Update brotli to v1.0.0-snapshot.

third_party/brotli/enc/block_splitter_inc.h

+/* NOLINT(build/header_guard) */
+/* Copyright 2013 Google Inc. All Rights Reserved.
+
+   Distributed under MIT license.
+   See file LICENSE for detail or copy at https://opensource.org/licenses/MIT
+*/
+
+/* template parameters: FN, DataType */
+
+#define HistogramType FN(Histogram)
+
+static void FN(InitialEntropyCodes)(const DataType* data, size_t length,
+                                    size_t stride,
+                                    size_t num_histograms,
+                                    HistogramType* histograms) {
+  unsigned int seed = 7;
+  size_t block_length = length / num_histograms;
+  size_t i;
+  FN(ClearHistograms)(histograms, num_histograms);
+  for (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;
+    }
+    FN(HistogramAddVector)(&histograms[i], data + pos, stride);
+  }
+}
+
+static void FN(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);
+  }
+  FN(HistogramAddVector)(sample, data + pos, stride);
+}
+
+static void FN(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;
+  size_t iter;
+  iters = ((iters + num_histograms - 1) / num_histograms) * num_histograms;
+  for (iter = 0; iter < iters; ++iter) {
+    HistogramType sample;
+    FN(HistogramClear)(&sample);
+    FN(RandomSample)(&seed, data, length, stride, &sample);
+    FN(HistogramAddHistogram)(&histograms[iter % num_histograms], &sample);
+  }
+}
+
+/* Assigns a block id from the range [0, num_histograms) 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. */
+static size_t FN(FindBlocks)(const DataType* data, const size_t length,
+                             const double block_switch_bitcost,
+                             const size_t num_histograms,
+                             const HistogramType* histograms,
+                             double* insert_cost,
+                             double* cost,
+                             uint8_t* switch_signal,
+                             uint8_t *block_id) {
+  const size_t data_size = FN(HistogramDataSize)();
+  const size_t bitmaplen = (num_histograms + 7) >> 3;
+  size_t num_blocks = 1;
+  size_t i;
+  size_t j;
+  assert(num_histograms <= 256);
+  if (num_histograms <= 1) {
+    for (i = 0; i < length; ++i) {
+      block_id[i] = 0;
+    }
+    return 1;
+  }
+  memset(insert_cost, 0, sizeof(insert_cost[0]) * data_size * num_histograms);
+  for (i = 0; i < num_histograms; ++i) {
+    insert_cost[i] = FastLog2((uint32_t)histograms[i].total_count_);
+  }
+  for (i = data_size; i != 0;) {
+    --i;
+    for (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 (i = 0; i < length; ++i) {
+    const size_t byte_ix = i;
+    size_t ix = byte_ix * bitmaplen;
+    size_t insert_cost_ix = data[byte_ix] * num_histograms;
+    double min_cost = 1e99;
+    double block_switch_cost = block_switch_bitcost;
+    size_t k;
+    for (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] = (uint8_t)k;
+      }
+    }
+    /* More blocks for the beginning. */
+    if (byte_ix < 2000) {
+      block_switch_cost *= 0.77 + 0.07 * (double)byte_ix / 2000;
+    }
+    for (k = 0; k < num_histograms; ++k) {
+      cost[k] -= min_cost;
+      if (cost[k] >= block_switch_cost) {
+        const uint8_t mask = (uint8_t)(1u << (k & 7));
+        cost[k] = block_switch_cost;
+        assert((k >> 3) < bitmaplen);
+        switch_signal[ix + (k >> 3)] |= mask;
