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Unified Diff: third_party/brotli/enc/bit_cost_inc.h

Issue 2537133002: Update brotli to v1.0.0-snapshot. (Closed)
Patch Set: Fixed typo Created 4 years ago
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Index: third_party/brotli/enc/bit_cost_inc.h
diff --git a/third_party/brotli/enc/bit_cost.h b/third_party/brotli/enc/bit_cost_inc.h
similarity index 20%
copy from third_party/brotli/enc/bit_cost.h
copy to third_party/brotli/enc/bit_cost_inc.h
index 4652006864c581c6589b92e50932251fca5a9124..453c22604209327a8691e995a12b74a81d603754 100644
--- a/third_party/brotli/enc/bit_cost.h
+++ b/third_party/brotli/enc/bit_cost_inc.h
@@ -1,66 +1,29 @@
+/* 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
*/
-// Functions to estimate the bit cost of Huffman trees.
+/* template parameters: FN */
-#ifndef BROTLI_ENC_BIT_COST_H_
-#define BROTLI_ENC_BIT_COST_H_
+#define HistogramType FN(Histogram)
-#include "./entropy_encode.h"
-#include "./fast_log.h"
-#include "./types.h"
-
-namespace brotli {
-
-static inline double ShannonEntropy(const uint32_t *population, size_t size,
- size_t *total) {
- size_t sum = 0;
- double retval = 0;
- const uint32_t *population_end = population + size;
- size_t p;
- if (size & 1) {
- goto odd_number_of_elements_left;
- }
- while (population < population_end) {
- p = *population++;
- sum += p;
- retval -= static_cast<double>(p) * FastLog2(p);
- odd_number_of_elements_left:
- p = *population++;
- sum += p;
- retval -= static_cast<double>(p) * FastLog2(p);
- }
- if (sum) retval += static_cast<double>(sum) * FastLog2(sum);
- *total = sum;
- return retval;
-}
-
-static inline double BitsEntropy(const uint32_t *population, size_t size) {
- size_t sum;
- double retval = ShannonEntropy(population, size, &sum);
- if (retval < sum) {
- // At least one bit per literal is needed.
- retval = static_cast<double>(sum);
- }
- return retval;
-}
-
-template<int kSize>
-double PopulationCost(const Histogram<kSize>& histogram) {
+double FN(BrotliPopulationCost)(const HistogramType* histogram) {
static const double kOneSymbolHistogramCost = 12;
static const double kTwoSymbolHistogramCost = 20;
static const double kThreeSymbolHistogramCost = 28;
static const double kFourSymbolHistogramCost = 37;
- if (histogram.total_count_ == 0) {
+ const size_t data_size = FN(HistogramDataSize)();
+ int count = 0;
+ size_t s[5];
+ double bits = 0.0;
+ size_t i;
+ if (histogram->total_count_ == 0) {
return kOneSymbolHistogramCost;
}
- int count = 0;
- int s[5];
- for (int i = 0; i < kSize; ++i) {
- if (histogram.data_[i] > 0) {
+ for (i = 0; i < data_size; ++i) {
+ if (histogram->data_[i] > 0) {
s[count] = i;
++count;
if (count > 4) break;
@@ -70,92 +33,95 @@ double PopulationCost(const Histogram<kSize>& histogram) {
return kOneSymbolHistogramCost;
}
if (count == 2) {
- return (kTwoSymbolHistogramCost +
- static_cast<double>(histogram.total_count_));
+ return (kTwoSymbolHistogramCost + (double)histogram->total_count_);
}
if (count == 3) {
- const uint32_t histo0 = histogram.data_[s[0]];
- const uint32_t histo1 = histogram.data_[s[1]];
- const uint32_t histo2 = histogram.data_[s[2]];
- const uint32_t histomax = std::max(histo0, std::max(histo1, histo2));
+ const uint32_t histo0 = histogram->data_[s[0]];
+ const uint32_t histo1 = histogram->data_[s[1]];
+ const uint32_t histo2 = histogram->data_[s[2]];
+ const uint32_t histomax =
+ BROTLI_MAX(uint32_t, histo0, BROTLI_MAX(uint32_t, histo1, histo2));
return (kThreeSymbolHistogramCost +
2 * (histo0 + histo1 + histo2) - histomax);
}
if (count == 4) {
uint32_t histo[4];
- for (int i = 0; i < 4; ++i) {
- histo[i] = histogram.data_[s[i]];
+ uint32_t h23;
+ uint32_t histomax;
+ for (i = 0; i < 4; ++i) {
+ histo[i] = histogram->data_[s[i]];
}
- // Sort
- for (int i = 0; i < 4; ++i) {
- for (int j = i + 1; j < 4; ++j) {
+ /* Sort */
+ for (i = 0; i < 4; ++i) {
+ size_t j;
+ for (j = i + 1; j < 4; ++j) {
if (histo[j] > histo[i]) {
- std::swap(histo[j], histo[i]);
+ BROTLI_SWAP(uint32_t, histo, j, i);
}
}
}
- const uint32_t h23 = histo[2] + histo[3];
- const uint32_t histomax = std::max(h23, histo[0]);
+ h23 = histo[2] + histo[3];
+ histomax = BROTLI_MAX(uint32_t, h23, histo[0]);
return (kFourSymbolHistogramCost +
3 * h23 + 2 * (histo[0] + histo[1]) - histomax);
}
- // In this loop we compute the entropy of the histogram and simultaneously
- // build a simplified histogram of the code length codes where we use the
- // zero repeat code 17, but we don't use the non-zero repeat code 16.
