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 |