| Index: third_party/brotli/enc/block_splitter.cc
|
| diff --git a/third_party/brotli/enc/block_splitter.cc b/third_party/brotli/enc/block_splitter.cc
|
| new file mode 100644
|
| index 0000000000000000000000000000000000000000..db8d9c606d6fab28641f815e0cffdf2aa67612b2
|
| --- /dev/null
|
| +++ b/third_party/brotli/enc/block_splitter.cc
|
| @@ -0,0 +1,505 @@
|
| +/* Copyright 2013 Google Inc. All Rights Reserved.
|
| +
|
| + Distributed under MIT license.
|
| + See file LICENSE for detail or copy at https://opensource.org/licenses/MIT
|
| +*/
|
| +
|
| +// Block split point selection utilities.
|
| +
|
| +#include "./block_splitter.h"
|
| +
|
| +#include <assert.h>
|
| +#include <math.h>
|
| +
|
| +#include <algorithm>
|
| +#include <cstring>
|
| +#include <vector>
|
| +
|
| +#include "./cluster.h"
|
| +#include "./command.h"
|
| +#include "./fast_log.h"
|
| +#include "./histogram.h"
|
| +
|
| +namespace brotli {
|
| +
|
| +static const size_t kMaxLiteralHistograms = 100;
|
| +static const size_t kMaxCommandHistograms = 50;
|
| +static const double kLiteralBlockSwitchCost = 28.1;
|
| +static const double kCommandBlockSwitchCost = 13.5;
|
| +static const double kDistanceBlockSwitchCost = 14.6;
|
| +static const size_t kLiteralStrideLength = 70;
|
| +static const size_t kCommandStrideLength = 40;
|
| +static const size_t kSymbolsPerLiteralHistogram = 544;
|
| +static const size_t kSymbolsPerCommandHistogram = 530;
|
| +static const size_t kSymbolsPerDistanceHistogram = 544;
|
| +static const size_t kMinLengthForBlockSplitting = 128;
|
| +static const size_t kIterMulForRefining = 2;
|
| +static const size_t kMinItersForRefining = 100;
|
| +
|
| +void CopyLiteralsToByteArray(const Command* cmds,
|
| + const size_t num_commands,
|
| + const uint8_t* data,
|
| + const size_t offset,
|
| + const size_t mask,
|
| + std::vector<uint8_t>* literals) {
|
| + // Count how many we have.
|
| + size_t total_length = 0;
|
| + for (size_t i = 0; i < num_commands; ++i) {
|
| + total_length += cmds[i].insert_len_;
|
| + }
|
| + if (total_length == 0) {
|
| + return;
|
| + }
|
| +
|
| + // Allocate.
|
| + literals->resize(total_length);
|
| +
|
| + // Loop again, and copy this time.
|
| + size_t pos = 0;
|
| + size_t from_pos = offset & mask;
|
| + for (size_t i = 0; i < num_commands && pos < total_length; ++i) {
|
| + size_t insert_len = cmds[i].insert_len_;
|
| + if (from_pos + insert_len > mask) {
|
| + size_t head_size = mask + 1 - from_pos;
|
| + memcpy(&(*literals)[pos], data + from_pos, head_size);
|
| + from_pos = 0;
|
| + pos += head_size;
|
| + insert_len -= head_size;
|
| + }
|
| + if (insert_len > 0) {
|
| + memcpy(&(*literals)[pos], data + from_pos, insert_len);
|
| + pos += insert_len;
|
| + }
|
| + from_pos = (from_pos + insert_len + cmds[i].copy_len()) & mask;
|
| + }
|
| +}
|
| +
|
| +inline static unsigned int MyRand(unsigned int* seed) {
|
| + *seed *= 16807U;
|
| + if (*seed == 0) {
|
| + *seed = 1;
|
| + }
|
| + return *seed;
|
| +}
|
| +
|
| +template<typename HistogramType, typename DataType>
|
| +void InitialEntropyCodes(const DataType* data, size_t length,
|
| + size_t stride,
|
| + size_t num_histograms,
|
| + HistogramType* histograms) {
|
| + for (size_t i = 0; i < num_histograms; ++i) {
|
| + histograms[i].Clear();
|
| + }
|
| + unsigned int seed = 7;
|
| + size_t block_length = length / num_histograms;
