Argument.cpp 22.5 KB
Newer Older
1
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Z
zhangjinchao01 已提交
2 3 4 5 6 7 8 9 10 11 12 13 14 15

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */

#include "Argument.h"
16
#include "paddle/math/SparseMatrix.h"
Z
zhangjinchao01 已提交
17 18 19 20

#include <algorithm>

namespace paddle {
21 22 23
static void resizeAndCopy(MatrixPtr& dest,
                          const MatrixPtr& src,
                          bool useGpu,
Z
zhangjinchao01 已提交
24 25
                          hl_stream_t stream) {
  if (src) {
26 27 28 29 30 31
    if (!dest) {
      dest = src->clone(0, 0, useGpu);
    } else {
      CHECK_EQ(dest->useGpu(), useGpu);
      dest->resize(src->getHeight(), src->getWidth());
    }
Z
zhangjinchao01 已提交
32 33 34 35 36 37
    dest->copyFrom(*src, stream);
  } else {
    dest.reset();
  }
}

38 39 40
static void resizeAndCopy(IVectorPtr& dest,
                          const IVectorPtr& src,
                          bool useGpu,
Z
zhangjinchao01 已提交
41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61
                          hl_stream_t stream) {
  if (src) {
    IVector::resizeOrCreate(dest, src->getSize(), useGpu);
    dest->copyFrom(*src, stream);
  } else {
    dest.reset();
  }
}

static void resizeAndCopy(ICpuGpuVectorPtr& dest,
                          const ICpuGpuVectorPtr& src,
                          bool useGpu,
                          hl_stream_t stream) {
  if (src) {
    ICpuGpuVector::resizeOrCreate(dest, src->getSize(), useGpu);
    dest->copyFrom(*src, stream);
  } else {
    dest.reset();
  }
}

62 63 64 65 66
static void resizeAndCopy(MatrixPtr& dest,
                          const MatrixPtr& src,
                          int32_t startRow,
                          int32_t copySize,
                          bool useGpu,
Z
zhangjinchao01 已提交
67 68 69 70 71
                          hl_stream_t stream = HPPL_STREAM_DEFAULT) {
  if (src) {
    CHECK_LE((size_t)startRow + copySize, src->getHeight());
    int height = copySize;
    int width = src->getWidth();
72 73 74 75 76 77
    if (!dest) {
      dest = src->clone(height, width, useGpu);
    } else {
      CHECK_EQ(dest->useGpu(), useGpu);
      dest->resize(height, width);
    }
Z
zhangjinchao01 已提交
78
    MatrixPtr submat = src->subMatrix(startRow, copySize);
79 80 81 82 83 84 85 86 87
    if (dynamic_cast<GpuSparseMatrix*>(dest.get())) {
      // copy a subMatrix of CpuSparseMatrix to GpuSparseMatrix.
      // First copy it to CPU, and then copy it to the GPU.
      MatrixPtr tmp = src->clone(height, width, false);
      tmp->copyFrom(*submat, stream);
      dest->copyFrom(*tmp, stream);
    } else {
      dest->copyFrom(*submat, stream);
    }
Z
zhangjinchao01 已提交
88 89 90 91 92
  } else {
    dest.reset();
  }
}

93 94 95 96 97
static void resizeAndCopy(IVectorPtr& dest,
                          const IVectorPtr& src,
                          int32_t startPos,
                          int32_t copySize,
                          bool useGpu,
Z
zhangjinchao01 已提交
98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125
                          hl_stream_t stream = HPPL_STREAM_DEFAULT) {
  if (src) {
    CHECK_LE((size_t)startPos + copySize, src->getSize());

    int height = copySize;
    IVector::resizeOrCreate(dest, height, useGpu);
    dest->copyFrom(src->getData() + startPos, height, stream);
  } else {
    dest.reset();
  }
}

static void resizeAndCopy(ICpuGpuVectorPtr& dest,
                          const ICpuGpuVectorPtr& src,
                          int32_t startPos,
                          int32_t copySize,
                          bool useGpu,
                          hl_stream_t stream = HPPL_STREAM_DEFAULT) {
  if (src) {
    CHECK_LE((size_t)startPos + copySize, src->getSize());

