq_id].empty() ? -1 : *seq_pos[seq_id].rbegin(); |
461 | 0 | } |
462 | | |
463 | 0 | void llama_batch_allocr::split_reset() { |
464 | 0 | out_ids.clear(); |
465 | |
|
466 | 0 | n_used = 0; |
467 | |
|
468 | 0 | used.clear(); |
469 | 0 | used.resize(get_n_tokens(), false); |
470 | 0 | } |
471 | | |
472 | 0 | llama_ubatch llama_batch_allocr::split_simple(uint32_t n_ubatch) { |
473 | | // find the first unused token |
474 | 0 | uint32_t cur_idx = 0; |
475 | 0 | while (cur_idx < used.size() && used[cur_idx]) { |
476 | 0 | ++cur_idx; |
477 | 0 | } |
478 | | |
479 | | // we are done |
480 | 0 | if (cur_idx >= used.size()) { |
481 | 0 | return {}; |
482 | 0 | } |
483 | | |
484 | 0 | std::vector<int32_t> idxs; |
485 | |
|
486 | 0 | while (true) { |
487 | 0 | idxs.push_back(cur_idx); |
488 | |
|
489 | 0 | used[cur_idx] = true; |
490 | 0 | ++n_used; |
491 | |
|
492 | 0 | ++cur_idx; |
493 | |
|
494 | 0 | if (cur_idx >= used.size()) { |
495 | 0 | break; |
496 | 0 | } |
497 | | |
498 | 0 | if (idxs.size() >= n_ubatch) { |
499 | 0 | break; |
500 | 0 | } |
501 | 0 | } |
502 | |
|
503 | 0 | return ubatch_add(idxs, idxs.size(), false); |
504 | 0 | } |
505 | | |
506 | 0 | llama_ubatch llama_batch_allocr::split_equal(uint32_t n_ubatch, bool sequential) { |
507 | 0 | if (sequential && has_cpl) { |
508 | 0 | LLAMA_LOG_ERROR("%s: sequential split is not supported when there are coupled sequences in the input batch (you may need to use the -kvu flag)\n", __func__); |
509 | |
|
510 | 0 | return {}; |
511 | 0 | } |
512 | | |
513 | 0 | std::vector<seq_set_t> cur_seq_set; |
514 | |
|
515 | 0 | llama_seq_id last_seq_id = -1; |
516 | | |
517 | | // determine the non-overlapping sequence sets participating in this ubatch |
518 | 0 | for (int32_t i = 0; i < batch.n_tokens; ++i) { |
519 | 0 | if (used[i]) { |
520 | 0 | continue; |
521 | 0 | } |
522 | | |
523 | 0 | bool add = true; |
524 | |
|
525 | 0 | for (uint32_t s = 0; s < cur_seq_set.size(); ++s) { |
526 | | // no overlap with existing sequence sets: |
527 | 0 | if (!(cur_seq_set[s] & seq_set[i]).none()) { |
528 | 0 | add = false; |
529 | 0 | break; |
530 | 0 | } |
531 | 0 | } |
532 | | |
533 | | // accept only increasing sequence ids |
534 | 0 | if (sequential) { |
535 | 0 | add = add && (cur_seq_set.empty() || batch.seq_id[i][0] == last_seq_id + 1); |
536 | 0 | } |
537 | |
|
538 | 0 | if (add) { |
539 | 0 | cur_seq_set.push_back(seq_set[i]); |
540 | |
|
541 | 0 | last_seq_id = batch.seq_id[i][0]; |
542 | |
|
543 | 0 | if (cur_seq_set.size() > n_ubatch) { |
544 | 0 | break; |
545 | 0 | } |
546 | 0 | } |
547 | 0 | } |
548 | |
|
549 | 0 | const uint32_t n_seqs = cur_seq_set.size(); |
550 | | |
551 | | // we are done |