|
| + for (size_t i = 0; i < num_histograms; ++i) {
|
| + size_t pos = length * i / num_histograms;
|
| + if (i != 0) {
|
| + pos += MyRand(&seed) % block_length;
|
| + }
|
| + if (pos + stride >= length) {
|
| + pos = length - stride - 1;
|
| + }
|
| + histograms[i].Add(data + pos, stride);
|
| + }
|
| +}
|
| +
|
| +template<typename HistogramType, typename DataType>
|
| +void RandomSample(unsigned int* seed,
|
| + const DataType* data,
|
| + size_t length,
|
| + size_t stride,
|
| + HistogramType* sample) {
|
| + size_t pos = 0;
|
| + if (stride >= length) {
|
| + pos = 0;
|
| + stride = length;
|
| + } else {
|
| + pos = MyRand(seed) % (length - stride + 1);
|
| + }
|
| + sample->Add(data + pos, stride);
|
| +}
|
| +
|
| +template<typename HistogramType, typename DataType>
|
| +void RefineEntropyCodes(const DataType* data, size_t length,
|
| + size_t stride,
|
| + size_t num_histograms,
|
| + HistogramType* histograms) {
|
| + size_t iters =
|
| + kIterMulForRefining * length / stride + kMinItersForRefining;
|
| + unsigned int seed = 7;
|
| + iters = ((iters + num_histograms - 1) / num_histograms) * num_histograms;
|
| + for (size_t iter = 0; iter < iters; ++iter) {
|
| + HistogramType sample;
|
| + RandomSample(&seed, data, length, stride, &sample);
|
| + size_t ix = iter % num_histograms;
|
| + histograms[ix].AddHistogram(sample);
|
| + }
|
| +}
|
| +
|
| +inline static double BitCost(size_t count) {
|
| + return count == 0 ? -2.0 : FastLog2(count);
|
| +}
|
| +
|
| +// Assigns a block id from the range [0, vec.size()) to each data element
|
| +// in data[0..length) and fills in block_id[0..length) with the assigned values.
|
| +// Returns the number of blocks, i.e. one plus the number of block switches.
|
| +template<typename DataType, int kSize>
|
| +size_t FindBlocks(const DataType* data, const size_t length,
|
| + const double block_switch_bitcost,
|
| + const size_t num_histograms,
|
| + const Histogram<kSize>* histograms,
|
| + double* insert_cost,
|
| + double* cost,
|
| + uint8_t* switch_signal,
|
| + uint8_t *block_id) {
|
| + if (num_histograms <= 1) {
|
| + for (size_t i = 0; i < length; ++i) {
|
| + block_id[i] = 0;
|
| + }
|
| + return 1;
|
| + }
|
| + const size_t bitmaplen = (num_histograms + 7) >> 3;
|
| + assert(num_histograms <= 256);
|
| + memset(insert_cost, 0, sizeof(insert_cost[0]) * kSize * num_histograms);
|
| + for (size_t j = 0; j < num_histograms; ++j) {
|
| + insert_cost[j] = FastLog2(static_cast<uint32_t>(
|
| + histograms[j].total_count_));
|
| + }
|
| + for (size_t i = kSize; i != 0;) {
|
| + --i;
|
| + for (size_t j = 0; j < num_histograms; ++j) {
|
| + insert_cost[i * num_histograms + j] =
|
| + insert_cost[j] - BitCost(histograms[j].data_[i]);
|
| + }
|
| + }
|
| + memset(cost, 0, sizeof(cost[0]) * num_histograms);
|
| + memset(switch_signal, 0, sizeof(switch_signal[0]) * length * bitmaplen);
|
| + // After each iteration of this loop, cost[k] will contain the difference
|
| + // between the minimum cost of arriving at the current byte position using
|
| + // entropy code k, and the minimum cost of arriving at the current byte
|
| + // position. This difference is capped at the block switch cost, and if it
|
| + // reaches block switch cost, it means that when we trace back from the last
|
| + // position, we need to switch here.