+      }
+    }
+  }
+  {  /* 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];
+    while (byte_ix > 0) {
+      const uint8_t mask = (uint8_t)(1u << (cur_id & 7));
+      assert(((size_t)cur_id >> 3) < bitmaplen);
+      --byte_ix;
+      ix -= 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 FN(RemapBlockIds)(uint8_t* block_ids, const size_t length,
+                                uint16_t* new_id, const size_t num_histograms) {
+  static const uint16_t kInvalidId = 256;
+  uint16_t next_id = 0;
+  size_t i;
+  for (i = 0; i < num_histograms; ++i) {
+    new_id[i] = kInvalidId;
+  }
+  for (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 (i = 0; i < length; ++i) {
+    block_ids[i] = (uint8_t)new_id[block_ids[i]];
+    assert(block_ids[i] < num_histograms);
+  }
+  assert(next_id <= num_histograms);
+  return next_id;
+}
+
+static void FN(BuildBlockHistograms)(const DataType* data, const size_t length,
+                                     const uint8_t* block_ids,
+                                     const size_t num_histograms,
+                                     HistogramType* histograms) {
+  size_t i;
+  FN(ClearHistograms)(histograms, num_histograms);
+  for (i = 0; i < length; ++i) {
+    FN(HistogramAdd)(&histograms[block_ids[i]], data[i]);
+  }
+}
+
+static void FN(ClusterBlocks)(MemoryManager* m,
+                              const DataType* data, const size_t length,
+                              const size_t num_blocks,
+                              uint8_t* block_ids,
+                              BlockSplit* split) {
+  uint32_t* histogram_symbols = BROTLI_ALLOC(m, uint32_t, num_blocks);
+  uint32_t* block_lengths = BROTLI_ALLOC(m, uint32_t, num_blocks);
+  const size_t expected_num_clusters = CLUSTERS_PER_BATCH *
+      (num_blocks + HISTOGRAMS_PER_BATCH - 1) / HISTOGRAMS_PER_BATCH;
+  size_t all_histograms_size = 0;
+  size_t all_histograms_capacity = expected_num_clusters;
+  HistogramType* all_histograms =
+      BROTLI_ALLOC(m, HistogramType, all_histograms_capacity);
+  size_t cluster_size_size = 0;
+  size_t cluster_size_capacity = expected_num_clusters;
+  uint32_t* cluster_size = BROTLI_ALLOC(m, uint32_t, cluster_size_capacity);
+  size_t num_clusters = 0;
+  HistogramType* histograms = BROTLI_ALLOC(m, HistogramType,
+      BROTLI_MIN(size_t, num_blocks, HISTOGRAMS_PER_BATCH));
+  size_t max_num_pairs =
+      HISTOGRAMS_PER_BATCH * HISTOGRAMS_PER_BATCH / 2;
+  size_t pairs_capacity = max_num_pairs + 1;
+  HistogramPair* pairs = BROTLI_ALLOC(m, HistogramPair, pairs_capacity);
+  size_t pos = 0;
+  uint32_t* clusters;
+  size_t num_final_clusters;
+  static const uint32_t kInvalidIndex = BROTLI_UINT32_MAX;
+  uint32_t* new_index;
+  uint8_t max_type = 0;
+  size_t i;
+  uint32_t sizes[HISTOGRAMS_PER_BATCH] = { 0 };
+  uint32_t new_clusters[HISTOGRAMS_PER_BATCH] = { 0 };
+  uint32_t symbols[HISTOGRAMS_PER_BATCH] = { 0 };
+  uint32_t remap[HISTOGRAMS_PER_BATCH] = { 0 };
+
+  if (BROTLI_IS_OOM(m)) return;
+
+  memset(block_lengths, 0, num_blocks * sizeof(uint32_t));
+
+  {
+    size_t block_idx = 0;
+    for (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);
+  }
+
+  for (i = 0; i < num_blocks; i += HISTOGRAMS_PER_BATCH) {
+    const size_t num_to_combine =
+        BROTLI_MIN(size_t, num_blocks - i, HISTOGRAMS_PER_BATCH);
+    size_t num_new_clusters;
+    size_t j;
+    for (j = 0; j < num_to_combine; ++j) {