552 | 0 | if (n_seqs == 0) { |
553 | 0 | return {}; |
554 | 0 | } |
555 | | |
556 | | // the current batch index of each sequence set |
557 | 0 | std::vector<int32_t> cur_idx(n_seqs, 0); |
558 | |
|
559 | 0 | for (uint32_t s = 0; s < n_seqs; ++s) { |
560 | 0 | while (used[seq_set_map[cur_seq_set[s]][cur_idx[s]]]) { |
561 | 0 | ++cur_idx[s]; |
562 | 0 | } |
563 | 0 | } |
564 | | |
565 | | // the list of batch indices for each sequence set |
566 | | // at the end we will concat these to get the final ubatch |
567 | 0 | std::vector<idx_vec_t> idxs_per_seq(n_seqs); |
568 | |
|
569 | 0 | while (true) { |
570 | | // we can only add new n_seq_tokens tokens if all the sequence sets have at least one more unused token and |
571 | | // if we haven't reached n_ubatch |
572 | 0 | bool can_expand = true; |
573 | |
|
574 | 0 | for (uint32_t s = 0; s < n_seqs; ++s) { |
575 | 0 | if (cur_idx[s] >= (int32_t) seq_set_map[cur_seq_set[s]].size()) { |
576 | 0 | can_expand = false; |
577 | 0 | break; |
578 | 0 | } |
579 | 0 | } |
580 | |
|
581 | 0 | if (!can_expand) { |
582 | 0 | break; |
583 | 0 | } |
584 | | |
585 | 0 | for (uint32_t s = 0; s < n_seqs; ++s) { |
586 | 0 | const int32_t idx = seq_set_map[cur_seq_set[s]][cur_idx[s]]; |
587 | |
|
588 | 0 | idxs_per_seq[s].push_back(idx); |
589 | |
|
590 | 0 | used[idx] = true; |
591 | 0 | ++n_used; |
592 | |
|
593 | 0 | ++cur_idx[s]; |
594 | 0 | } |
595 | |
|
596 | 0 | if ((idxs_per_seq[0].size() + 1)*n_seqs > n_ubatch) { |
597 | 0 | break; |
598 | 0 | } |
599 | 0 | } |
600 | | |
601 | | // concat the per-sequence-set lists |
602 | 0 | std::vector<int32_t> idxs; |
603 | |
|
604 | 0 | for (uint32_t s = 0; s < n_seqs; ++s) { |
605 | 0 | idxs.insert(idxs.end(), idxs_per_seq[s].begin(), idxs_per_seq[s].end()); |
606 | 0 | } |
607 | |
|
608 | 0 | return ubatch_add(idxs, n_seqs, true); |
609 | 0 | } |
610 | | |
611 | 0 | llama_ubatch llama_batch_allocr::split_seq(uint32_t n_ubatch) { |
612 | | // find the first unused token |
613 | 0 | uint32_t cur_idx = 0; |
614 | 0 | while (cur_idx < used.size() && used[cur_idx]) { |
615 | 0 | ++cur_idx; |
616 | 0 | } |
617 | | |
618 | | // we are done |
619 | 0 | if (cur_idx >= used.size()) { |
620 | 0 | return {}; |
621 | 0 | } |
622 | | |
623 | | // this is the starting sequence set |
624 | | // we allow adding tokens only if their sequence set is a subset of the current sequence set |
625 | 0 | auto cur_seq_set = seq_set[cur_idx]; |
626 | |
|
627 | 0 | std::vector<int32_t> idxs; |
628 | |
|
629 | 0 | while (true) { |
630 | 0 | idxs.push_back(cur_idx); |
631 | |
|
632 | 0 | used[cur_idx] = true; |
633 | 0 | ++n_used; |
634 | |
|
635 | 0 | if (idxs.size() >= n_ubatch) { |