|
| + for (size_t byte_ix = 0; byte_ix < length; ++byte_ix) {
|
| + size_t ix = byte_ix * bitmaplen;
|
| + size_t insert_cost_ix = data[byte_ix] * num_histograms;
|
| + double min_cost = 1e99;
|
| + for (size_t k = 0; k < num_histograms; ++k) {
|
| + // We are coding the symbol in data[byte_ix] with entropy code k.
|
| + cost[k] += insert_cost[insert_cost_ix + k];
|
| + if (cost[k] < min_cost) {
|
| + min_cost = cost[k];
|
| + block_id[byte_ix] = static_cast<uint8_t>(k);
|
| + }
|
| + }
|
| + double block_switch_cost = block_switch_bitcost;
|
| + // More blocks for the beginning.
|
| + if (byte_ix < 2000) {
|
| + block_switch_cost *= 0.77 + 0.07 * static_cast<double>(byte_ix) / 2000;
|
| + }
|
| + for (size_t k = 0; k < num_histograms; ++k) {
|
| + cost[k] -= min_cost;
|
| + if (cost[k] >= block_switch_cost) {
|
| + cost[k] = block_switch_cost;
|
| + const uint8_t mask = static_cast<uint8_t>(1u << (k & 7));
|
| + assert((k >> 3) < bitmaplen);
|
| + switch_signal[ix + (k >> 3)] |= mask;
|
| + }
|
| + }
|
| + }
|
| + // Now trace back from the last position and switch at the marked places.
|
| + size_t byte_ix = length - 1;
|
| + size_t ix = byte_ix * bitmaplen;
|
| + uint8_t cur_id = block_id[byte_ix];
|
| + size_t num_blocks = 1;
|
| + while (byte_ix > 0) {
|
| + --byte_ix;
|
| + ix -= bitmaplen;
|
| + const uint8_t mask = static_cast<uint8_t>(1u << (cur_id & 7));
|
| + assert((static_cast<size_t>(cur_id) >> 3) < bitmaplen);
|
| + if (switch_signal[ix + (cur_id >> 3)] & mask) {
|
| + if (cur_id != block_id[byte_ix]) {
|
| + cur_id = block_id[byte_ix];
|
| + ++num_blocks;
|
| + }
|
| + }
|
| + block_id[byte_ix] = cur_id;
|
| + }
|
| + return num_blocks;
|
| +}
|
| +
|
| +static size_t RemapBlockIds(uint8_t* block_ids, const size_t length,
|
| + uint16_t* new_id, const size_t num_histograms) {
|
| + static const uint16_t kInvalidId = 256;
|
| + for (size_t i = 0; i < num_histograms; ++i) {
|
| + new_id[i] = kInvalidId;
|
| + }
|
| + uint16_t next_id = 0;
|
| + for (size_t i = 0; i < length; ++i) {
|
| + assert(block_ids[i] < num_histograms);
|
| + if (new_id[block_ids[i]] == kInvalidId) {
|
| + new_id[block_ids[i]] = next_id++;
|
| + }
|
| + }
|
| + for (size_t i = 0; i < length; ++i) {
|
| + block_ids[i] = static_cast<uint8_t>(new_id[block_ids[i]]);
|
| + assert(block_ids[i] < num_histograms);
|
| + }
|
| + assert(next_id <= num_histograms);
|
| + return next_id;
|
| +}
|
| +
|
| +template<typename HistogramType, typename DataType>
|
| +void BuildBlockHistograms(const DataType* data, const size_t length,
|
| + const uint8_t* block_ids,
|
| + const size_t num_histograms,
|
| + HistogramType* histograms) {
|
| + for (size_t i = 0; i < num_histograms; ++i) {
|
| + histograms[i].Clear();
|
| + }
|
| + for (size_t i = 0; i < length; ++i) {
|
| + histograms[block_ids[i]].Add(data[i]);
|
| + }
|
| +}
|
| +
|
| +template<typename HistogramType, typename DataType>
|
| +void ClusterBlocks(const DataType* data, const size_t length,
|
| + const size_t num_blocks,