+      size_t k;
+      FN(HistogramClear)(&histograms[j]);
+      for (k = 0; k < block_lengths[i + j]; ++k) {
+        FN(HistogramAdd)(&histograms[j], data[pos++]);
+      }
+      histograms[j].bit_cost_ = FN(BrotliPopulationCost)(&histograms[j]);
+      new_clusters[j] = (uint32_t)j;
+      symbols[j] = (uint32_t)j;
+      sizes[j] = 1;
+    }
+    num_new_clusters = FN(BrotliHistogramCombine)(
+        histograms, sizes, symbols, new_clusters, pairs, num_to_combine,
+        num_to_combine, HISTOGRAMS_PER_BATCH, max_num_pairs);
+    BROTLI_ENSURE_CAPACITY(m, HistogramType, all_histograms,
+        all_histograms_capacity, all_histograms_size + num_new_clusters);
+    BROTLI_ENSURE_CAPACITY(m, uint32_t, cluster_size,
+        cluster_size_capacity, cluster_size_size + num_new_clusters);
+    if (BROTLI_IS_OOM(m)) return;
+    for (j = 0; j < num_new_clusters; ++j) {
+      all_histograms[all_histograms_size++] = histograms[new_clusters[j]];
+      cluster_size[cluster_size_size++] = sizes[new_clusters[j]];
+      remap[new_clusters[j]] = (uint32_t)j;
+    }
+    for (j = 0; j < num_to_combine; ++j) {
+      histogram_symbols[i + j] = (uint32_t)num_clusters + remap[symbols[j]];
+    }
+    num_clusters += num_new_clusters;
+    assert(num_clusters == cluster_size_size);
+    assert(num_clusters == all_histograms_size);
+  }
+  BROTLI_FREE(m, histograms);
+
+  max_num_pairs =
+      BROTLI_MIN(size_t, 64 * num_clusters, (num_clusters / 2) * num_clusters);
+  if (pairs_capacity < max_num_pairs + 1) {
+    BROTLI_FREE(m, pairs);
+    pairs = BROTLI_ALLOC(m, HistogramPair, max_num_pairs + 1);
+    if (BROTLI_IS_OOM(m)) return;
+  }
+
+  clusters = BROTLI_ALLOC(m, uint32_t, num_clusters);
+  if (BROTLI_IS_OOM(m)) return;
+  for (i = 0; i < num_clusters; ++i) {
+    clusters[i] = (uint32_t)i;
+  }
+  num_final_clusters = FN(BrotliHistogramCombine)(
+      all_histograms, cluster_size, histogram_symbols, clusters, pairs,
+      num_clusters, num_blocks, BROTLI_MAX_NUMBER_OF_BLOCK_TYPES,
+      max_num_pairs);
+  BROTLI_FREE(m, pairs);
+  BROTLI_FREE(m, cluster_size);
+
+  new_index = BROTLI_ALLOC(m, uint32_t, num_clusters);
+  if (BROTLI_IS_OOM(m)) return;
+  for (i = 0; i < num_clusters; ++i) new_index[i] = kInvalidIndex;
+  pos = 0;
+  {
+    uint32_t next_index = 0;
+    for (i = 0; i < num_blocks; ++i) {
+      HistogramType histo;
+      size_t j;
+      uint32_t best_out;
+      double best_bits;
+      FN(HistogramClear)(&histo);
+      for (j = 0; j < block_lengths[i]; ++j) {
+        FN(HistogramAdd)(&histo, data[pos++]);
+      }
+      best_out = (i == 0) ? histogram_symbols[0] : histogram_symbols[i - 1];
+      best_bits =
+          FN(BrotliHistogramBitCostDistance)(&histo, &all_histograms[best_out]);
+      for (j = 0; j < num_final_clusters; ++j) {
+        const double cur_bits = FN(BrotliHistogramBitCostDistance)(
+            &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++;
+      }
+    }
+  }
+  BROTLI_FREE(m, clusters);
+  BROTLI_FREE(m, all_histograms);
+  BROTLI_ENSURE_CAPACITY(
+      m, uint8_t, split->types, split->types_alloc_size, num_blocks);
+  BROTLI_ENSURE_CAPACITY(
+      m, uint32_t, split->lengths, split->lengths_alloc_size, num_blocks);
+  if (BROTLI_IS_OOM(m)) return;
+  {
+    uint32_t cur_length = 0;
+    size_t block_idx = 0;
+    for (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 = (uint8_t)new_index[histogram_symbols[i]];