636 | 0 | break; |
637 | 0 | } |
638 | | |
639 | 0 | do { |
640 | 0 | ++cur_idx; |
641 | 0 | } while (cur_idx < get_n_tokens() && (used[cur_idx] || ((cur_seq_set & seq_set[cur_idx]) != seq_set[cur_idx]))); |
642 | |
|
643 | 0 | if (cur_idx == get_n_tokens()) { |
644 | 0 | break; |
645 | 0 | } |
646 | | |
647 | 0 | cur_seq_set = seq_set[cur_idx]; |
648 | 0 | } |
649 | |
|
650 | 0 | return ubatch_add(idxs, 1, true); |
651 | 0 | } |
652 | | |
653 | 0 | void llama_batch_allocr::clear() { |
654 | 0 | n_outputs = 0; |
655 | |
|
656 | 0 | batch = {}; |
657 | |
|
658 | 0 | pos .clear(); |
659 | 0 | n_seq_id .clear(); |
660 | 0 | seq_id .clear(); |
661 | 0 | seq_id_unq.clear(); |
662 | 0 | output .clear(); |
663 | |
|
664 | 0 | for (auto & cur : seq_pos) { |
665 | 0 | cur.clear(); |
666 | 0 | } |
667 | |
|
668 | 0 | for (auto & cur : seq_cpl) { |
669 | 0 | std::fill(cur.begin(), cur.end(), false); |
670 | 0 | } |
671 | |
|
672 | 0 | seq_set.clear(); |
673 | |
|
674 | 0 | seq_set_map.clear(); |
675 | |
|
676 | 0 | std::fill(seq_idx.begin(), seq_idx.end(), -1); |
677 | 0 | } |
678 | | |
679 | 0 | llama_ubatch llama_batch_allocr::ubatch_add(const std::vector<int32_t> & idxs, uint32_t n_seqs, bool equal_seqs) { |
680 | 0 | const uint32_t n_tokens = idxs.size(); |
681 | |
|
682 | 0 | assert(n_tokens%n_seqs == 0); |
683 | |
|
684 | 0 | auto udata = std::make_shared<llama_ubatch::data_t>(); |
685 | |
|
686 | 0 | const int64_t n_embd_all = batch.embd ? (int64_t) n_tokens*n_embd : 0; |
687 | 0 | const int64_t n_pos_all = (int64_t) n_tokens*n_pos_per_embd; |
688 | |
|
689 | 0 | udata->token .resize(n_tokens); |
690 | 0 | udata->embd .resize(n_embd_all); |
691 | 0 | udata->pos .resize(n_pos_all); |
692 | 0 | udata->n_seq_id .resize(n_tokens); |
693 | 0 | udata->seq_id .resize(n_tokens); |
694 | 0 | udata->seq_id_unq.resize(0); |
695 | 0 | udata->seq_idx .resize(LLAMA_MAX_SEQ, -1); |
696 | 0 | udata->output .resize(n_tokens); |
697 | |
|
698 | 0 | udata->seq_id_data.reserve(n_tokens); |
699 | |
|
700 | 0 | seq_set_t seq_set_unq; |
701 | |
|
702 | 0 | for (size_t i = 0; i < idxs.size(); ++i) { |
703 | 0 | if (batch.token) { |
704 | 0 | udata->token[i] = batch.token[idxs[i]]; |
705 | 0 | } |
706 | |
|
707 | 0 | if (batch.embd) { |
708 | 0 | memcpy(udata->embd.data() + i*n_embd, batch.embd + (int64_t) idxs[i]*n_embd, n_embd*sizeof(float)); |
709 | 0 | } |
710 | |
|
711 | 0 | for (size_t j = 0; j < (size_t)n_pos_per_embd; ++j) { |
712 | | // if we are using M-RoPE |
713 | | // if the current batch is text, we need to broadcast the same position across all RoPE sections |
714 | | // otherwise, the input batch is image embeddings, we copy the positions as-is |
