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e9b278ac6e
* doxygenize and update API documentation * fix spelling * add "fuzz" corpus for java decoder to improve coverage * use upper-case-snake names for dictionary constant definitions * use `LDFLAGS` in conventional `Makefile`
433 lines
16 KiB
C
433 lines
16 KiB
C
/* NOLINT(build/header_guard) */
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/* Copyright 2013 Google Inc. All Rights Reserved.
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Distributed under MIT license.
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See file LICENSE for detail or copy at https://opensource.org/licenses/MIT
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*/
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/* template parameters: FN, DataType */
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#define HistogramType FN(Histogram)
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static void FN(InitialEntropyCodes)(const DataType* data, size_t length,
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size_t stride,
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size_t num_histograms,
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HistogramType* histograms) {
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unsigned int seed = 7;
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size_t block_length = length / num_histograms;
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size_t i;
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FN(ClearHistograms)(histograms, num_histograms);
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for (i = 0; i < num_histograms; ++i) {
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size_t pos = length * i / num_histograms;
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if (i != 0) {
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pos += MyRand(&seed) % block_length;
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}
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if (pos + stride >= length) {
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pos = length - stride - 1;
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}
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FN(HistogramAddVector)(&histograms[i], data + pos, stride);
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}
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}
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static void FN(RandomSample)(unsigned int* seed,
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const DataType* data,
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size_t length,
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size_t stride,
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HistogramType* sample) {
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size_t pos = 0;
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if (stride >= length) {
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pos = 0;
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stride = length;
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} else {
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pos = MyRand(seed) % (length - stride + 1);
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}
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FN(HistogramAddVector)(sample, data + pos, stride);
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}
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static void FN(RefineEntropyCodes)(const DataType* data, size_t length,
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size_t stride,
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size_t num_histograms,
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HistogramType* histograms) {
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size_t iters =
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kIterMulForRefining * length / stride + kMinItersForRefining;
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unsigned int seed = 7;
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size_t iter;
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iters = ((iters + num_histograms - 1) / num_histograms) * num_histograms;
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for (iter = 0; iter < iters; ++iter) {
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HistogramType sample;
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FN(HistogramClear)(&sample);
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FN(RandomSample)(&seed, data, length, stride, &sample);
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FN(HistogramAddHistogram)(&histograms[iter % num_histograms], &sample);
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}
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}
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/* Assigns a block id from the range [0, num_histograms) to each data element
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in data[0..length) and fills in block_id[0..length) with the assigned values.
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Returns the number of blocks, i.e. one plus the number of block switches. */
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static size_t FN(FindBlocks)(const DataType* data, const size_t length,
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const double block_switch_bitcost,
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const size_t num_histograms,
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const HistogramType* histograms,
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double* insert_cost,
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double* cost,
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uint8_t* switch_signal,
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uint8_t *block_id) {
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const size_t data_size = FN(HistogramDataSize)();
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const size_t bitmaplen = (num_histograms + 7) >> 3;
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size_t num_blocks = 1;
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size_t i;
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size_t j;
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assert(num_histograms <= 256);
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if (num_histograms <= 1) {
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for (i = 0; i < length; ++i) {
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block_id[i] = 0;
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}
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return 1;
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}
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memset(insert_cost, 0, sizeof(insert_cost[0]) * data_size * num_histograms);
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for (i = 0; i < num_histograms; ++i) {
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insert_cost[i] = FastLog2((uint32_t)histograms[i].total_count_);
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}
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for (i = data_size; i != 0;) {
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--i;
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for (j = 0; j < num_histograms; ++j) {
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insert_cost[i * num_histograms + j] =
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insert_cost[j] - BitCost(histograms[j].data_[i]);
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}
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}
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memset(cost, 0, sizeof(cost[0]) * num_histograms);
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memset(switch_signal, 0, sizeof(switch_signal[0]) * length * bitmaplen);
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/* After each iteration of this loop, cost[k] will contain the difference
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between the minimum cost of arriving at the current byte position using
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entropy code k, and the minimum cost of arriving at the current byte
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position. This difference is capped at the block switch cost, and if it
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reaches block switch cost, it means that when we trace back from the last
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position, we need to switch here. */
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for (i = 0; i < length; ++i) {