|
| + uint8_t* block_ids,
|
| + BlockSplit* split) {
|
| + static const size_t kMaxNumberOfBlockTypes = 256;
|
| + static const size_t kHistogramsPerBatch = 64;
|
| + static const size_t kClustersPerBatch = 16;
|
| + std::vector<uint32_t> histogram_symbols(num_blocks);
|
| + std::vector<uint32_t> block_lengths(num_blocks);
|
| +
|
| + size_t block_idx = 0;
|
| + for (size_t i = 0; i < length; ++i) {
|
| + assert(block_idx < num_blocks);
|
| + ++block_lengths[block_idx];
|
| + if (i + 1 == length || block_ids[i] != block_ids[i + 1]) {
|
| + ++block_idx;
|
| + }
|
| + }
|
| + assert(block_idx == num_blocks);
|
| +
|
| + const size_t expected_num_clusters =
|
| + kClustersPerBatch *
|
| + (num_blocks + kHistogramsPerBatch - 1) / kHistogramsPerBatch;
|
| + std::vector<HistogramType> all_histograms;
|
| + std::vector<uint32_t> cluster_size;
|
| + all_histograms.reserve(expected_num_clusters);
|
| + cluster_size.reserve(expected_num_clusters);
|
| + size_t num_clusters = 0;
|
| + std::vector<HistogramType> histograms(
|
| + std::min(num_blocks, kHistogramsPerBatch));
|
| + size_t max_num_pairs = kHistogramsPerBatch * kHistogramsPerBatch / 2;
|
| + std::vector<HistogramPair> pairs(max_num_pairs + 1);
|
| + size_t pos = 0;
|
| + for (size_t i = 0; i < num_blocks; i += kHistogramsPerBatch) {
|
| + const size_t num_to_combine = std::min(num_blocks - i, kHistogramsPerBatch);
|
| + uint32_t sizes[kHistogramsPerBatch];
|
| + uint32_t clusters[kHistogramsPerBatch];
|
| + uint32_t symbols[kHistogramsPerBatch];
|
| + uint32_t remap[kHistogramsPerBatch];
|
| + for (size_t j = 0; j < num_to_combine; ++j) {
|
| + histograms[j].Clear();
|
| + for (size_t k = 0; k < block_lengths[i + j]; ++k) {
|
| + histograms[j].Add(data[pos++]);
|
| + }
|
| + histograms[j].bit_cost_ = PopulationCost(histograms[j]);
|
| + symbols[j] = clusters[j] = static_cast<uint32_t>(j);
|
| + sizes[j] = 1;
|
| + }
|
| + size_t num_new_clusters = HistogramCombine(
|
| + &histograms[0], sizes, symbols, clusters, &pairs[0], num_to_combine,
|
| + num_to_combine, kHistogramsPerBatch, max_num_pairs);
|
| + for (size_t j = 0; j < num_new_clusters; ++j) {
|
| + all_histograms.push_back(histograms[clusters[j]]);
|
| + cluster_size.push_back(sizes[clusters[j]]);
|
| + remap[clusters[j]] = static_cast<uint32_t>(j);
|
| + }
|
| + for (size_t j = 0; j < num_to_combine; ++j) {
|
| + histogram_symbols[i + j] =
|
| + static_cast<uint32_t>(num_clusters) + remap[symbols[j]];
|
| + }
|
| + num_clusters += num_new_clusters;
|
| + assert(num_clusters == cluster_size.size());
|
| + assert(num_clusters == all_histograms.size());
|
| + }
|
| +
|
| + max_num_pairs =
|
| + std::min(64 * num_clusters, (num_clusters / 2) * num_clusters);
|
| + pairs.resize(max_num_pairs + 1);
|
| +
|
| + std::vector<uint32_t> clusters(num_clusters);
|
| + for (size_t i = 0; i < num_clusters; ++i) {
|
| + clusters[i] = static_cast<uint32_t>(i);
|
| + }
|
| + size_t num_final_clusters =
|
| + HistogramCombine(&all_histograms[0], &cluster_size[0],