    ICpuGpuVector::resizeOrCreate(dest, copySize, useGpu);
    dest->copyFrom(*src, startPos, copySize, useGpu, stream);
  } else {
    dest.reset();
  }
}

126 127 128
static void resizeAndCopy(SVectorPtr& dest,
                          const SVectorPtr& src,
                          bool useGpu,
Z
zhangjinchao01 已提交
129 130 131 132 133 134 135 136 137 138 139 140 141 142
                          hl_stream_t stream) {
  if (src) {
    size_t height = src->size();
    if (!dest) {
      dest = std::make_shared<std::vector<std::string>>(height);
    } else {
      dest->resize(height);
    }
    std::copy_n(src->begin(), height, dest->begin());
  } else {
    dest.reset();
  }
}

143 144 145 146 147
static void resizeAndCopy(SVectorPtr& dest,
                          const SVectorPtr& src,
                          int32_t startPos,
                          int32_t copySize,
                          bool useGpu,
Z
zhangjinchao01 已提交
148 149 150 151 152 153 154 155 156 157 158 159 160 161 162
                          hl_stream_t stream = HPPL_STREAM_DEFAULT) {
  if (src) {
    CHECK_LE((size_t)startPos + copySize, src->size());
    size_t height = copySize;
    if (!dest) {
      dest = std::make_shared<std::vector<std::string>>(height);
    } else {
      dest->resize(height);
    }
    std::copy_n(src->begin() + startPos, height, dest->begin());
  } else {
    dest.reset();
  }
}

163
void Argument::resizeAndCopyFrom(const Argument& src, bool useGpu) {
164 165
  resizeAndCopyFrom(src, useGpu, HPPL_STREAM_DEFAULT);
  hl_stream_synchronize(HPPL_STREAM_DEFAULT);
166 167
}

168 169
void Argument::resizeAndCopyFrom(const Argument& src,
                                 bool useGpu,
Z
zhangjinchao01 已提交
170 171 172 173 174 175
                                 hl_stream_t stream) {
  dataId = src.dataId;
  resizeAndCopy(value, src.value, useGpu, stream);
  resizeAndCopy(grad, src.grad, useGpu, stream);
  resizeAndCopy(in, src.in, useGpu, stream);
  resizeAndCopy(ids, src.ids, useGpu, stream);
176 177 178 179
  resizeAndCopy(sequenceStartPositions,
                src.sequenceStartPositions,
                false /* useGpu */,
                stream);
Z
zhangjinchao01 已提交
180 181
  if (src.hasSubseq()) {
    resizeAndCopy(subSequenceStartPositions,
182 183 184
                  src.subSequenceStartPositions,
                  false /* useGpu */,
                  stream);
Z
zhangjinchao01 已提交
185 186
  }
  resizeAndCopy(strs, src.strs, useGpu, stream);
L
Luo Tao 已提交
187 188
  frameWidth = src.frameWidth;
  frameHeight = src.frameHeight;
Z
zhangjinchao01 已提交
189 190
}

191 192 193 194 195 196 197 198
int32_t Argument::resizeAndCopyFrom(const Argument& src,
                                    int32_t startSeq,
                                    int32_t copySize,
                                    bool useGpu) {
  int32_t size =
      resizeAndCopyFrom(src, startSeq, copySize, useGpu, HPPL_STREAM_DEFAULT);
  hl_stream_synchronize(HPPL_STREAM_DEFAULT);
  return size;
199 200
}

