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// Copyright 2013 Google Inc. All Rights Reserved.
//
// 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.
//
// Block split point selection utilities.
#include "./block_splitter.h"
#include <math.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <algorithm>
#include <map>
#include "./cluster.h"
#include "./command.h"
#include "./fast_log.h"
#include "./histogram.h"
namespace brotli {
static const int kMaxLiteralHistograms = 100;
static const int kMaxCommandHistograms = 50;
static const double kLiteralBlockSwitchCost = 28.1;
static const double kCommandBlockSwitchCost = 13.5;
static const double kDistanceBlockSwitchCost = 14.6;
static const int kLiteralStrideLength = 70;
static const int kCommandStrideLength = 40;
static const int kSymbolsPerLiteralHistogram = 544;
static const int kSymbolsPerCommandHistogram = 530;
static const int kSymbolsPerDistanceHistogram = 544;
static const int kMinLengthForBlockSplitting = 128;
static const int kIterMulForRefining = 2;
static const int kMinItersForRefining = 100;
void CopyLiteralsToByteArray(const Command* cmds,
const size_t num_commands,
const uint8_t* data,
std::vector<uint8_t>* literals) {
// Count how many we have.
size_t total_length = 0;
for (int 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 = 0;
for (int i = 0; i < num_commands && pos < total_length; ++i) {
memcpy(&(*literals)[pos], data + from_pos, cmds[i].insert_len_);
pos += cmds[i].insert_len_;
from_pos += cmds[i].insert_len_ + cmds[i].copy_len_;
}
}
void CopyCommandsToByteArray(const Command* cmds,
const size_t num_commands,
std::vector<uint16_t>* insert_and_copy_codes,
std::vector<uint8_t>* distance_prefixes) {
for (int i = 0; i < num_commands; ++i) {
const Command& cmd = cmds[i];
insert_and_copy_codes->push_back(cmd.cmd_prefix_);
if (cmd.copy_len_ > 0 && cmd.cmd_prefix_ >= 128) {
distance_prefixes->push_back(cmd.dist_prefix_);
}
}
}
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,
int literals_per_histogram,
int max_histograms,
size_t stride,
std::vector<HistogramType>* vec) {
int total_histograms = length / literals_per_histogram + 1;
if (total_histograms > max_histograms) {
total_histograms = max_histograms;
}
unsigned int seed = 7;
int block_length = length / total_histograms;
for (int i = 0; i < total_histograms; ++i) {
int pos = length * i / total_histograms;
if (i != 0) {
pos += MyRand(&seed) % block_length;
}
if (pos + stride >= length) {
pos = length - stride - 1;
}
HistogramType histo;
histo.Add(data + pos, stride);
vec->push_back(histo);
}
}
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,
std::vector<HistogramType>* vec) {
int iters =
kIterMulForRefining * length / stride + kMinItersForRefining;
unsigned int seed = 7;
iters = ((iters + vec->size() - 1) / vec->size()) * vec->size();
for (int iter = 0; iter < iters; ++iter) {
HistogramType sample;
RandomSample(&seed, data, length, stride, &sample);
int ix = iter % vec->size();
(*vec)[ix].AddHistogram(sample);
}
}
inline static float BitCost(int total, int count) {
return count == 0 ? FastLog2(total) + 2 : FastLog2(total) - FastLog2(count);
}
template<typename DataType, int kSize>
void FindBlocks(const DataType* data, const size_t length,
const double block_switch_bitcost,
const std::vector<Histogram<kSize> > &vec,
uint8_t *block_id) {
if (vec.size() <= 1) {
for (int i = 0; i < length; ++i) {
block_id[i] = 0;
}
return;
}
int vecsize = vec.size();
double* insert_cost = new double[kSize * vecsize];
memset(insert_cost, 0, sizeof(insert_cost[0]) * kSize * vecsize);
for (int i = 0; i < kSize; ++i) {
for (int j = 0; j < vecsize; ++j) {
insert_cost[i * vecsize + j] =
BitCost(vec[j].total_count_, vec[j].data_[i]);
}
}
double *cost = new double[vecsize];
memset(cost, 0, sizeof(cost[0]) * vecsize);
bool* switch_signal = new bool[length * vecsize];
memset(switch_signal, 0, sizeof(switch_signal[0]) * length * vecsize);
// 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) {
int ix = byte_ix * vecsize;
int insert_cost_ix = data[byte_ix] * vecsize;
double min_cost = 1e99;
for (int k = 0; k < vecsize; ++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] = k;
}
}
double block_switch_cost = block_switch_bitcost;
// More blocks for the beginning.
if (byte_ix < 2000) {
block_switch_cost *= 0.77 + 0.07 * byte_ix / 2000;
}
for (int k = 0; k < vecsize; ++k) {
cost[k] -= min_cost;
if (cost[k] >= block_switch_cost) {
cost[k] = block_switch_cost;
switch_signal[ix + k] = true;
}
}
}
// Now trace back from the last position and switch at the marked places.