|
| + &histogram_symbols[0],
|
| + &clusters[0], &pairs[0], num_clusters,
|
| + num_blocks, kMaxNumberOfBlockTypes, max_num_pairs);
|
| +
|
| + static const uint32_t kInvalidIndex = std::numeric_limits<uint32_t>::max();
|
| + std::vector<uint32_t> new_index(num_clusters, kInvalidIndex);
|
| + uint32_t next_index = 0;
|
| + pos = 0;
|
| + for (size_t i = 0; i < num_blocks; ++i) {
|
| + HistogramType histo;
|
| + for (size_t j = 0; j < block_lengths[i]; ++j) {
|
| + histo.Add(data[pos++]);
|
| + }
|
| + uint32_t best_out =
|
| + i == 0 ? histogram_symbols[0] : histogram_symbols[i - 1];
|
| + double best_bits = HistogramBitCostDistance(
|
| + histo, all_histograms[best_out]);
|
| + for (size_t j = 0; j < num_final_clusters; ++j) {
|
| + const double cur_bits = HistogramBitCostDistance(
|
| + histo, all_histograms[clusters[j]]);
|
| + if (cur_bits < best_bits) {
|
| + best_bits = cur_bits;
|
| + best_out = clusters[j];
|
| + }
|
| + }
|
| + histogram_symbols[i] = best_out;
|
| + if (new_index[best_out] == kInvalidIndex) {
|
| + new_index[best_out] = next_index++;
|
| + }
|
| + }
|
| + uint8_t max_type = 0;
|
| + uint32_t cur_length = 0;
|
| + block_idx = 0;
|
| + split->types.resize(num_blocks);
|
| + split->lengths.resize(num_blocks);
|
| + for (size_t i = 0; i < num_blocks; ++i) {
|
| + cur_length += block_lengths[i];
|
| + if (i + 1 == num_blocks ||
|
| + histogram_symbols[i] != histogram_symbols[i + 1]) {
|
| + const uint8_t id = static_cast<uint8_t>(new_index[histogram_symbols[i]]);
|
| + split->types[block_idx] = id;
|
| + split->lengths[block_idx] = cur_length;
|
| + max_type = std::max(max_type, id);
|
| + cur_length = 0;
|
| + ++block_idx;
|
| + }
|
| + }
|
| + split->types.resize(block_idx);
|
| + split->lengths.resize(block_idx);
|
| + split->num_types = static_cast<size_t>(max_type) + 1;
|
| +}
|
| +
|
| +template<int kSize, typename DataType>
|
| +void SplitByteVector(const std::vector<DataType>& data,
|
| + const size_t literals_per_histogram,
|
| + const size_t max_histograms,
|
| + const size_t sampling_stride_length,
|
| + const double block_switch_cost,
|
| + BlockSplit* split) {
|
| + if (data.empty()) {
|
| + split->num_types = 1;
|
| + return;
|
| + } else if (data.size() < kMinLengthForBlockSplitting) {
|
| + split->num_types = 1;
|
| + split->types.push_back(0);
|
| + split->lengths.push_back(static_cast<uint32_t>(data.size()));
|
| + return;
|
| + }
|
| + size_t num_histograms = data.size() / literals_per_histogram + 1;
|
| + if (num_histograms > max_histograms) {
|
| + num_histograms = max_histograms;
|
| + }
|
| + Histogram<kSize>* histograms = new Histogram<kSize>[num_histograms];
|
| + // Find good entropy codes.
|
| + InitialEntropyCodes(&data[0], data.size(),
|
| + sampling_stride_length,
|
| + num_histograms, histograms);
|
| + RefineEntropyCodes(&data[0], data.size(),
|
| + sampling_stride_length,
|
| + num_histograms, histograms);
|
| + // Find a good path through literals with the good entropy codes.