201 202 203 204
int32_t Argument::resizeAndCopyFrom(const Argument& src,
                                    int32_t startSeq,
                                    int32_t copySize,
                                    bool useGpu,
Z
zhangjinchao01 已提交
205 206
                                    hl_stream_t stream) {
  dataId = src.dataId;
207 208
  frameWidth = src.frameWidth;
  frameHeight = src.frameHeight;
Z
zhangjinchao01 已提交
209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228

  if (!src.sequenceStartPositions) {
    // non-sequence input, copy samples directly
    int32_t startRow = startSeq;
    resizeAndCopy(in, src.in, startRow, copySize, useGpu, stream);
    resizeAndCopy(value, src.value, startRow, copySize, useGpu, stream);
    resizeAndCopy(grad, src.grad, startRow, copySize, useGpu, stream);
    resizeAndCopy(ids, src.ids, startRow, copySize, useGpu, stream);
    resizeAndCopy(strs, src.strs, startRow, copySize, useGpu, stream);
    return copySize;
  } else {
    // sequence input
    const int* sequence = src.sequenceStartPositions->getData(false);
    int32_t startRow = sequence[startSeq];           // sample start from here
    int32_t endRow = sequence[startSeq + copySize];  // sample end
    int32_t copyFeatureSize = endRow - startRow;     // num of samples
    resizeAndCopy(in, src.in, startRow, copyFeatureSize, useGpu, stream);
    resizeAndCopy(value, src.value, startRow, copyFeatureSize, useGpu, stream);
    resizeAndCopy(grad, src.grad, startRow, copyFeatureSize, useGpu, stream);
    resizeAndCopy(ids, src.ids, startRow, copyFeatureSize, useGpu, stream);
229 230 231 232 233 234
    resizeAndCopy(sequenceStartPositions,
                  src.sequenceStartPositions,
                  startSeq,
                  copySize + 1,
                  false,
                  stream);
Z
zhangjinchao01 已提交
235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257
    // modify new sequenceStartPositions
    int* destSequences = sequenceStartPositions->getMutableData(false);
    for (int i = 0; i < copySize + 1; i++) {
      destSequences[i] -= startRow;
    }
    CHECK_EQ(destSequences[0], 0);
    CHECK_EQ(destSequences[copySize], copyFeatureSize);
    if (src.hasSubseq()) {
      // sequence has sub-sequence
      int* subSequence = src.subSequenceStartPositions->getMutableData(false);
      int32_t subStartSeq = 0;
      int32_t subEndSeq = 0;
      int numSubSequences = src.getNumSubSequences();
      for (int i = 0; i < numSubSequences + 1; i++) {
        if (subSequence[i] == startRow) {
          subStartSeq = i;
        } else if (subSequence[i] == endRow) {
          subEndSeq = i;
          break;
        }
      }
      int32_t copySubSize = subEndSeq - subStartSeq;
      resizeAndCopy(subSequenceStartPositions,
258 259 260 261 262
                    src.subSequenceStartPositions,
                    subStartSeq,
                    copySubSize + 1,
                    false,
                    stream);
Z
zhangjinchao01 已提交
263 264 265 266 267 268 269 270 271 272 273 274 275 276 277
      // modify new subSequenceStartPositions
      int* destSubSequences = subSequenceStartPositions->getMutableData(false);
      for (int i = 0; i < copySubSize + 1; i++) {
        destSubSequences[i] -= startRow;
      }
      CHECK_EQ(destSubSequences[0], 0);
      CHECK_EQ(destSubSequences[copySubSize], copyFeatureSize);
    }
    resizeAndCopy(strs, src.strs, startRow, copySize, useGpu, stream);
    return copyFeatureSize;
  }
}

void Argument::concat(const std::vector<Argument>& args,
                      const std::vector<int>& selectRows,
278 279 280 281
                      const std::vector<int>& seqStartPos,
                      bool useGpu,
                      hl_stream_t stream,
                      PassType passType) {
282
  CHECK(!subSequenceStartPositions)
283
      << "undefined behavior for subsequence positions";
284

Z
zhangjinchao01 已提交
285
  size_t batchSize = selectRows.size();
286 287 288 289 290
  auto copyArg = [batchSize, stream](MatrixPtr& dst,
                                     MatrixPtr src,
                                     int startRow,
                                     int pos,
                                     int size,
Z
zhangjinchao01 已提交
291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306
                                     bool useGpu) {
    if (!src) {
      dst.reset();
      return;
    }
    size_t width = src->getWidth();
    if (!dst) {
      dst = src->clone(batchSize, width, useGpu);
    } else {
      dst->resize(batchSize, width);
    }

