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35e69fc7cf
* New feature: "Large Window Brotli" By setting special encoder/decoder flag it is now possible to extend LZ-window up to 30 bits; though produced stream will not be RFC7932 compliant. Added new dictionary generator - "DSH". It combines speed of "Sieve" and quality of "DM". Plus utilities to prepare train corpora (remove unique strings). Improved compression ratio: now two sub-blocks could be stitched: the last copy command could be extended to span the next sub-block. Fixed compression ineffectiveness caused by floating numbers rounding and wrong cost heuristic. Other C changes: - combined / moved `context.h` to `common` - moved transforms to `common` - unified some aspects of code formatting - added an abstraction for encoder (static) dictionary - moved default allocator/deallocator functions to `common` brotli CLI: - window size is auto-adjusted if not specified explicitly Java: - added "eager" decoding both to JNI wrapper and pure decoder - huge speed-up of `DictionaryData` initialization * Add dictionaryless compressed dictionary * Fix `sources.lst` * Fix `sources.lst` and add a note that `libtool` is also required. * Update setup.py * Fix `EagerStreamTest` * Fix BUILD file * Add missing `libdivsufsort` dependency * Fix "unused parameter" warning.
260 lines
7.3 KiB
C++
Executable File
260 lines
7.3 KiB
C++
Executable File
#include "./sieve.h"
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/* Pointer to position in (combined corpus) text. */
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typedef uint32_t TextIdx;
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/* Index of sample / generation. */
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typedef uint16_t SampleIdx;
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typedef struct Slot {
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TextIdx next;
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TextIdx offset;
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SampleIdx presence;
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SampleIdx mark;
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} Slot;
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static const TextIdx kNowhere = static_cast<TextIdx>(-1);
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static TextIdx dryRun(TextIdx sliceLen, Slot* map, TextIdx* shortcut,
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TextIdx end, TextIdx middle, SampleIdx minPresence, SampleIdx iteration) {
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TextIdx from = kNowhere;
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TextIdx to = kNowhere;
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TextIdx result = 0;
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SampleIdx targetPresence = minPresence;
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for (TextIdx i = 0; i < end; ++i) {
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if (i == middle) {
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targetPresence++;
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}
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Slot& item = map[shortcut[i]];
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if (item.mark != iteration) {
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item.mark = iteration;
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if (item.presence >= targetPresence) {
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if ((to == kNowhere) || (to < i)) {
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if (from != kNowhere) {
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result += to - from;
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}
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from = i;
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}
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to = i + sliceLen;
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}
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}
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}
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if (from != kNowhere) {
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result += to - from;
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}
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return result;
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}
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static std::string createDictionary(const uint8_t* data, TextIdx sliceLen,
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Slot* map, TextIdx* shortcut, TextIdx end, TextIdx middle,
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SampleIdx minPresence, SampleIdx iteration) {
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std::string output;
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TextIdx from = kNowhere;
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TextIdx to = kNowhere;
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SampleIdx targetPresence = minPresence;
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for (TextIdx i = 0; i < end; ++i) {
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if (i == middle) {
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targetPresence++;
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}
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Slot& item = map[shortcut[i]];
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if (item.mark != iteration) {
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item.mark = iteration;
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if (item.presence >= targetPresence) {
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if ((to == kNowhere) || (to < i)) {
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if (from != kNowhere) {
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output.insert(output.end(), &data[from], &data[to]);
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}
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from = i;
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}
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to = i + sliceLen;
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}
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}
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}
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if (from != kNowhere) {
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output.insert(output.end(), &data[from], &data[to]);
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}
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return output;
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}
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std::string sieve_generate(size_t dictionary_size_limit, size_t slice_len,
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const std::vector<size_t>& sample_sizes, const uint8_t* sample_data) {
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/* Parameters aliasing */
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TextIdx targetSize = static_cast<TextIdx>(dictionary_size_limit);
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if (targetSize != dictionary_size_limit) {
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fprintf(stderr, "dictionary_size_limit is too large\n");
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return "";
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}
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TextIdx sliceLen = static_cast<TextIdx>(slice_len);
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if (sliceLen != slice_len) {
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fprintf(stderr, "slice_len is too large\n");
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return "";
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}
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if (sliceLen < 1) {
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fprintf(stderr, "slice_len is too small\n");
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return "";
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}
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SampleIdx numSamples = static_cast<SampleIdx>(sample_sizes.size());
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if ((numSamples != sample_sizes.size()) || (numSamples * 2 < numSamples)) {
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fprintf(stderr, "too many samples\n");
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return "";
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}
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const uint8_t* data = sample_data;
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TextIdx total = 0;
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std::vector<TextIdx> offsets;
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for (SampleIdx i = 0; i < numSamples; ++i) {
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TextIdx delta = static_cast<TextIdx>(sample_sizes[i]);
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if (delta != sample_sizes[i]) {
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fprintf(stderr, "sample is too large\n");
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return "";
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}
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if (delta == 0) {
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fprintf(stderr, "empty samples are prohibited\n");
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return "";
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}
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if (total + delta <= total) {
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fprintf(stderr, "corpus is too large\n");
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return "";
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}
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total += delta;
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offsets.push_back(total);
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}
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if (total * 2 < total) {
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fprintf(stderr, "corpus is too large\n");
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return "";
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}
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if (total < sliceLen) {
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fprintf(stderr, "slice_len is larger than corpus size\n");
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return "";
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}
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/*****************************************************************************
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* Build coverage map.