|
| + std::vector<uint8_t> block_ids(data.size());
|
| + size_t num_blocks;
|
| + const size_t bitmaplen = (num_histograms + 7) >> 3;
|
| + double* insert_cost = new double[kSize * num_histograms];
|
| + double *cost = new double[num_histograms];
|
| + uint8_t* switch_signal = new uint8_t[data.size() * bitmaplen];
|
| + uint16_t* new_id = new uint16_t[num_histograms];
|
| + for (size_t i = 0; i < 10; ++i) {
|
| + num_blocks = FindBlocks(&data[0], data.size(),
|
| + block_switch_cost,
|
| + num_histograms, histograms,
|
| + insert_cost, cost, switch_signal,
|
| + &block_ids[0]);
|
| + num_histograms = RemapBlockIds(&block_ids[0], data.size(),
|
| + new_id, num_histograms);
|
| + BuildBlockHistograms(&data[0], data.size(), &block_ids[0],
|
| + num_histograms, histograms);
|
| + }
|
| + delete[] insert_cost;
|
| + delete[] cost;
|
| + delete[] switch_signal;
|
| + delete[] new_id;
|
| + delete[] histograms;
|
| + ClusterBlocks<Histogram<kSize> >(&data[0], data.size(), num_blocks,
|
| + &block_ids[0], split);
|
| +}
|
| +
|
| +void SplitBlock(const Command* cmds,
|
| + const size_t num_commands,
|
| + const uint8_t* data,
|
| + const size_t pos,
|
| + const size_t mask,
|
| + BlockSplit* literal_split,
|
| + BlockSplit* insert_and_copy_split,
|
| + BlockSplit* dist_split) {
|
| + {
|
| + // Create a continuous array of literals.
|
| + std::vector<uint8_t> literals;
|
| + CopyLiteralsToByteArray(cmds, num_commands, data, pos, mask, &literals);
|
| + // Create the block split on the array of literals.
|
| + // Literal histograms have alphabet size 256.
|
| + SplitByteVector<256>(
|
| + literals,
|
| + kSymbolsPerLiteralHistogram, kMaxLiteralHistograms,
|
| + kLiteralStrideLength, kLiteralBlockSwitchCost,
|
| + literal_split);
|
| + }
|
| +
|
| + {
|
| + // Compute prefix codes for commands.
|
| + std::vector<uint16_t> insert_and_copy_codes(num_commands);
|
| + for (size_t i = 0; i < num_commands; ++i) {
|
| + insert_and_copy_codes[i] = cmds[i].cmd_prefix_;
|
| + }
|
| + // Create the block split on the array of command prefixes.
|
| + SplitByteVector<kNumCommandPrefixes>(
|
| + insert_and_copy_codes,
|
| + kSymbolsPerCommandHistogram, kMaxCommandHistograms,
|
| + kCommandStrideLength, kCommandBlockSwitchCost,
|
| + insert_and_copy_split);
|
| + }
|
| +
|
| + {
|
| + // Create a continuous array of distance prefixes.
|
| + std::vector<uint16_t> distance_prefixes(num_commands);
|
| + size_t pos = 0;
|
| + for (size_t i = 0; i < num_commands; ++i) {
|
| + const Command& cmd = cmds[i];
|
| + if (cmd.copy_len() && cmd.cmd_prefix_ >= 128) {
|
| + distance_prefixes[pos++] = cmd.dist_prefix_;
|
| + }
|
| + }
|
| + distance_prefixes.resize(pos);
|
| + // Create the block split on the array of distance prefixes.
|
| + SplitByteVector<kNumDistancePrefixes>(
|
| + distance_prefixes,
|
| + kSymbolsPerDistanceHistogram, kMaxCommandHistograms,
|
| + kCommandStrideLength, kDistanceBlockSwitchCost,
|
| + dist_split);
|
| + }
|
| +}
|
| +
|
| +} // namespace brotli
|
|
|