    MatrixPtr tmpMatrix = dst->subMatrix(startRow, size);
    tmpMatrix->copyFrom(*src->subMatrix(pos, size), stream);
  };

307 308 309 310 311
  auto copyIds = [batchSize, stream](IVectorPtr& dst,
                                     const IVectorPtr& src,
                                     int startRow,
                                     int pos,
                                     int size,
Z
zhangjinchao01 已提交
312 313 314 315 316 317 318 319 320
                                     bool useGpu) {
    if (!src) {
      dst.reset();
      return;
    }
    IVector::resizeOrCreate(dst, batchSize, useGpu);
    dst->subVec(startRow, size)->copyFrom(*src->subVec(pos, size), stream);
  };

321 322 323 324 325
  auto copyStrs = [batchSize, stream](SVectorPtr& dst,
                                      const SVectorPtr& src,
                                      int startRow,
                                      int pos,
                                      int size,
Z
zhangjinchao01 已提交
326 327 328 329 330 331 332 333 334 335
                                      bool useGpu) {
    if (!src) {
      dst.reset();
      return;
    }
    if (!dst) {
      dst = std::make_shared<std::vector<std::string>>(batchSize);
    } else {
      dst->resize(batchSize);
    }
336 337
    std::copy(
        src->begin() + pos, src->begin() + pos + size, dst->begin() + startRow);
Z
zhangjinchao01 已提交
338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361
  };

  dataId = args[0].dataId;
  CHECK_NE(seqStartPos.size(), 0UL);
  size_t sampleNum = seqStartPos.size() - 1;
  for (size_t i = 0; i < sampleNum; ++i) {
    int startPos = seqStartPos[i];
    int endPos = seqStartPos[i + 1];
    CHECK_GE(args.size(), static_cast<size_t>(endPos - startPos));
    for (int j = startPos; j < endPos; ++j) {
      const Argument& arg = args[j - startPos];
      CHECK_EQ(arg.dataId, dataId) << "Arguments in concat should have"
                                   << " same dataId";
      const int copySize = 1;
      const int rowIdx = selectRows[j];
      copyArg(in, arg.in, j, rowIdx, copySize, useGpu);
      copyArg(value, arg.value, j, rowIdx, copySize, useGpu);
      if (passType != PASS_TEST) {
        copyArg(grad, arg.grad, j, rowIdx, copySize, useGpu);
      }
      copyIds(ids, arg.ids, j, rowIdx, copySize, useGpu);
      copyStrs(strs, arg.strs, j, rowIdx, copySize, useGpu);
    }
  }
362 363 364 365
  ICpuGpuVector::resizeOrCreate(
      sequenceStartPositions, seqStartPos.size(), useGpu);
  sequenceStartPositions->copyFrom(
      seqStartPos.data(), seqStartPos.size(), useGpu);
Z
zhangjinchao01 已提交
366 367
}

368 369 370 371
void Argument::concat(const std::vector<Argument>& args,
                      bool useGpu,
                      hl_stream_t stream,
                      PassType passType) {
Z
zhangjinchao01 已提交
372 373
  int32_t batchSize = 0;
  int64_t numSequences = 0;
374
  int64_t numSubSequences = 0;
Z
zhangjinchao01 已提交
375 376 377
  for (auto& arg : args) {
    batchSize += arg.getBatchSize();
    numSequences += arg.getNumSequences();
378
    numSubSequences += arg.getNumSubSequences();
Z
zhangjinchao01 已提交
379 380
  }

381 382
  auto copyArg = [batchSize, stream](
      MatrixPtr& dst, MatrixPtr src, int startRow, bool useGpu) {
Z
zhangjinchao01 已提交
383 384 385 386 387 388 389 390 391 392 393 394 395 396 397
    if (!src) {
      dst.reset();
      return;
    }
    size_t width = src->getWidth();
    if (!dst) {
      dst = src->clone(batchSize, width, useGpu);
    } else {
      dst->resize(batchSize, width);
    }