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const size_t byte_ix = i;
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size_t ix = byte_ix * bitmaplen;
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size_t insert_cost_ix = data[byte_ix] * num_histograms;
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double min_cost = 1e99;
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double block_switch_cost = block_switch_bitcost;
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size_t k;
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for (k = 0; k < num_histograms; ++k) {
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/* We are coding the symbol in data[byte_ix] with entropy code k. */
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cost[k] += insert_cost[insert_cost_ix + k];
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if (cost[k] < min_cost) {
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min_cost = cost[k];
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block_id[byte_ix] = (uint8_t)k;
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}
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}
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/* More blocks for the beginning. */
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if (byte_ix < 2000) {
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block_switch_cost *= 0.77 + 0.07 * (double)byte_ix / 2000;
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}
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for (k = 0; k < num_histograms; ++k) {
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cost[k] -= min_cost;
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if (cost[k] >= block_switch_cost) {
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const uint8_t mask = (uint8_t)(1u << (k & 7));
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cost[k] = block_switch_cost;
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assert((k >> 3) < bitmaplen);
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switch_signal[ix + (k >> 3)] |= mask;
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}
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}
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}
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{ /* Trace back from the last position and switch at the marked places. */
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size_t byte_ix = length - 1;
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size_t ix = byte_ix * bitmaplen;
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uint8_t cur_id = block_id[byte_ix];
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while (byte_ix > 0) {
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const uint8_t mask = (uint8_t)(1u << (cur_id & 7));
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assert(((size_t)cur_id >> 3) < bitmaplen);
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--byte_ix;
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ix -= bitmaplen;
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if (switch_signal[ix + (cur_id >> 3)] & mask) {
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if (cur_id != block_id[byte_ix]) {
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cur_id = block_id[byte_ix];
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++num_blocks;
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}
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}
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block_id[byte_ix] = cur_id;
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}
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}
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return num_blocks;
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}
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static size_t FN(RemapBlockIds)(uint8_t* block_ids, const size_t length,
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uint16_t* new_id, const size_t num_histograms) {
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static const uint16_t kInvalidId = 256;
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uint16_t next_id = 0;
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size_t i;
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for (i = 0; i < num_histograms; ++i) {
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new_id[i] = kInvalidId;
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}
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for (i = 0; i < length; ++i) {
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assert(block_ids[i] < num_histograms);
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if (new_id[block_ids[i]] == kInvalidId) {
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new_id[block_ids[i]] = next_id++;
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}
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}
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for (i = 0; i < length; ++i) {
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block_ids[i] = (uint8_t)new_id[block_ids[i]];
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assert(block_ids[i] < num_histograms);
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}
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assert(next_id <= num_histograms);
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return next_id;
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}
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static void FN(BuildBlockHistograms)(const DataType* data, const size_t length,
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const uint8_t* block_ids,
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const size_t num_histograms,
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HistogramType* histograms) {
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size_t i;
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FN(ClearHistograms)(histograms, num_histograms);
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for (i = 0; i < length; ++i) {
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FN(HistogramAdd)(&histograms[block_ids[i]], data[i]);
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}
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}
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static void FN(ClusterBlocks)(MemoryManager* m,
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const DataType* data, const size_t length,
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const size_t num_blocks,
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uint8_t* block_ids,
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BlockSplit* split) {
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uint32_t* histogram_symbols = BROTLI_ALLOC(m, uint32_t, num_blocks);
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uint32_t* block_lengths = BROTLI_ALLOC(m, uint32_t, num_blocks);
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const size_t expected_num_clusters = CLUSTERS_PER_BATCH *
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(num_blocks + HISTOGRAMS_PER_BATCH - 1) / HISTOGRAMS_PER_BATCH;
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size_t all_histograms_size = 0;
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size_t all_histograms_capacity = expected_num_clusters;
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HistogramType* all_histograms =
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BROTLI_ALLOC(m, HistogramType, all_histograms_capacity);
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size_t cluster_size_size = 0;
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size_t cluster_size_capacity = expected_num_clusters;
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uint32_t* cluster_size = BROTLI_ALLOC(m, uint32_t, cluster_size_capacity);
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size_t num_clusters = 0;
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HistogramType* histograms = BROTLI_ALLOC(m, HistogramType,
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BROTLI_MIN(size_t, num_blocks, HISTOGRAMS_PER_BATCH));
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size_t max_num_pairs =
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HISTOGRAMS_PER_BATCH * HISTOGRAMS_PER_BATCH / 2;
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size_t pairs_capacity = max_num_pairs + 1;
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HistogramPair* pairs = BROTLI_ALLOC(m, HistogramPair, pairs_capacity);
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size_t pos = 0;
