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1 /* NOLINT(build/header_guard) */
2 /* Copyright 2013 Google Inc. All Rights Reserved.
3 
4    Distributed under MIT license.
5    See file LICENSE for detail or copy at https://opensource.org/licenses/MIT
6 */
7 
8 /* template parameters: FN, DataType */
9 
10 #define HistogramType FN(Histogram)
11 
FN(InitialEntropyCodes)12 static void FN(InitialEntropyCodes)(const DataType* data, size_t length,
13                                     size_t stride,
14                                     size_t num_histograms,
15                                     HistogramType* histograms) {
16   uint32_t seed = 7;
17   size_t block_length = length / num_histograms;
18   size_t i;
19   FN(ClearHistograms)(histograms, num_histograms);
20   for (i = 0; i < num_histograms; ++i) {
21     size_t pos = length * i / num_histograms;
22     if (i != 0) {
23       pos += MyRand(&seed) % block_length;
24     }
25     if (pos + stride >= length) {
26       pos = length - stride - 1;
27     }
28     FN(HistogramAddVector)(&histograms[i], data + pos, stride);
29   }
30 }
31 
FN(RandomSample)32 static void FN(RandomSample)(uint32_t* seed,
33                              const DataType* data,
34                              size_t length,
35                              size_t stride,
36                              HistogramType* sample) {
37   size_t pos = 0;
38   if (stride >= length) {
39     stride = length;
40   } else {
41     pos = MyRand(seed) % (length - stride + 1);
42   }
43   FN(HistogramAddVector)(sample, data + pos, stride);
44 }
45 
FN(RefineEntropyCodes)46 static void FN(RefineEntropyCodes)(const DataType* data, size_t length,
47                                    size_t stride,
48                                    size_t num_histograms,
49                                    HistogramType* histograms) {
50   size_t iters =
51       kIterMulForRefining * length / stride + kMinItersForRefining;
52   uint32_t seed = 7;
53   size_t iter;
54   iters = ((iters + num_histograms - 1) / num_histograms) * num_histograms;
55   for (iter = 0; iter < iters; ++iter) {
56     HistogramType sample;
57     FN(HistogramClear)(&sample);
58     FN(RandomSample)(&seed, data, length, stride, &sample);
59     FN(HistogramAddHistogram)(&histograms[iter % num_histograms], &sample);
60   }
61 }
62 
63 /* Assigns a block id from the range [0, num_histograms) to each data element
64    in data[0..length) and fills in block_id[0..length) with the assigned values.
65    Returns the number of blocks, i.e. one plus the number of block switches. */
FN(FindBlocks)66 static size_t FN(FindBlocks)(const DataType* data, const size_t length,
67                              const double block_switch_bitcost,
68                              const size_t num_histograms,
69                              const HistogramType* histograms,
70                              double* insert_cost,
71                              double* cost,
72                              uint8_t* switch_signal,
73                              uint8_t *block_id) {
74   const size_t data_size = FN(HistogramDataSize)();
75   const size_t bitmaplen = (num_histograms + 7) >> 3;
76   size_t num_blocks = 1;
77   size_t i;
78   size_t j;
79   assert(num_histograms <= 256);
80   if (num_histograms <= 1) {
81     for (i = 0; i < length; ++i) {
82       block_id[i] = 0;
83     }
84     return 1;
85   }
86   memset(insert_cost, 0, sizeof(insert_cost[0]) * data_size * num_histograms);
87   for (i = 0; i < num_histograms; ++i) {
88     insert_cost[i] = FastLog2((uint32_t)histograms[i].total_count_);