- double bits = 0;
- size_t max_depth = 1;
- uint32_t depth_histo[kCodeLengthCodes] = { 0 };
- const double log2total = FastLog2(histogram.total_count_);
- for (size_t i = 0; i < kSize;) {
- if (histogram.data_[i] > 0) {
- // Compute -log2(P(symbol)) = -log2(count(symbol)/total_count) =
- // = log2(total_count) - log2(count(symbol))
- double log2p = log2total - FastLog2(histogram.data_[i]);
- // Approximate the bit depth by round(-log2(P(symbol)))
- size_t depth = static_cast<size_t>(log2p + 0.5);
- bits += histogram.data_[i] * log2p;
- if (depth > 15) {
- depth = 15;
- }
- if (depth > max_depth) {
- max_depth = depth;
- }
- ++depth_histo[depth];
- ++i;
- } else {
- // Compute the run length of zeros and add the appropriate number of 0 and
- // 17 code length codes to the code length code histogram.
- uint32_t reps = 1;
- for (size_t k = i + 1; k < kSize && histogram.data_[k] == 0; ++k) {
- ++reps;
- }
- i += reps;
- if (i == kSize) {
- // Don't add any cost for the last zero run, since these are encoded
- // only implicitly.
- break;
- }
- if (reps < 3) {
- depth_histo[0] += reps;
+ {
+ /* In this loop we compute the entropy of the histogram and simultaneously
+ build a simplified histogram of the code length codes where we use the
+ zero repeat code 17, but we don't use the non-zero repeat code 16. */
+ size_t max_depth = 1;
+ uint32_t depth_histo[BROTLI_CODE_LENGTH_CODES] = { 0 };
+ const double log2total = FastLog2(histogram->total_count_);
+ for (i = 0; i < data_size;) {
+ if (histogram->data_[i] > 0) {
+ /* Compute -log2(P(symbol)) = -log2(count(symbol)/total_count) =
+ = log2(total_count) - log2(count(symbol)) */
+ double log2p = log2total - FastLog2(histogram->data_[i]);
+ /* Approximate the bit depth by round(-log2(P(symbol))) */
+ size_t depth = (size_t)(log2p + 0.5);
+ bits += histogram->data_[i] * log2p;
+ if (depth > 15) {
+ depth = 15;
+ }
+ if (depth > max_depth) {
+ max_depth = depth;
+ }
+ ++depth_histo[depth];
+ ++i;
} else {
- reps -= 2;
- while (reps > 0) {
- ++depth_histo[17];
- // Add the 3 extra bits for the 17 code length code.
- bits += 3;
- reps >>= 3;
+ /* Compute the run length of zeros and add the appropriate number of 0
+ and 17 code length codes to the code length code histogram. */
+ uint32_t reps = 1;
+ size_t k;
+ for (k = i + 1; k < data_size && histogram->data_[k] == 0; ++k) {
+ ++reps;
+ }
+ i += reps;
+ if (i == data_size) {
+ /* Don't add any cost for the last zero run, since these are encoded
+ only implicitly. */
+ break;
+ }
+ if (reps < 3) {
+ depth_histo[0] += reps;
+ } else {
+ reps -= 2;
+ while (reps > 0) {
+ ++depth_histo[BROTLI_REPEAT_ZERO_CODE_LENGTH];
+ /* Add the 3 extra bits for the 17 code length code. */
+ bits += 3;
+ reps >>= 3;
+ }
}
}
}
+ /* Add the estimated encoding cost of the code length code histogram. */
+ bits += (double)(18 + 2 * max_depth);
+ /* Add the entropy of the code length code histogram. */
+ bits += BitsEntropy(depth_histo, BROTLI_CODE_LENGTH_CODES);
}
- // Add the estimated encoding cost of the code length code histogram.
- bits += static_cast<double>(18 + 2 * max_depth);
- // Add the entropy of the code length code histogram.
- bits += BitsEntropy(depth_histo, kCodeLengthCodes);
return bits;
}
-} // namespace brotli
-
-#endif // BROTLI_ENC_BIT_COST_H_
+#undef HistogramType
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