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uint32_t* clusters;
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size_t num_final_clusters;
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static const uint32_t kInvalidIndex = BROTLI_UINT32_MAX;
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uint32_t* new_index;
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uint8_t max_type = 0;
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size_t i;
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uint32_t sizes[HISTOGRAMS_PER_BATCH] = { 0 };
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uint32_t new_clusters[HISTOGRAMS_PER_BATCH] = { 0 };
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uint32_t symbols[HISTOGRAMS_PER_BATCH] = { 0 };
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uint32_t remap[HISTOGRAMS_PER_BATCH] = { 0 };
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if (BROTLI_IS_OOM(m)) return;
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memset(block_lengths, 0, num_blocks * sizeof(uint32_t));
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{
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size_t block_idx = 0;
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for (i = 0; i < length; ++i) {
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assert(block_idx < num_blocks);
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++block_lengths[block_idx];
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if (i + 1 == length || block_ids[i] != block_ids[i + 1]) {
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++block_idx;
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}
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}
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assert(block_idx == num_blocks);
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}
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for (i = 0; i < num_blocks; i += HISTOGRAMS_PER_BATCH) {
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const size_t num_to_combine =
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BROTLI_MIN(size_t, num_blocks - i, HISTOGRAMS_PER_BATCH);
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size_t num_new_clusters;
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size_t j;
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for (j = 0; j < num_to_combine; ++j) {
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size_t k;
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FN(HistogramClear)(&histograms[j]);
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for (k = 0; k < block_lengths[i + j]; ++k) {
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FN(HistogramAdd)(&histograms[j], data[pos++]);
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}
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histograms[j].bit_cost_ = FN(BrotliPopulationCost)(&histograms[j]);
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new_clusters[j] = (uint32_t)j;
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symbols[j] = (uint32_t)j;
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sizes[j] = 1;
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}
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num_new_clusters = FN(BrotliHistogramCombine)(
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histograms, sizes, symbols, new_clusters, pairs, num_to_combine,
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num_to_combine, HISTOGRAMS_PER_BATCH, max_num_pairs);
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BROTLI_ENSURE_CAPACITY(m, HistogramType, all_histograms,
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all_histograms_capacity, all_histograms_size + num_new_clusters);
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BROTLI_ENSURE_CAPACITY(m, uint32_t, cluster_size,
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cluster_size_capacity, cluster_size_size + num_new_clusters);
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if (BROTLI_IS_OOM(m)) return;
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for (j = 0; j < num_new_clusters; ++j) {
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all_histograms[all_histograms_size++] = histograms[new_clusters[j]];
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cluster_size[cluster_size_size++] = sizes[new_clusters[j]];
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remap[new_clusters[j]] = (uint32_t)j;
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}
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for (j = 0; j < num_to_combine; ++j) {
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histogram_symbols[i + j] = (uint32_t)num_clusters + remap[symbols[j]];
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}
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num_clusters += num_new_clusters;
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assert(num_clusters == cluster_size_size);
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assert(num_clusters == all_histograms_size);
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}
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BROTLI_FREE(m, histograms);
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max_num_pairs =
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BROTLI_MIN(size_t, 64 * num_clusters, (num_clusters / 2) * num_clusters);
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if (pairs_capacity < max_num_pairs + 1) {
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BROTLI_FREE(m, pairs);
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pairs = BROTLI_ALLOC(m, HistogramPair, max_num_pairs + 1);
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if (BROTLI_IS_OOM(m)) return;
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}
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clusters = BROTLI_ALLOC(m, uint32_t, num_clusters);
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if (BROTLI_IS_OOM(m)) return;
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for (i = 0; i < num_clusters; ++i) {
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clusters[i] = (uint32_t)i;
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}
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num_final_clusters = FN(BrotliHistogramCombine)(
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all_histograms, cluster_size, histogram_symbols, clusters, pairs,
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num_clusters, num_blocks, BROTLI_MAX_NUMBER_OF_BLOCK_TYPES,
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max_num_pairs);
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BROTLI_FREE(m, pairs);
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BROTLI_FREE(m, cluster_size);
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new_index = BROTLI_ALLOC(m, uint32_t, num_clusters);
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if (BROTLI_IS_OOM(m)) return;
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for (i = 0; i < num_clusters; ++i) new_index[i] = kInvalidIndex;
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pos = 0;
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{
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uint32_t next_index = 0;
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for (i = 0; i < num_blocks; ++i) {
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HistogramType histo;
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size_t j;
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uint32_t best_out;
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double best_bits;
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FN(HistogramClear)(&histo);
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for (j = 0; j < block_lengths[i]; ++j) {
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FN(HistogramAdd)(&histo, data[pos++]);
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}
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best_out = (i == 0) ? histogram_symbols[0] : histogram_symbols[i - 1];
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best_bits =
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FN(BrotliHistogramBitCostDistance)(&histo, &all_histograms[best_out]);
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for (j = 0; j < num_final_clusters; ++j) {
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const double cur_bits = FN(BrotliHistogramBitCostDistance)(
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&histo, &all_histograms[clusters[j]]);
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if (cur_bits < best_bits) {
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best_bits = cur_bits;