89   }
90   for (i = data_size; i != 0;) {
91     --i;
92     for (j = 0; j < num_histograms; ++j) {
93       insert_cost[i * num_histograms + j] =
94           insert_cost[j] - BitCost(histograms[j].data_[i]);
95     }
96   }
97   memset(cost, 0, sizeof(cost[0]) * num_histograms);
98   memset(switch_signal, 0, sizeof(switch_signal[0]) * length * bitmaplen);
99   /* After each iteration of this loop, cost[k] will contain the difference
100      between the minimum cost of arriving at the current byte position using
101      entropy code k, and the minimum cost of arriving at the current byte
102      position. This difference is capped at the block switch cost, and if it
103      reaches block switch cost, it means that when we trace back from the last
104      position, we need to switch here. */
105   for (i = 0; i < length; ++i) {
106     const size_t byte_ix = i;
107     size_t ix = byte_ix * bitmaplen;
108     size_t insert_cost_ix = data[byte_ix] * num_histograms;
109     double min_cost = 1e99;
110     double block_switch_cost = block_switch_bitcost;
111     size_t k;
112     for (k = 0; k < num_histograms; ++k) {
113       /* We are coding the symbol in data[byte_ix] with entropy code k. */
114       cost[k] += insert_cost[insert_cost_ix + k];
115       if (cost[k] < min_cost) {
116         min_cost = cost[k];
117         block_id[byte_ix] = (uint8_t)k;
118       }
119     }
120     /* More blocks for the beginning. */
121     if (byte_ix < 2000) {
122       block_switch_cost *= 0.77 + 0.07 * (double)byte_ix / 2000;
123     }
124     for (k = 0; k < num_histograms; ++k) {
125       cost[k] -= min_cost;
126       if (cost[k] >= block_switch_cost) {
127         const uint8_t mask = (uint8_t)(1u << (k & 7));
128         cost[k] = block_switch_cost;
129         assert((k >> 3) < bitmaplen);
130         switch_signal[ix + (k >> 3)] |= mask;
131       }
132     }
133   }
134   {  /* Trace back from the last position and switch at the marked places. */
135     size_t byte_ix = length - 1;
136     size_t ix = byte_ix * bitmaplen;
137     uint8_t cur_id = block_id[byte_ix];
138     while (byte_ix > 0) {
139       const uint8_t mask = (uint8_t)(1u << (cur_id & 7));
140       assert(((size_t)cur_id >> 3) < bitmaplen);
141       --byte_ix;
142       ix -= bitmaplen;
143       if (switch_signal[ix + (cur_id >> 3)] & mask) {
144         if (cur_id != block_id[byte_ix]) {
145           cur_id = block_id[byte_ix];
146           ++num_blocks;
147         }
148       }
149       block_id[byte_ix] = cur_id;
150     }
151   }
152   return num_blocks;
153 }
154 
FN(RemapBlockIds)155 static size_t FN(RemapBlockIds)(uint8_t* block_ids, const size_t length,
156                                 uint16_t* new_id, const size_t num_histograms) {
157   static const uint16_t kInvalidId = 256;
158   uint16_t next_id = 0;
159   size_t i;
160   for (i = 0; i < num_histograms; ++i) {
161     new_id[i] = kInvalidId;
162   }
163   for (i = 0; i < length; ++i) {
164     assert(block_ids[i] < num_histograms);
165     if (new_id[block_ids[i]] == kInvalidId) {
166       new_id[block_ids[i]] = next_id++;
167     }
168   }
169   for (i = 0; i < length; ++i) {
170     block_ids[i] = (uint8_t)new_id[block_ids[i]];
171     assert(block_ids[i] < num_histograms);
172   }
173   assert(next_id <= num_histograms);
174   return next_id;
175 }
176 
FN(BuildBlockHistograms)177 static void FN(BuildBlockHistograms)(const DataType* data, const size_t length,
178                                      const uint8_t* block_ids,
179                                      const size_t num_histograms,