    MatrixPtr tmpMatrix = dst->subMatrix(startRow, src->getHeight());
    tmpMatrix->copyFrom(*src, stream);
  };

398 399
  auto copyIds = [batchSize, stream](
      IVectorPtr& dst, const IVectorPtr& src, int startRow, bool useGpu) {
Z
zhangjinchao01 已提交
400 401 402 403 404 405 406 407
    if (!src) {
      dst.reset();
      return;
    }
    IVector::resizeOrCreate(dst, batchSize, useGpu);
    dst->subVec(startRow, src->getSize())->copyFrom(*src, stream);
  };

408 409
  auto copyStrs = [batchSize, stream](
      SVectorPtr& dst, const SVectorPtr& src, int startRow, bool useGpu) {
Z
zhangjinchao01 已提交
410 411 412 413 414 415 416 417 418 419 420 421
    if (!src) {
      dst.reset();
      return;
    }
    if (!dst) {
      dst = std::make_shared<std::vector<std::string>>(batchSize);
    } else {
      dst->resize(batchSize);
    }
    std::copy(src->begin(), src->end(), dst->begin() + startRow);
  };

422 423 424 425 426 427 428 429 430 431 432 433
  auto copySequencePos = [](ICpuGpuVectorPtr& dstSeq,
                            const ICpuGpuVectorPtr& srcSeq,
                            int dstNumSequences,
                            int srcNumSequences,
                            int& startSequences,
                            int startRow) {
    if (srcSeq) {
      ICpuGpuVector::resizeOrCreate(dstSeq, dstNumSequences + 1, false);
      const int* src = srcSeq->getData(false);
      int* dest = dstSeq->getMutableData(false);
      for (int i = 0; i < srcNumSequences + 1; ++i) {
        dest[i + startSequences] = src[i] + startRow;
434
      }
435 436 437 438
      startSequences += srcNumSequences;
    } else {
      dstSeq.reset();
    }
439 440
  };

Z
zhangjinchao01 已提交
441 442
  int startRow = 0;
  int startSequences = 0;
443
  int startSubSequences = 0;
Z
zhangjinchao01 已提交
444 445 446 447 448 449 450 451
  dataId = args[0].dataId;
  for (auto& arg : args) {
    CHECK_EQ(arg.dataId, dataId) << "Arguments in concat should have"
                                 << " same dataId";
    copyArg(in, arg.in, startRow, useGpu);
    copyArg(value, arg.value, startRow, useGpu);
    if (passType != PASS_TEST) copyArg(grad, arg.grad, startRow, useGpu);
    copyIds(ids, arg.ids, startRow, useGpu);
452 453 454 455 456 457 458 459 460 461 462 463
    copySequencePos(sequenceStartPositions,
                    arg.sequenceStartPositions,
                    numSequences,
                    arg.getNumSequences(),
                    startSequences,
                    startRow);
    copySequencePos(subSequenceStartPositions,
                    arg.subSequenceStartPositions,
                    numSubSequences,
                    arg.getNumSubSequences(),
                    startSubSequences,
                    startRow);
Z
zhangjinchao01 已提交
464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488
    copyStrs(strs, arg.strs, startRow, useGpu);
    startRow += arg.getBatchSize();
  }
}

void Argument::splitByDataId(const std::vector<Argument>& argus,
                             std::vector<std::vector<Argument>>* arguGroups) {
  arguGroups->clear();
  int lastDataId = -1;
  for (const auto& argu : argus) {
    if (argu.dataId == -1) {
      // is -1, then create a new group
      arguGroups->emplace_back();
      lastDataId = -1;
    } else if (argu.dataId != lastDataId) {
      // not -1, also not equal to last Argument, then create a new group
      arguGroups->emplace_back();
      lastDataId = argu.dataId;
    } else {
      // not -1, and equal to last Argument, do nothing
    }
    arguGroups->back().push_back(argu);
  }
}