715 | | // if we are not using M-RoPE, there is only one position per token (this loop runs only once) |
716 | 0 | size_t src_off = batch.token ? 0 : j*batch.n_tokens; |
717 | 0 | udata->pos[j*n_tokens + i] = batch.pos[src_off + idxs[i]]; |
718 | 0 | } |
719 | |
|
720 | 0 | udata->n_seq_id[i] = batch.n_seq_id[idxs[i]]; |
721 | 0 | udata->output[i] = batch.logits[idxs[i]]; |
722 | |
|
723 | 0 | for (int s = 0; s < udata->n_seq_id[i]; ++s) { |
724 | 0 | const llama_seq_id seq_id = batch.seq_id[idxs[i]][s]; |
725 | |
|
726 | 0 | udata->seq_id_data.push_back(seq_id); |
727 | 0 | seq_set_unq.set(seq_id); |
728 | 0 | } |
729 | |
|
730 | 0 | if (udata->output[i]) { |
731 | 0 | out_ids.push_back(idxs[i]); |
732 | 0 | } |
733 | 0 | } |
734 | |
|
735 | 0 | llama_seq_id * seq_id_ptr = udata->seq_id_data.data(); |
736 | 0 | for (size_t i = 0; i < idxs.size(); ++i) { |
737 | 0 | udata->seq_id[i] = seq_id_ptr; |
738 | 0 | seq_id_ptr += udata->n_seq_id[i]; |
739 | 0 | } |
740 | |
|
741 | 0 | for (uint32_t s = 0; s < n_seq_max; ++s) { |
742 | 0 | if (seq_set_unq.test(s)) { |
743 | 0 | udata->seq_idx[s] = udata->seq_id_unq.size(); |
744 | 0 | udata->seq_id_unq.push_back(s); |
745 | 0 | } |
746 | 0 | } |
747 | |
|
748 | 0 | llama_ubatch res { |
749 | 0 | /*.b_equal_seqs =*/ equal_seqs, |
750 | 0 | /*.n_tokens =*/ n_tokens, |
751 | 0 | /*.n_seq_tokens =*/ n_tokens/n_seqs, |
752 | 0 | /*.n_seqs =*/ n_seqs, |
753 | 0 | /*.n_seqs_unq =*/ (uint32_t) udata->seq_id_unq.size(), |
754 | 0 | /*.n_pos =*/ n_pos_per_embd, |
755 | | |
756 | 0 | /*.token =*/ batch.token ? udata->token.data() : nullptr, |
757 | 0 | /*.embd =*/ batch.embd ? udata->embd.data() : nullptr, |
758 | 0 | /*.pos =*/ udata->pos.data(), |
759 | 0 | /*.n_seq_id =*/ udata->n_seq_id.data(), |
760 | 0 | /*.seq_id =*/ udata->seq_id.data(), |
761 | 0 | /*.seq_id_unq =*/ udata->seq_id_unq.data(), |
762 | 0 | /*.seq_idx =*/ udata->seq_idx.data(), |
763 | 0 | /*.output =*/ udata->output.data(), |
764 | 0 | /*.data =*/ std::move(udata), |
765 | 0 | }; |
766 | |
|
767 | 0 | if (debug > 0) { |
768 | 0 | LLAMA_LOG_DEBUG("%s: added ubatch to split:\n", __func__); |
769 | |
|
770 | 0 | ubatch_print(res, debug); |
771 | 0 | } |
772 | |
|
773 | 0 | return res; |
774 | 0 | } |
775 | | |
776 | 0 | void llama_batch_allocr::ubatch_print(const llama_ubatch & ubatch, int debug) { |
777 | 0 | if (debug > 0) { |
778 | 0 | LLAMA_LOG_DEBUG("%s: equal_seqs = %d\n", __func__, ubatch.equal_seqs()); |
779 | 0 | LLAMA_LOG_DEBUG("%s: n_tokens = %d\n", __func__, ubatch.n_tokens); |
780 | 0 | LLAMA_LOG_DEBUG("%s: n_seq_tokens = %d\n", __func__, ubatch.n_seq_tokens); |
781 | 0 | LLAMA_LOG_DEBUG("%s: n_seqs = %d\n", __func__, ubatch.n_seqs); |