180                                      HistogramType* histograms) {
181   size_t i;
182   FN(ClearHistograms)(histograms, num_histograms);
183   for (i = 0; i < length; ++i) {
184     FN(HistogramAdd)(&histograms[block_ids[i]], data[i]);
185   }
186 }
187 
FN(ClusterBlocks)188 static void FN(ClusterBlocks)(MemoryManager* m,
189                               const DataType* data, const size_t length,
190                               const size_t num_blocks,
191                               uint8_t* block_ids,
192                               BlockSplit* split) {
193   uint32_t* histogram_symbols = BROTLI_ALLOC(m, uint32_t, num_blocks);
194   uint32_t* block_lengths = BROTLI_ALLOC(m, uint32_t, num_blocks);
195   const size_t expected_num_clusters = CLUSTERS_PER_BATCH *
196       (num_blocks + HISTOGRAMS_PER_BATCH - 1) / HISTOGRAMS_PER_BATCH;
197   size_t all_histograms_size = 0;
198   size_t all_histograms_capacity = expected_num_clusters;
199   HistogramType* all_histograms =
200       BROTLI_ALLOC(m, HistogramType, all_histograms_capacity);
201   size_t cluster_size_size = 0;
202   size_t cluster_size_capacity = expected_num_clusters;
203   uint32_t* cluster_size = BROTLI_ALLOC(m, uint32_t, cluster_size_capacity);
204   size_t num_clusters = 0;
205   HistogramType* histograms = BROTLI_ALLOC(m, HistogramType,
206       BROTLI_MIN(size_t, num_blocks, HISTOGRAMS_PER_BATCH));
207   size_t max_num_pairs =
208       HISTOGRAMS_PER_BATCH * HISTOGRAMS_PER_BATCH / 2;
209   size_t pairs_capacity = max_num_pairs + 1;
210   HistogramPair* pairs = BROTLI_ALLOC(m, HistogramPair, pairs_capacity);
211   size_t pos = 0;
212   uint32_t* clusters;
213   size_t num_final_clusters;
214   static const uint32_t kInvalidIndex = BROTLI_UINT32_MAX;
215   uint32_t* new_index;
216   size_t i;
217   uint32_t sizes[HISTOGRAMS_PER_BATCH] = { 0 };
218   uint32_t new_clusters[HISTOGRAMS_PER_BATCH] = { 0 };
219   uint32_t symbols[HISTOGRAMS_PER_BATCH] = { 0 };
220   uint32_t remap[HISTOGRAMS_PER_BATCH] = { 0 };
221 
222   if (BROTLI_IS_OOM(m)) return;
223 
224   memset(block_lengths, 0, num_blocks * sizeof(uint32_t));
225 
226   {
227     size_t block_idx = 0;
228     for (i = 0; i < length; ++i) {
229       assert(block_idx < num_blocks);
230       ++block_lengths[block_idx];
231       if (i + 1 == length || block_ids[i] != block_ids[i + 1]) {
232         ++block_idx;
233       }
234     }
235     assert(block_idx == num_blocks);
236   }
237 
238   for (i = 0; i < num_blocks; i += HISTOGRAMS_PER_BATCH) {
239     const size_t num_to_combine =
240         BROTLI_MIN(size_t, num_blocks - i, HISTOGRAMS_PER_BATCH);
241     size_t num_new_clusters;
242     size_t j;
243     for (j = 0; j < num_to_combine; ++j) {
244       size_t k;
245       FN(HistogramClear)(&histograms[j]);
246       for (k = 0; k < block_lengths[i + j]; ++k) {
247         FN(HistogramAdd)(&histograms[j], data[pos++]);
248       }
249       histograms[j].bit_cost_ = FN(BrotliPopulationCost)(&histograms[j]);
250       new_clusters[j] = (uint32_t)j;
251       symbols[j] = (uint32_t)j;
252       sizes[j] = 1;
253     }
254     num_new_clusters = FN(BrotliHistogramCombine)(
255         histograms, sizes, symbols, new_clusters, pairs, num_to_combine,
256         num_to_combine, HISTOGRAMS_PER_BATCH, max_num_pairs);
257     BROTLI_ENSURE_CAPACITY(m, HistogramType, all_histograms,
258         all_histograms_capacity, all_histograms_size + num_new_clusters);
259     BROTLI_ENSURE_CAPACITY(m, uint32_t, cluster_size,
260         cluster_size_capacity, cluster_size_size + num_new_clusters);