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****************************************************************************/
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std::vector<Slot> map;
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std::vector<TextIdx> shortcut;
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map.push_back({0, 0, 0, 0});
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TextIdx end = total - sliceLen;
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TextIdx hashLen = 11;
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while (hashLen < 29 && ((1u << hashLen) < end)) {
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hashLen += 3;
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}
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hashLen -= 3;
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TextIdx hashMask = (1u << hashLen) - 1u;
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std::vector<TextIdx> hashHead(1 << hashLen);
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TextIdx hashSlot = 1;
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SampleIdx piece = 0;
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TextIdx hash = 0;
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TextIdx lShift = 3;
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TextIdx rShift = hashLen - lShift;
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for (TextIdx i = 0; i < sliceLen - 1; ++i) {
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TextIdx v = data[i];
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hash = (((hash << lShift) | (hash >> rShift)) & hashMask) ^ v;
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}
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TextIdx lShiftX = (lShift * (sliceLen - 1)) % hashLen;
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TextIdx rShiftX = hashLen - lShiftX;
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for (TextIdx i = 0; i < end; ++i) {
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TextIdx v = data[i + sliceLen - 1];
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hash = (((hash << lShift) | (hash >> rShift)) & hashMask) ^ v;
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if (offsets[piece] == i) {
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piece++;
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}
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TextIdx slot = hashHead[hash];
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while (slot != 0) {
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Slot& item = map[slot];
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TextIdx start = item.offset;
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bool miss = false;
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for (TextIdx j = 0; j < sliceLen; ++j) {
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if (data[i + j] != data[start + j]) {
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miss = true;
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break;
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}
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}
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if (!miss) {
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if (item.mark != piece) {
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item.mark = piece;
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item.presence++;
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}
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shortcut.push_back(slot);
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break;
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}
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slot = item.next;
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}
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if (slot == 0) {
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map.push_back({hashHead[hash], i, 1, piece});
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hashHead[hash] = hashSlot;
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shortcut.push_back(hashSlot);
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hashSlot++;
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}
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v = data[i];
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hash ^= ((v << lShiftX) | (v >> rShiftX)) & hashMask;
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}
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/*****************************************************************************
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* Build dictionary of specified size.
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****************************************************************************/
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SampleIdx a = 1;
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TextIdx size = dryRun(
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sliceLen, map.data(), shortcut.data(), end, end, a, ++piece);
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/* Maximal output is smaller than target. */
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if (size <= targetSize) {
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return createDictionary(
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data, sliceLen, map.data(), shortcut.data(), end, end, a, ++piece);
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}
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SampleIdx b = numSamples;
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size = dryRun(sliceLen, map.data(), shortcut.data(), end, end, b, ++piece);
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if (size == targetSize) {
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return createDictionary(
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data, sliceLen, map.data(), shortcut.data(), end, end, b, ++piece);
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}
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/* Run binary search. */
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if (size < targetSize) {
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/* size(a) > targetSize > size(b) && a < m < b */
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while (a + 1 < b) {
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SampleIdx m = static_cast<SampleIdx>((a + b) / 2);
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size = dryRun(
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sliceLen, map.data(), shortcut.data(), end, end, m, ++piece);
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if (size < targetSize) {
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b = m;
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} else if (size > targetSize) {
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a = m;
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} else {
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return createDictionary(
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data, sliceLen, map.data(), shortcut.data(), end, end, b, ++piece);
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}
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}
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} else {
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a = b;
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}
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/* size(minPresence) > targetSize > size(minPresence + 1) */
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SampleIdx minPresence = a;
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TextIdx c = 0;
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TextIdx d = end;
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/* size(a) < targetSize < size(b) && a < m < b */
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while (c + 1 < d) {
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TextIdx m = (c + d) / 2;
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size = dryRun(
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sliceLen, map.data(), shortcut.data(), end, m, minPresence, ++piece);
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if (size < targetSize) {
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c = m;
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} else if (size > targetSize) {
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d = m;
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} else {
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return createDictionary(data, sliceLen, map.data(), shortcut.data(), end,
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m, minPresence, ++piece);
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}
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}
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bool unrestricted = false;
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if (minPresence <= 2 && !unrestricted) {
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minPresence = 2;
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c = end;
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}
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return createDictionary(data, sliceLen, map.data(), shortcut.data(), end, c,
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minPresence, ++piece);
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}
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