int byte_ix = length - 1;
int ix = byte_ix * vecsize;
int cur_id = block_id[byte_ix];
while (byte_ix > 0) {
--byte_ix;
ix -= vecsize;
if (switch_signal[ix + cur_id]) {
cur_id = block_id[byte_ix];
}
block_id[byte_ix] = cur_id;
}
delete[] insert_cost;
delete[] cost;
delete[] switch_signal;
}
int RemapBlockIds(uint8_t* block_ids, const size_t length) {
std::map<uint8_t, uint8_t> new_id;
int next_id = 0;
for (int i = 0; i < length; ++i) {
if (new_id.find(block_ids[i]) == new_id.end()) {
new_id[block_ids[i]] = next_id;
++next_id;
}
}
for (int i = 0; i < length; ++i) {
block_ids[i] = new_id[block_ids[i]];
}
return next_id;
}
template<typename HistogramType, typename DataType>
void BuildBlockHistograms(const DataType* data, const size_t length,
uint8_t* block_ids,
std::vector<HistogramType>* histograms) {
int num_types = RemapBlockIds(block_ids, length);
histograms->clear();
histograms->resize(num_types);
for (int 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,
uint8_t* block_ids) {
std::vector<HistogramType> histograms;
std::vector<int> block_index(length);
int cur_idx = 0;
HistogramType cur_histogram;
for (int i = 0; i < length; ++i) {
bool block_boundary = (i + 1 == length || block_ids[i] != block_ids[i + 1]);
block_index[i] = cur_idx;
cur_histogram.Add(data[i]);
if (block_boundary) {
histograms.push_back(cur_histogram);
cur_histogram.Clear();
++cur_idx;
}
}
std::vector<HistogramType> clustered_histograms;
std::vector<int> histogram_symbols;
// Block ids need to fit in one byte.
static const int kMaxNumberOfBlockTypes = 256;
ClusterHistograms(histograms, 1, histograms.size(),
kMaxNumberOfBlockTypes,
&clustered_histograms,
&histogram_symbols);
for (int i = 0; i < length; ++i) {
block_ids[i] = histogram_symbols[block_index[i]];
}
}
void BuildBlockSplit(const std::vector<uint8_t>& block_ids, BlockSplit* split) {
int cur_id = block_ids[0];
int cur_length = 1;
split->num_types = -1;
for (int i = 1; i < block_ids.size(); ++i) {
if (block_ids[i] != cur_id) {
split->types.push_back(cur_id);
split->lengths.push_back(cur_length);
split->num_types = std::max(split->num_types, cur_id);
cur_id = block_ids[i];
cur_length = 0;
}
++cur_length;
}
split->types.push_back(cur_id);
split->lengths.push_back(cur_length);
split->num_types = std::max(split->num_types, cur_id);
++split->num_types;
}
template<typename HistogramType, typename DataType>
void SplitByteVector(const std::vector<DataType>& data,
const int literals_per_histogram,
const int max_histograms,
const int 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(data.size());
return;
}
std::vector<HistogramType> histograms;
// Find good entropy codes.
InitialEntropyCodes(data.data(), data.size(),
literals_per_histogram,
max_histograms,
sampling_stride_length,
&histograms);
RefineEntropyCodes(data.data(), data.size(),
sampling_stride_length,
&histograms);
// Find a good path through literals with the good entropy codes.
std::vector<uint8_t> block_ids(data.size());
for (int i = 0; i < 10; ++i) {
FindBlocks(data.data(), data.size(),
block_switch_cost,
histograms,
&block_ids[0]);
BuildBlockHistograms(data.data(), data.size(), &block_ids[0], &histograms);
}
ClusterBlocks<HistogramType>(data.data(), data.size(), &block_ids[0]);
BuildBlockSplit(block_ids, split);
}
void SplitBlock(const Command* cmds,
const size_t num_commands,
const uint8_t* data,
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, &literals);
// Compute prefix codes for commands.
std::vector<uint16_t> insert_and_copy_codes;
std::vector<uint8_t> distance_prefixes;
CopyCommandsToByteArray(cmds, num_commands,
&insert_and_copy_codes,
&distance_prefixes);
SplitByteVector<HistogramLiteral>(
literals,
kSymbolsPerLiteralHistogram, kMaxLiteralHistograms,
kLiteralStrideLength, kLiteralBlockSwitchCost,
literal_split);
SplitByteVector<HistogramCommand>(
insert_and_copy_codes,
kSymbolsPerCommandHistogram, kMaxCommandHistograms,
kCommandStrideLength, kCommandBlockSwitchCost,
insert_and_copy_split);
SplitByteVector<HistogramDistance>(
distance_prefixes,
kSymbolsPerDistanceHistogram, kMaxCommandHistograms,
kCommandStrideLength, kDistanceBlockSwitchCost,
dist_split);
}
void SplitBlockByTotalLength(const Command* all_commands,
const size_t num_commands,
int input_size,
int target_length,
std::vector<std::vector<Command> >* blocks) {
int num_blocks = input_size / target_length + 1;
int length_limit = input_size / num_blocks + 1;
int total_length = 0;
std::vector<Command> cur_block;
for (int i = 0; i < num_commands; ++i) {
const Command& cmd = all_commands[i];
int cmd_length = cmd.insert_len_ + cmd.copy_len_;
if (total_length > length_limit) {
blocks->push_back(cur_block);
cur_block.clear();
total_length = 0;
}
cur_block.push_back(cmd);
total_length += cmd_length;
}
blocks->push_back(cur_block);
}
} // namespace brotli