261     if (BROTLI_IS_OOM(m)) return;
262     for (j = 0; j < num_new_clusters; ++j) {
263       all_histograms[all_histograms_size++] = histograms[new_clusters[j]];
264       cluster_size[cluster_size_size++] = sizes[new_clusters[j]];
265       remap[new_clusters[j]] = (uint32_t)j;
266     }
267     for (j = 0; j < num_to_combine; ++j) {
268       histogram_symbols[i + j] = (uint32_t)num_clusters + remap[symbols[j]];
269     }
270     num_clusters += num_new_clusters;
271     assert(num_clusters == cluster_size_size);
272     assert(num_clusters == all_histograms_size);
273   }
274   BROTLI_FREE(m, histograms);
275 
276   max_num_pairs =
277       BROTLI_MIN(size_t, 64 * num_clusters, (num_clusters / 2) * num_clusters);
278   if (pairs_capacity < max_num_pairs + 1) {
279     BROTLI_FREE(m, pairs);
280     pairs = BROTLI_ALLOC(m, HistogramPair, max_num_pairs + 1);
281     if (BROTLI_IS_OOM(m)) return;
282   }
283 
284   clusters = BROTLI_ALLOC(m, uint32_t, num_clusters);
285   if (BROTLI_IS_OOM(m)) return;
286   for (i = 0; i < num_clusters; ++i) {
287     clusters[i] = (uint32_t)i;
288   }
289   num_final_clusters = FN(BrotliHistogramCombine)(
290       all_histograms, cluster_size, histogram_symbols, clusters, pairs,
291       num_clusters, num_blocks, BROTLI_MAX_NUMBER_OF_BLOCK_TYPES,
292       max_num_pairs);
293   BROTLI_FREE(m, pairs);
294   BROTLI_FREE(m, cluster_size);
295 
296   new_index = BROTLI_ALLOC(m, uint32_t, num_clusters);
297   if (BROTLI_IS_OOM(m)) return;
298   for (i = 0; i < num_clusters; ++i) new_index[i] = kInvalidIndex;
299   pos = 0;
300   {
301     uint32_t next_index = 0;
302     for (i = 0; i < num_blocks; ++i) {
303       HistogramType histo;
304       size_t j;
305       uint32_t best_out;
306       double best_bits;
307       FN(HistogramClear)(&histo);
308       for (j = 0; j < block_lengths[i]; ++j) {
309         FN(HistogramAdd)(&histo, data[pos++]);
310       }
311       best_out = (i == 0) ? histogram_symbols[0] : histogram_symbols[i - 1];
312       best_bits =
313           FN(BrotliHistogramBitCostDistance)(&histo, &all_histograms[best_out]);
314       for (j = 0; j < num_final_clusters; ++j) {
315         const double cur_bits = FN(BrotliHistogramBitCostDistance)(
316             &histo, &all_histograms[clusters[j]]);
317         if (cur_bits < best_bits) {
318           best_bits = cur_bits;
319           best_out = clusters[j];
320         }
321       }
322       histogram_symbols[i] = best_out;
323       if (new_index[best_out] == kInvalidIndex) {
324         new_index[best_out] = next_index++;
325       }
326     }
327   }
328   BROTLI_FREE(m, clusters);
329   BROTLI_FREE(m, all_histograms);
330   BROTLI_ENSURE_CAPACITY(
331       m, uint8_t, split->types, split->types_alloc_size, num_blocks);
332   BROTLI_ENSURE_CAPACITY(
333       m, uint32_t, split->lengths, split->lengths_alloc_size, num_blocks);
334   if (BROTLI_IS_OOM(m)) return;
335   {
336     uint32_t cur_length = 0;
337     size_t block_idx = 0;
338     uint8_t max_type = 0;
339     for (i = 0; i < num_blocks; ++i) {
340       cur_length += block_lengths[i];
341       if (i + 1 == num_blocks ||
342           histogram_symbols[i] != histogram_symbols[i + 1]) {
343         const uint8_t id = (uint8_t)new_index[histogram_symbols[i]];
344         split->types[block_idx] = id;
345         split->lengths[block_idx] = cur_length;
346         max_type = BROTLI_MAX(uint8_t, max_type, id);
347         cur_length = 0;
348         ++block_idx;
349       }
350     }
351     split->num_blocks = block_idx;
352     split->num_types = (size_t)max_type + 1;
353   }