782 | 0 | LLAMA_LOG_DEBUG("%s: n_seqs_unq = %d\n", __func__, ubatch.n_seqs_unq); |
783 | |
|
784 | 0 | std::stringstream ss_seq_id_unq; |
785 | 0 | std::stringstream ss_seq_idx; |
786 | |
|
787 | 0 | ss_seq_id_unq << "[ "; |
788 | 0 | ss_seq_idx << "["; |
789 | |
|
790 | 0 | for (uint32_t s = 0; s < ubatch.n_seqs_unq; ++s) { |
791 | 0 | ss_seq_id_unq << ubatch.seq_id_unq[s] << " "; |
792 | 0 | } |
793 | |
|
794 | 0 | for (uint32_t s = 0; s < LLAMA_MAX_SEQ; ++s) { |
795 | 0 | if (ubatch.seq_idx[s] >= 0) { |
796 | 0 | ss_seq_idx << ubatch.seq_idx[s]%10; |
797 | 0 | } else { |
798 | 0 | ss_seq_idx << "."; |
799 | 0 | } |
800 | 0 | } |
801 | |
|
802 | 0 | ss_seq_id_unq << "]"; |
803 | 0 | ss_seq_idx << "]"; |
804 | |
|
805 | 0 | LLAMA_LOG_DEBUG("%s: token = %p\n", __func__, (void *) ubatch.token); |
806 | 0 | LLAMA_LOG_DEBUG("%s: embd = %p\n", __func__, (void *) ubatch.embd); |
807 | 0 | LLAMA_LOG_DEBUG("%s: pos = %p\n", __func__, (void *) ubatch.pos); |
808 | 0 | LLAMA_LOG_DEBUG("%s: n_seq_id = %p\n", __func__, (void *) ubatch.n_seq_id); |
809 | 0 | LLAMA_LOG_DEBUG("%s: seq_id = %p\n", __func__, (void *) ubatch.seq_id); |
810 | 0 | LLAMA_LOG_DEBUG("%s: seq_id_unq = %s\n", __func__, ss_seq_id_unq.str().c_str()); |
811 | 0 | LLAMA_LOG_DEBUG("%s: seq_idx = %s\n", __func__, ss_seq_idx.str().c_str()); |
812 | 0 | LLAMA_LOG_DEBUG("%s: output = %p\n", __func__, (void *) ubatch.output); |
813 | 0 | LLAMA_LOG_DEBUG("%s: n_outputs = %d\n", __func__, n_outputs); |
814 | |
|
815 | 0 | if (debug > 1) { |
816 | 0 | int seq_id_max = 0; |
817 | 0 | for (uint32_t i = 0; i < ubatch.n_tokens; ++i) { |
818 | 0 | for (int s = 0; s < ubatch.n_seq_id[i]; ++s) { |
819 | 0 | for (int s = 0; s < ubatch.n_seq_id[i]; ++s) { |
820 | 0 | seq_id_max = std::max(seq_id_max, ubatch.seq_id[i][s]); |
821 | 0 | } |
822 | 0 | } |
823 | 0 | } |
824 | 0 | ++seq_id_max; |
825 | |
|
826 | 0 | LLAMA_LOG_DEBUG("%s: token = [\n", __func__); |
827 | 0 | for (uint32_t i = 0; i < ubatch.n_tokens; ++i) { |
828 | 0 | std::vector<int8_t> seq_id(seq_id_max); |
829 | |
|
830 | 0 | for (int s = 0; s < ubatch.n_seq_id[i]; ++s) { |
831 | 0 | seq_id[ubatch.seq_id[i][s]] = 1; |
832 | 0 | } |
833 | |
|
834 | 0 | std::stringstream ss; |
835 | 0 | for (int s = 0; s < seq_id_max; ++s) { |
836 | 0 | if (seq_id[s]) { |
837 | 0 | ss << s%10; |
838 | 0 | } else { |
839 | 0 | ss << "."; |
840 | 0 | } |
841 | 0 | } |
842 | |
|
843 | 0 | if (ubatch.token) { |
844 | 0 | LLAMA_LOG_DEBUG("%s: %4d: id = %6d (%16s), pos = %4d, n_seq_id = %2d, seq_id = [%s], output = %d\n", |
845 | 0 | __func__, i, ubatch.token[i], vocab->token_to_piece(ubatch.token[i]).c_str(), |