489
void Argument::getSeqInfo(std::vector<SeqInfo>* seqInfo) const {
Z
zhangjinchao01 已提交
490
  const int* starts = sequenceStartPositions->getData(false);
491 492
  const int* subStarts =
      hasSubseq() ? subSequenceStartPositions->getData(false) : nullptr;
493 494 495 496 497 498 499 500 501 502 503 504
  size_t numSequences = getNumSequences();
  seqInfo->reserve(numSequences);
  int subSeqEnd = 0;
  for (size_t i = 0; i < numSequences; ++i) {
    SeqInfo info;
    info.seqStart = starts[i];
    info.subLevelLength = starts[i + 1] - starts[i];
    info.seqId = i;
    if (hasSubseq()) {
      info.subSeqStart = subSeqEnd;
      while (subStarts[subSeqEnd] < starts[i + 1]) {
        ++subSeqEnd;
Z
zhangjinchao01 已提交
505
      }
506 507 508 509
      info.topLevelLength = subSeqEnd - info.subSeqStart;
    } else {
      info.topLevelLength = info.subLevelLength;
      info.subSeqStart = 0;  // not used
Z
zhangjinchao01 已提交
510
    }
511
    seqInfo->push_back(info);
Z
zhangjinchao01 已提交
512
  }
Y
Yu Yang 已提交
513 514 515 516
  std::sort(
      seqInfo->begin(), seqInfo->end(), [](const SeqInfo& a, const SeqInfo& b) {
        return a.topLevelLength > b.topLevelLength;
      });
Z
zhangjinchao01 已提交
517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542
}

void Argument::checkSubset() const {
  if (getNumSequences() > getNumSubSequences()) {
    LOG(FATAL) << "numSubSequences is less than numSequences ("
               << getNumSubSequences() << " vs. " << getNumSequences() << ")";
  }
  const int* start = sequenceStartPositions->getData(false);
  const int* subStart = subSequenceStartPositions->getData(false);
  int seqId = 0;
  int subSeqId = 0;
  while (seqId < getNumSequences() && subSeqId < getNumSubSequences()) {
    if (start[seqId] > subStart[subSeqId]) {
      ++subSeqId;
    } else if (start[seqId] == subStart[subSeqId]) {
      ++subSeqId;
      ++seqId;
    } else {
      LOG(FATAL) << "seqStartPositions is not subset of subSeqStartPositions";
    }
  }
  if (seqId < getNumSequences()) {
    LOG(FATAL) << "seqStartPositions is not subset of subSeqStartPositions";
  }
}

543
void Argument::degradeSequence(const Argument& input) {
Z
zhangjinchao01 已提交
544 545 546
  CHECK_EQ(input.hasSubseq(), 1UL);
  size_t numSequences = input.getNumSequences();
  size_t numSubSequences = input.getNumSubSequences();
547 548
  ICpuGpuVector::resizeOrCreate(
      sequenceStartPositions, numSequences + 1, false);
Z
zhangjinchao01 已提交
549 550 551 552 553 554 555 556 557 558 559 560 561
  int* tgtBuf = sequenceStartPositions->getMutableData(false);
  const int* starts = input.sequenceStartPositions->getData(false);
  const int* subStarts = input.subSequenceStartPositions->getData(false);
  int seqId = 0;
  for (size_t subSeqId = 0; subSeqId < numSubSequences; ++subSeqId) {
    if (subStarts[subSeqId] == starts[seqId]) {
      tgtBuf[seqId] = subSeqId;
      seqId++;
    }
  }
  tgtBuf[numSequences] = numSubSequences;
}