354   BROTLI_FREE(m, new_index);
355   BROTLI_FREE(m, block_lengths);
356   BROTLI_FREE(m, histogram_symbols);
357 }
358 
FN(SplitByteVector)359 static void FN(SplitByteVector)(MemoryManager* m,
360                                 const DataType* data, const size_t length,
361                                 const size_t literals_per_histogram,
362                                 const size_t max_histograms,
363                                 const size_t sampling_stride_length,
364                                 const double block_switch_cost,
365                                 const BrotliEncoderParams* params,
366                                 BlockSplit* split) {
367   const size_t data_size = FN(HistogramDataSize)();
368   size_t num_histograms = length / literals_per_histogram + 1;
369   HistogramType* histograms;
370   if (num_histograms > max_histograms) {
371     num_histograms = max_histograms;
372   }
373   if (length == 0) {
374     split->num_types = 1;
375     return;
376   } else if (length < kMinLengthForBlockSplitting) {
377     BROTLI_ENSURE_CAPACITY(m, uint8_t,
378         split->types, split->types_alloc_size, split->num_blocks + 1);
379     BROTLI_ENSURE_CAPACITY(m, uint32_t,
380         split->lengths, split->lengths_alloc_size, split->num_blocks + 1);
381     if (BROTLI_IS_OOM(m)) return;
382     split->num_types = 1;
383     split->types[split->num_blocks] = 0;
384     split->lengths[split->num_blocks] = (uint32_t)length;
385     split->num_blocks++;
386     return;
387   }
388   histograms = BROTLI_ALLOC(m, HistogramType, num_histograms);
389   if (BROTLI_IS_OOM(m)) return;
390   /* Find good entropy codes. */
391   FN(InitialEntropyCodes)(data, length,
392                           sampling_stride_length,
393                           num_histograms, histograms);
394   FN(RefineEntropyCodes)(data, length,
395                          sampling_stride_length,
396                          num_histograms, histograms);
397   {
398     /* Find a good path through literals with the good entropy codes. */
399     uint8_t* block_ids = BROTLI_ALLOC(m, uint8_t, length);
400     size_t num_blocks = 0;
401     const size_t bitmaplen = (num_histograms + 7) >> 3;
402     double* insert_cost = BROTLI_ALLOC(m, double, data_size * num_histograms);
403     double* cost = BROTLI_ALLOC(m, double, num_histograms);
404     uint8_t* switch_signal = BROTLI_ALLOC(m, uint8_t, length * bitmaplen);
405     uint16_t* new_id = BROTLI_ALLOC(m, uint16_t, num_histograms);
406     const size_t iters = params->quality < HQ_ZOPFLIFICATION_QUALITY ? 3 : 10;
407     size_t i;
408     if (BROTLI_IS_OOM(m)) return;
409     for (i = 0; i < iters; ++i) {
410       num_blocks = FN(FindBlocks)(data, length,
411                                   block_switch_cost,
412                                   num_histograms, histograms,
413                                   insert_cost, cost, switch_signal,
414                                   block_ids);
415       num_histograms = FN(RemapBlockIds)(block_ids, length,
416                                          new_id, num_histograms);
417       FN(BuildBlockHistograms)(data, length, block_ids,
418                                num_histograms, histograms);
419     }
420     BROTLI_FREE(m, insert_cost);
421     BROTLI_FREE(m, cost);
422     BROTLI_FREE(m, switch_signal);
423     BROTLI_FREE(m, new_id);
424     BROTLI_FREE(m, histograms);
425     FN(ClusterBlocks)(m, data, length, num_blocks, block_ids, split);
426     if (BROTLI_IS_OOM(m)) return;
427     BROTLI_FREE(m, block_ids);
428   }
429 }
430 
431 #undef HistogramType
432