+        split->types[block_idx] = id;
+        split->lengths[block_idx] = cur_length;
+        max_type = BROTLI_MAX(uint8_t, max_type, id);
+        cur_length = 0;
+        ++block_idx;
+      }
+    }
+    split->num_blocks = block_idx;
+    split->num_types = (size_t)max_type + 1;
+  }
+  BROTLI_FREE(m, new_index);
+  BROTLI_FREE(m, block_lengths);
+  BROTLI_FREE(m, histogram_symbols);
+}
+
+static void FN(SplitByteVector)(MemoryManager* m,
+                                const DataType* data, const size_t length,
+                                const size_t literals_per_histogram,
+                                const size_t max_histograms,
+                                const size_t sampling_stride_length,
+                                const double block_switch_cost,
+                                const BrotliEncoderParams* params,
+                                BlockSplit* split) {
+  const size_t data_size = FN(HistogramDataSize)();
+  size_t num_histograms = length / literals_per_histogram + 1;
+  HistogramType* histograms;
+  if (num_histograms > max_histograms) {
+    num_histograms = max_histograms;
+  }
+  if (length == 0) {
+    split->num_types = 1;
+    return;
+  } else if (length < kMinLengthForBlockSplitting) {
+    BROTLI_ENSURE_CAPACITY(m, uint8_t,
+        split->types, split->types_alloc_size, split->num_blocks + 1);
+    BROTLI_ENSURE_CAPACITY(m, uint32_t,
+        split->lengths, split->lengths_alloc_size, split->num_blocks + 1);
+    if (BROTLI_IS_OOM(m)) return;
+    split->num_types = 1;
+    split->types[split->num_blocks] = 0;
+    split->lengths[split->num_blocks] = (uint32_t)length;
+    split->num_blocks++;
+    return;
+  }
+  histograms = BROTLI_ALLOC(m, HistogramType, num_histograms);
+  if (BROTLI_IS_OOM(m)) return;
+  /* Find good entropy codes. */
+  FN(InitialEntropyCodes)(data, length,
+                          sampling_stride_length,
+                          num_histograms, histograms);
+  FN(RefineEntropyCodes)(data, length,
+                         sampling_stride_length,
+                         num_histograms, histograms);
+  {
+    /* Find a good path through literals with the good entropy codes. */
+    uint8_t* block_ids = BROTLI_ALLOC(m, uint8_t, length);
+    size_t num_blocks;
+    const size_t bitmaplen = (num_histograms + 7) >> 3;
+    double* insert_cost = BROTLI_ALLOC(m, double, data_size * num_histograms);
+    double* cost = BROTLI_ALLOC(m, double, num_histograms);
+    uint8_t* switch_signal = BROTLI_ALLOC(m, uint8_t, length * bitmaplen);
+    uint16_t* new_id = BROTLI_ALLOC(m, uint16_t, num_histograms);
+    const size_t iters = params->quality < HQ_ZOPFLIFICATION_QUALITY ? 3 : 10;
+    size_t i;
+    if (BROTLI_IS_OOM(m)) return;
+    for (i = 0; i < iters; ++i) {
+      num_blocks = FN(FindBlocks)(data, length,
+                                  block_switch_cost,
+                                  num_histograms, histograms,
+                                  insert_cost, cost, switch_signal,
+                                  block_ids);
+      num_histograms = FN(RemapBlockIds)(block_ids, length,
+                                         new_id, num_histograms);
+      FN(BuildBlockHistograms)(data, length, block_ids,
+                               num_histograms, histograms);
+    }
+    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