562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601
void Argument::poolSequenceWithStride(const Argument& input,
                                      size_t stride,
                                      std::vector<int>* stridePostions) {
  /*
   * If input.sequenceStartPositions = [0, 9, 14, 17, 30] and stride = 5,
   * then sequenceStartPositions = [0, 2, 3, 4, 7],
   * and stridePostions = [0, 5, 9, 14, 17, 22, 27, 30]
   */
  CHECK(input.sequenceStartPositions);
  CHECK_EQ(input.hasSubseq(), 0UL);
  CHECK_GT(stride, 0) << "stride must larger than 0";
  size_t numSequences = input.getNumSequences();
  ICpuGpuVector::resizeOrCreate(
      sequenceStartPositions, numSequences + 1, false);
  const int* starts = input.sequenceStartPositions->getData(false);
  int* tgtBuf = sequenceStartPositions->getMutableData(false);
  // first index of target sequence and stride positions are both 0
  tgtBuf[0] = 0;
  (*stridePostions).clear();
  for (size_t seqId = 0; seqId < numSequences; ++seqId) {
    size_t seqLength = starts[seqId + 1] - starts[seqId];
    (*stridePostions).emplace_back(starts[seqId]);
    if (seqLength == 0) {
      // empty sequence
      tgtBuf[seqId + 1] = tgtBuf[seqId];
    } else if (seqLength < stride) {
      tgtBuf[seqId + 1] = tgtBuf[seqId] + 1;
    } else {
      tgtBuf[seqId + 1] = tgtBuf[seqId] + ceil((float)seqLength / stride);
      int size =
          (seqLength % stride) ? seqLength / stride : seqLength / stride - 1;
      for (int i = 0; i < size; i++) {
        (*stridePostions).emplace_back((*stridePostions).back() + stride);
      }
    }
  }
  (*stridePostions).emplace_back(starts[numSequences]);
  CHECK_EQ((*stridePostions).size() - 1, tgtBuf[numSequences]);
}

602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627
void Argument::getValueString(
    std::unordered_map<std::string, std::string>* out) const {
  if (value) {
    std::ostringstream os;
    value->print(os);
    out->insert({"value", os.str()});
  }
  if (ids) {
    std::ostringstream os;
    ids->print(os, ids->getSize());
    out->insert({"ids", os.str()});
  }
  if (sequenceStartPositions) {
    std::ostringstream os;
    sequenceStartPositions->getVector(false)->print(
        os, sequenceStartPositions->getSize());
    out->insert({"sequence pos", os.str()});
  }
  if (subSequenceStartPositions) {
    std::ostringstream os;
    subSequenceStartPositions->getVector(false)->print(
        os, subSequenceStartPositions->getSize());
    out->insert({"sub-sequence pos", os.str()});
  }
}

628 629 630 631 632 633 634 635 636 637 638 639
void Argument::printValueString(std::ostream& stream,
                                const std::string& prefix) const {
  std::unordered_map<std::string, std::string> out;
  getValueString(&out);
  for (auto field : {"value", "id", "sequence pos", "sub-sequence pos"}) {
    auto it = out.find(field);
    if (it != out.end()) {
      stream << prefix << field << ":\n" << it->second;
    }
  }
}

640 641 642 643 644 645 646 647 648
void Argument::subArgFrom(const Argument& input,
                          size_t offset,
                          size_t height,
                          size_t width,
                          bool useGpu,
                          bool trans,
                          bool seqFlag,
                          size_t seqStart,
                          size_t seqSize) {
649
  if (input.value) {
650 651
    value = Matrix::create(
        input.value->getData() + offset * width, height, width, trans, useGpu);
652 653 654 655
  }
  if (input.ids) {
    ids = IVector::create(input.ids->getData() + offset, height, useGpu);
  }
Z
zhangjinchao01 已提交
656
  if (input.grad) {
657 658
    grad = Matrix::create(
        input.grad->getData() + offset * width, height, width, trans, useGpu);
Z
zhangjinchao01 已提交
659 660 661
  }
  if (seqFlag) {
    sequenceStartPositions = std::make_shared<ICpuGpuVector>(
662
        *(input.sequenceStartPositions), seqStart, seqSize);
Z
zhangjinchao01 已提交
663 664 665 666
  }
}

}  // namespace paddle