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best_out = clusters[j];
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}
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}
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histogram_symbols[i] = best_out;
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if (new_index[best_out] == kInvalidIndex) {
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new_index[best_out] = next_index++;
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}
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}
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}
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BROTLI_FREE(m, clusters);
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BROTLI_FREE(m, all_histograms);
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BROTLI_ENSURE_CAPACITY(
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m, uint8_t, split->types, split->types_alloc_size, num_blocks);
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BROTLI_ENSURE_CAPACITY(
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m, uint32_t, split->lengths, split->lengths_alloc_size, num_blocks);
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if (BROTLI_IS_OOM(m)) return;
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{
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uint32_t cur_length = 0;
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size_t block_idx = 0;
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for (i = 0; i < num_blocks; ++i) {
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cur_length += block_lengths[i];
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if (i + 1 == num_blocks ||
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histogram_symbols[i] != histogram_symbols[i + 1]) {
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const uint8_t id = (uint8_t)new_index[histogram_symbols[i]];
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split->types[block_idx] = id;
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split->lengths[block_idx] = cur_length;
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max_type = BROTLI_MAX(uint8_t, max_type, id);
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cur_length = 0;
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++block_idx;
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}
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}
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split->num_blocks = block_idx;
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split->num_types = (size_t)max_type + 1;
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}
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BROTLI_FREE(m, new_index);
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BROTLI_FREE(m, block_lengths);
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BROTLI_FREE(m, histogram_symbols);
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}
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static void FN(SplitByteVector)(MemoryManager* m,
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const DataType* data, const size_t length,
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const size_t literals_per_histogram,
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const size_t max_histograms,
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const size_t sampling_stride_length,
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const double block_switch_cost,
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const BrotliEncoderParams* params,
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BlockSplit* split) {
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const size_t data_size = FN(HistogramDataSize)();
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size_t num_histograms = length / literals_per_histogram + 1;
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HistogramType* histograms;
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if (num_histograms > max_histograms) {
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num_histograms = max_histograms;
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}
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if (length == 0) {
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split->num_types = 1;
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return;
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} else if (length < kMinLengthForBlockSplitting) {
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BROTLI_ENSURE_CAPACITY(m, uint8_t,
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split->types, split->types_alloc_size, split->num_blocks + 1);
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BROTLI_ENSURE_CAPACITY(m, uint32_t,
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split->lengths, split->lengths_alloc_size, split->num_blocks + 1);
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if (BROTLI_IS_OOM(m)) return;
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split->num_types = 1;
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split->types[split->num_blocks] = 0;
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split->lengths[split->num_blocks] = (uint32_t)length;
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split->num_blocks++;
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return;
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}
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histograms = BROTLI_ALLOC(m, HistogramType, num_histograms);
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if (BROTLI_IS_OOM(m)) return;
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/* Find good entropy codes. */
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FN(InitialEntropyCodes)(data, length,
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sampling_stride_length,
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num_histograms, histograms);
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FN(RefineEntropyCodes)(data, length,
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sampling_stride_length,
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num_histograms, histograms);
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{
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/* Find a good path through literals with the good entropy codes. */
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uint8_t* block_ids = BROTLI_ALLOC(m, uint8_t, length);
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size_t num_blocks;
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const size_t bitmaplen = (num_histograms + 7) >> 3;
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double* insert_cost = BROTLI_ALLOC(m, double, data_size * num_histograms);
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double* cost = BROTLI_ALLOC(m, double, num_histograms);
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uint8_t* switch_signal = BROTLI_ALLOC(m, uint8_t, length * bitmaplen);
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uint16_t* new_id = BROTLI_ALLOC(m, uint16_t, num_histograms);
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const size_t iters = params->quality < HQ_ZOPFLIFICATION_QUALITY ? 3 : 10;
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size_t i;
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if (BROTLI_IS_OOM(m)) return;
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for (i = 0; i < iters; ++i) {
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num_blocks = FN(FindBlocks)(data, length,
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block_switch_cost,
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num_histograms, histograms,
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insert_cost, cost, switch_signal,
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block_ids);
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num_histograms = FN(RemapBlockIds)(block_ids, length,
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new_id, num_histograms);
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FN(BuildBlockHistograms)(data, length, block_ids,
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num_histograms, histograms);
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|
}
|
|
BROTLI_FREE(m, insert_cost);
|
|
BROTLI_FREE(m, cost);
|
|
BROTLI_FREE(m, switch_signal);
|
|
BROTLI_FREE(m, new_id);
|
|
BROTLI_FREE(m, histograms);
|
|
FN(ClusterBlocks)(m, data, length, num_blocks, block_ids, split);
|
|
if (BROTLI_IS_OOM(m)) return;
|
|
BROTLI_FREE(m, block_ids);
|
|
}
|
|
}
|
|
|
|
#undef HistogramType
|