846 | 0 | ubatch.pos[i], ubatch.n_seq_id[i], ss.str().c_str(), ubatch.output[i]); |
847 | 0 | } else { |
848 | 0 | LLAMA_LOG_DEBUG("%s: %4d: [embd], pos = %4d, n_seq_id = %2d, seq_id = [%s], output = %d\n", |
849 | 0 | __func__, i, ubatch.pos[i], ubatch.n_seq_id[i], ss.str().c_str(), ubatch.output[i]); |
850 | 0 | } |
851 | 0 | } |
852 | 0 | LLAMA_LOG_DEBUG("%s: ]\n", __func__); |
853 | 0 | } |
854 | 0 | } |
855 | 0 | } |
856 | | |
857 | | // |
858 | | // interface implementation |
859 | | // |
860 | | |
861 | | struct llama_batch llama_batch_get_one( |
862 | | llama_token * tokens, |
863 | 0 | int32_t n_tokens) { |
864 | 0 | return { |
865 | 0 | /*n_tokens =*/ n_tokens, |
866 | 0 | /*tokens =*/ tokens, |
867 | 0 | /*embd =*/ nullptr, |
868 | 0 | /*pos =*/ nullptr, |
869 | 0 | /*n_seq_id =*/ nullptr, |
870 | 0 | /*seq_id =*/ nullptr, |
871 | 0 | /*logits =*/ nullptr, |
872 | 0 | }; |
873 | 0 | } |
874 | | |
875 | 0 | struct llama_batch llama_batch_init(int32_t n_tokens_alloc, int32_t embd, int32_t n_seq_max) { |
876 | 0 | llama_batch batch = { |
877 | 0 | /*n_tokens =*/ 0, |
878 | 0 | /*tokens =*/ nullptr, |
879 | 0 | /*embd =*/ nullptr, |
880 | 0 | /*pos =*/ nullptr, |
881 | 0 | /*n_seq_id =*/ nullptr, |
882 | 0 | /*seq_id =*/ nullptr, |
883 | 0 | /*logits =*/ nullptr, |
884 | 0 | }; |
885 | |
|
886 | 0 | if (embd) { |
887 | 0 | batch.embd = (float *) malloc(sizeof(float) * n_tokens_alloc * embd); |
888 | 0 | } else { |
889 | 0 | batch.token = (llama_token *) malloc(sizeof(llama_token) * n_tokens_alloc); |
890 | 0 | } |
891 | |
|
892 | 0 | batch.pos = (llama_pos *) malloc(sizeof(llama_pos) * n_tokens_alloc); |
893 | 0 | batch.n_seq_id = (int32_t *) malloc(sizeof(int32_t) * n_tokens_alloc); |
894 | 0 | batch.seq_id = (llama_seq_id **) malloc(sizeof(llama_seq_id *) * (n_tokens_alloc + 1)); |
895 | 0 | for (int i = 0; i < n_tokens_alloc; ++i) { |
896 | 0 | batch.seq_id[i] = (llama_seq_id *) malloc(sizeof(llama_seq_id) * n_seq_max); |
897 | 0 | } |
898 | 0 | batch.seq_id[n_tokens_alloc] = nullptr; |
899 | |
|
900 | 0 | batch.logits = (int8_t *) malloc(sizeof(int8_t) * n_tokens_alloc); |
901 | |
|
902 | 0 | return batch; |
903 | 0 | } |
904 | | |
905 | 0 | void llama_batch_free(struct llama_batch batch) { |
906 | 0 | if (batch.token) free(batch.token); |
907 | 0 | if (batch.embd) free(batch.embd); |
908 | 0 | if (batch.pos) free(batch.pos); |
909 | 0 | if (batch.n_seq_id) free(batch.n_seq_id); |
910 | 0 | if (batch.seq_id) { |
911 | 0 | for (int i = 0; batch.seq_id[i] != nullptr; ++i) { |
912 | 0 | free(batch.seq_id[i]); |
913 | 0 | } |
914 | 0 | free(batch.seq_id); |
915 | 0 | } |
916 | 0 | if (batch.logits) free(batch.logits); |
917 | 0 | } |